Performance Analysis Of WIMAX And Its Perspective In Bangladesh

WiMax, the Worldwide Interoperability for Microwave Access, is a telecommunications technology aimed at providing wireless data over long distances in a variety of ways, from point-to-point links to full mobile cellular type access. It is based on the IEEE 802.16 standard, which is also called Wireless MAN. Wimax allows a user, for example, to browse the Internet on a laptop computer without physically connecting the laptop to a router or switch port via an Ethernet port. The name Wimax was created by the Wimax Forum, which was formed in June 2001 to promote conformance and interoperability of the standard. The forum describes Wimax as "   A standard-based technology enabling the delivery of last mile wireless broadband access as an alternative to cable and DSL." The industry trade group WiMAX Forum TM ( has defined WiMAX as a "last mile" broadband wireless access (BWA) alternative to cable modem service, Telephone Company Digital    Subscriber Line (DSL)or T1/E1service. The terms "fixed WiMAX", "mobile WiMAX", "802.16d" and "802.16e" are frequently used incorrectly.
Correct definitions are:                                                                                                           
1.1.1 802.16d: Strictly speaking, 802.16d has never existed as a standard. The standard is correctly called 802.16-2004. However, since this standard is frequently called 802.16d, that term is also used in this article to assist readability.
1.1.2 802.16eJust as 802.16d has never existed, a standard called 802.16e hasn't either. It's an amendment to 802.16-2004, so it is not a standard in its own right. It is properly referred to as 802.16e-2005.
1.1.3 Fixed WiMAX This is a phrase frequently used to refer to systems built using 802.16-2004 ('802.16d') as the air interface technology.
1.1.4 Mobile WiMAX A phrase frequently used to refer to systems built using 802.16e-2005 as the air interface technology. "Mobile WiMAX" implementations are therefore frequently used to deliver pure fixed services. Mobile WiMAX takes the fixed wireless application a step further and enables cell phone-like applications on a much larger scale. For example, mobile WiMAX enables streaming video to be broadcast from a speeding police or other emergency vehicle at over 70 MPH. It potentially replaces cell phones and mobile data offerings from cell phone operators such as EvDo, EvDv and HSDPA. In addition to being the final leg in a quadruple play, it offers superior building penetration and improved security measures over fixed WiMAX. Mobile WiMAX will be very valuable for emerging services such as mobile TV and gaming.
Visualize turning on an FM radio in your office. You receive information (news, weather, sports) from that service (the FM radio station) and hardware (the FM radio with attached antenna). WiMAX can be described as being somewhat similar. In place of a radio station there is a base station (radio and antenna) that transmits information (internet access, VOIP, IPTV) and the subscriber has a WiMAX CPE that receives the services. The major difference is that with WiMAX the service is two-way or interactive.


Fig 1.1: WiMAX as mobile data and cell phone bypass
1.2. Background on IEEE 802.16 and Wimax
The IEEE 802.16 group was formed in 1998 to develop an air-interface standard for wireless broadband. The group’s initial focus was the development of a LOS-based point-to-multipoint wireless broadband system for operation in the 10GHz–66GHz millimeter wave band. The resulting standard—the original 802.16 standard, completed in December 2001—was based on a single-carrier physical (PHY) layer with a burst time division multiplexed (TDM) MAC layer. Many of the concepts related to the MAC layer were adapted for wireless from the popular cable modem DOCSIS (data over cable service interface specification) standard.
The IEEE 802.16 group subsequently produced 802.16a, an amendment to the standard, to include NLOS applications in the 2GHz–11GHz band, using an orthogonal frequency division multiplexing (OFDM)-based physical layer. Additions to the MAC layer, such as support for orthogonal frequency division multiple access (OFDMA), were also included. Further revisions resulted in a new standard in 2004, called IEEE 802.16-2004, which replaced all prior versions and formed the basis for the first WiMAX solution. These early WiMAX solutions based on IEEE 802.16-2004 targeted fixed applications, and we will refer to these as fixed WiMAX. In December 2005, the IEEE group completed and approved IFEEE 802.16e-2005, an amendment to the IEEE 802.16-2004 standard that added mobility support. The IEEE 802.16e-2005 forms the basis for the WiMAX solution for nomadic and mobile applications and is often referred to as mobile WiMAX. The basic characteristics of the various IEEE 802.16 standards are summarized in Table 1.2.1. Note that these standards offer a variety of fundamentally different design options. For example, there are multiple physical-layer choices: a single-carrier-based physical layer called Wireless- MAN-SC@, an OFDM-based physical layer called Wireless MAN-OFDM, and an OFDMA based physical layer called Wireless-OFDMA. Similarly, there are multiple choices for MAC architecture, duplexing, frequency band of operation, etc. These standards were developed to suit a variety of applications and deployment scenarios, and hence offer a plethora of design choices for system developers. In fact, one could say that IEEE 802.16 is a collection of standards, not one single interoperable standard. For practical reasons of interoperability, the scope of the standard needs to be reduced, and a smaller set of design choices for implementation need to be defined. The WiMAX Forum does this by defining a limited number of system profiles and certification profiles.
A system profile defines the subset of mandatory and optional physical- and MAC-layer features selected by the WiMAX Forum from the IEEE 802.16-2004 or IEEE 802.16e-2005 standard. It should be noted that the mandatory and optional status of a particular feature within a WiMAX system profile may be different from what it is in the original IEEE standard. Currently, the WiMAX Forum has two different system profiles: one based on IEEE 802.16-2004, OFDM PHY, called the fixed system profile; the other one based on IEEE 802.16e-2005 scalable OFDMA PHY, called the mobility system profile. A certification profile is defined as a particular instantiation of a system profile where the operating frequency, channel bandwidth, and duplexing mode are also specified. WiMAX equipment is certified for interoperability against a particular certification profile.
The WiMAX Forum has thus far defined five fixed certification profiles and fourteen mobility certification profiles . To date, there are two fixed WiMAX profiles against which equipment have been certified. These are 3.5GHz systems operating over a 3.5MHz channel, using the fixed system profile based on the IEEE 802.16-2004 OFDM physical layer with a point-to-multipoint MAC. One of the profiles uses frequency division duplexing (FDD), and the other uses time division duplexing (TDD).
The first release of the IEEE 802.16 standard addressed applications in the licensed 10-66 GHz frequency range. Subsequent amendments to the standard (802.16a/b/c/d) addressed the licensed and license-exempt bands in the sub-11 GHz frequency range. Operation in these lower frequency bands enables the technology to address non-line-of-sight (NLOS) as well as LOS applications, allowing for ubiquitous coverage in a variety of demographic environments. The release of the IEEE 802.16e amendment, which will add mobility to the suite of services covered by the standard, is expected during the later half of 2006.
Fig 1.2.1 WiMAX Architecture and Applications
Figure 1.2.2: WiMAX Bridges the Gap between LAN and WAN
Table 1.2.1 Basic Data on IEEE 802.16 Standard:
  802.16 802.16.2004 802.16e.2005
Completed December
Completed June 2004 Completed December 2005
Frequency band
2GHz–11GHz for fixed;
2GHz–6GHz for mobile
Application Fixed LOS
Fixed NLOS Fixed and mobile NLO
MACarchitecture Point-to-multipoint,mesh Point-to-multipoint,
Point-to-multipoint, mesh
Transmission scheme
Single carrier only
Single carrier, 256
OFDM or 2,048 OFDM
Single carrier, 256 OFDM
or scalable OFDM with
128, 512, 1,024, or 2,048
Modulation QPSK, 16 QAM,64 QAM QPSK, 16 QAM,
64 QAM
QPSK, 16 QAM, 64 QAM
Gross data rate 32Mbps–134.4Mbps 1Mbps–75Mbps 1Mbps–75Mbps
Duplexing TDD and FDD TDD and FDD TDD and FDD
Channel bandwidths 20MHz, 25MHz,28MHz 1.75MHz, 3.5MHz,
7MHz, 14MHz,
1.25MHz, 5MHz,
10MHz, 15MHz,
1.75MHz, 3.5MHz, 7MHz,
14MHz, 1.25MHz, 5MHz,
10MHz, 15MHz, 8.75MHz
Wireless MAN-SC
Wireless MAN-SC
Wireless MAN-OFDM
Wireless MAN-OFDMA
Wireless HUMAN@
Wireless MAN-SC
Wireless MAN-OFDM
Wireless MAN-OFDMA
Wireless HUMAN@
@ Wireless HUMAN (wireless high-speed unlicensed MAN) is similar to OFDM-PHY (physical layer) but mandates dynamic frequency selection for license-exempt bands.

1.3 Salient Features of WiMAX: WiMAX is a wireless broadband solution that offers a rich set of features with a lot of flexibility in terms of deployment options and potential service offerings. Some of the more salient features that deserve highlighting are as follows:
1.3.1 OFDM-based physical layer: The WiMAX physical layer (PHY) is based on orthogonal frequency division multiplexing, a scheme that offers good resistance to multipath, and allows WiMAX to operate in NLOS conditions. OFDM is now widely recognized as the method of choice for mitigating multipath for broadband wireless.
1.3.2 Very high peak data rates: WiMAX is capable of supporting very high peak data rates. In fact, the peak PHY data rate can be as high as 74Mbps when operating using a 20MHz2 wide spectrum. More typically, using a 10MHz spectrum operating using TDD scheme with a 3:1 downlink-to-uplink ratio, the peak PHY data rate is about 25Mbps and 6.7Mbps for the downlink and the uplink, respectively. These peak PHY data rates are achieved when using 64 QAM modulation with rate 5/6 error-correction coding. Under very good signal conditions, even higher peak rates may be achieved using multiple antennas and spatial multiplexing.
1.3.3 Scalable bandwidth and data rate support:  WiMAX has a scalable physical-layer architecture that allows for the data rate to scale easily with available channel bandwidth. This scalability is supported in the OFDMA mode, where the FFT (fast fourier transform) size may be scaled based on the available channel bandwidth. For example, a WiMAX system may use 128-, 512-, or 1,048-bit FFTs based on whether the channel bandwidth is 1.25MHz, 5MHz, or 10MHz, respectively. This scaling may be done dynamically to support user roaming across different networks that may have different bandwidth allocations.
1.3.4 Adaptive modulation and coding (AMC): WiMAX supports a number of modulation and forward error correction (FEC) coding schemes and allows the scheme to be changed on a per user and per frame basis, based on channel conditions. AMC is an effective mechanism to maximize throughput in a time-varying channel. The adaptation algorithm typically calls for the use of the highest modulation and coding scheme that can be supported by the signal-to-noise and interference ratio at the receiver such that each user is provided with the highest possible data rate that can be supported in their respective links.
1.3.5 Link-layer retransmissions: For connections that require enhanced reliability, WiMAX supports automatic retransmission requests (ARQ) at the link layer. ARQ-enabled connections require each transmitted packet to be acknowledged by the receiver; unacknowledged packets are assumed to be lost and are retransmitted. WiMAX also optionally supports hybrid-ARQ, which is an effective hybrid between FEC and ARQ.
1.3.6 Support for TDD and FDD: IEEE 802.16-2004 and IEEE 802.16e-2005 supports both time division duplexing and frequency division duplexing, as well as a half-duplex FDD, which allows for a low-cost system implementation. TDD is favoured by a majority of implementations because of its advantages:
flexibility in choosing uplink-to-downlink data rate ratio sability to exploit channel reciprocity, ability to implement in non paired spectrumless complex transceiver design. All the initial WiMAX profiles are based on TDD, except for two fixed WiMAX profiles in 3.5GHz.
1.3.7 Orthogonal frequency division multiple access (OFDMA): Mobile WiMAX uses OFDM as a multiple-access technique, whereby different users can be allocated different subsets of the OFDM tones. OFDMA facilitates the exploitation of frequency diversity and multiuser diversity to significantly improve the system capacity.
1.3.8 Flexible and dynamic per user resource allocation: Both uplink and downlink resource allocation are controlled by a scheduler in the base station. Capacity is shared among multiple users on a demand basis, using a burst TDM scheme. When using the OFDMA-PHY mode, multiplexing is additionally done in the frequency dimension, by allocating different subsets of OFDM subcarriers to different users. Resources may be allocated in the spatial domain as well when using the optional advanced antenna systems (AAS). The standard allows for bandwidth resources to be allocated in time, frequency, and space and has a flexible mechanism to convey the resource allocation information on a frame-by-frame basis.
1.3.9 Support for advanced antenna techniques: The WiMAX solution has a number of hooks built into the physical-layer design, which allows for the use of multiple-antenna techniques, such as beam forming, space-time coding, and spatial multiplexing. These schemes can be used to improve the overall system capacity and spectral efficiency by deploying multiple antennas at the transmitter and/or the receiver.
1.3.10 Quality-of-service support: The WiMAX MAC layer has a connection-oriented architecture that is designed to support a variety of applications, including voice and multimedia services. The system offers support for constant bit rate, variable bit rate, real-time, and non-real-time traffic flows, in addition to best-effort data traffic. WiMAX MAC is designed to support a large number of users, with multiple connections per terminal, each with its own QoS requirement.
1.3.11 Robust security: WiMAX supports strong encryption, using Advanced Encryption Standard (AES), and has a robust privacy and key-management protocol. The system also offers a very flexible authentication architecture based on Extensible Authentication Protocol (EAP), which allows for a variety of user credentials, including username/password, digital certificates, and smart cards.
1.3.12 Support for mobility: The mobile WiMAX variant of the system has mechanisms to support secure seamless handovers for delay-tolerant full-mobility applications, such as VOIP. The system also has built-in support for power-saving mechanisms that extend the battery life of handheld subscriber devices. Physical-layer enhancements, such as more frequent channel estimation, uplink subchannelization, and power control, are also specified in support of mobile applications.
1.3.13 IP-based architecture: The WiMAX Forum has defined a reference network architecture that is based on an all-IP platform. All end-to-end services are delivered over an IP architecture relying on IP-based protocols for end-to-end transport, QOS, session management, security, and mobility. Reliance on IP allows WiMAX to ride the declining cost curves of IP processing, facilitate easy convergence with other networks, and exploit the rich ecosystem for application development that exists for IP.
1.4 WiMAX Mobile Applications (802.16e):
In order to execute a true quadruple play strategy, a service provider will need to offer mobile services. Even though it's called "mobile", 802.16e-2005 offers a number of ad-vantages to the fixed wireless market as well. Better building penetration as well as improvements in security and QOS point to a strategy of "one network serves all".
1.4.4 WiMAX as cellular alternative
Of all the sub industries in telecommunications, perhaps the one best positioned to take advantage of WiMAX is the cellular service providers. They have a lot going for them including a wireless culture (RF engineers, wireless savvy sales staff, etc) and millions of "early adaptor" customers. On the other hand, the transition from legacy circuit switching and a dependency on the incumbent telephone service provider's network will not be easy or inexpensive. As the diagram below supports, a large percentage of a cell phone operator's monthly operating expense (OPEX) is T1 backhaul to support their base stations. In addition, they use aging circuit switches (Class 4 and 5 as well as Mobile Switching Centers) to switch phone calls. These come with expensive annual service contracts. A WiMAX substitute for the cell phone infrastructure could be operated at as little as 10% of the OPEX of a cellular operator using legacy infrastructure .Replacing a cell phone infrastructure with WiMAX will need to incorporate a large mo-bile data and mobile TV element with it as data bandwidth demands on the system will be far greater than what is now seen with a voice-centric cell phone network. The diagram below provides a high overview of a converged voice and data wireless network

Figure 1.4.1: The cellular network is a mixture of wireless and PS architecture
When one mentions "mobile" the first thing to come to mind is cell phone service, which is a huge industry in itself. However, mobile now connotes a wide range of services be-yond voice to include mobile data and TV, as well as emergency services (police, fire, ambulance, aka 4.9GHz market).

Figure 1.4.3:   WiMAX as a mobile voice and data network is potentially exponentially more efficient (profitable) than the legacy cellular infrastructure.
A wireless operator will want to pay close attention to their ARPU while minimizing their OPEX. WiMAX allows an operator to do both simultaneously. Failure to update a legacy network could put an operator at risk of losing business to new market entrants armed with WiMAX.
1.5 WiMAX Economics:WiMAX costs less to deploy than any other broadband technology. As the table below indicates many technologies such as fiber to the home (FTTH) are exponentially more expensive to deploy. The doomsday scenario for service providers using an expensive landline technology (and their investors) such as FTTH or cable is that after an invest-ment in the many billions of dollars to serve one small region, a WiMAX operator could enter their market and far less capital expenditure (CAPEX) and drive the incumbent, high CAPEX operator out of business.

DSL $270 Bn $30-$50 –
CABEL $65 Bn $1,200 –
2/2.5/3G $405 Bn $50 #
FIBER TO THE HOME(FTTH) $93 Bn (estimated) $1,250
WIMAX $3 Bn (estimated) $ 8*
 Source: Hal Varian University of California and Robert Litan, Brookings Institute
#Source: Morgan Stanley(2004)
The table above shows the strong economic advantage of WiMAX over other broadband technologies. With the exception 2.5 and 3 G wireless technologies, the other broadband technologies cannot offer mobile services and are not quadruple play capable. Disruptive technology is defined by Harvard Business School Professor Clayton Christensen as being "cheaper, simpler, smaller and more convenient to use" than legacy technologies. WiMAX is clearly a disruptive technology. As Table 1.5.1 would suggest, the barrier to entry for WiMAX service providers is very low relative to other broadband technologies. This has the potential to invite entrepreneurs into many markets to offer WiMAX-related services in direct competition with incumbent service providers who have invested millions if not billions of dollars in their respective network infrastructure. The best way to illustrate this is the notion that, for the price of a new pickup truck, an entrepreneur could be the ISP, the telephone company, the cable TV company and even the cell phone company for a small city. This puts at risk investment in incumbent service providers who do not upgrade their infrastructure to compete with WiMAX.
1.6 Objective of the Thesis
The main objective of thesis is to focus on performance analysis of WiMax and to implement and simulate the IEEE 802.16 OFDM physical layer using Mat lab in order to have better understanding of the standard and the system performance.  This involves studying,  through  simulation,  the  various  PHY modulation,  coding  schemes  and  interleaving  in  the  form  of  bit-error-rate  (BER)  and effects of FEC  on the transmission side. The Stanford University Interim (SUI) channel models are selected for the wireless channel in the simulation. The evaluation was done in simulation developed in MATLAB. The influence of these parts on the system performance is shown and analyzed great detail in Simulink also. Finally the market evaluation of WiMax around the world and its prospects in Bangladesh under the basis of the work of technical advancement, present status, its possible implementation are also focused.
1.7 Thesis layout
Chapter one contains introduction which consists of an overview of WiMAX and its type. It also consists of different features of WiMAX.
Chapter two contains description of WiMAX transmitter.
Chapter three is about transmission channel.
Chapter four describes receiver.
Chapter five is of performance analysis of WiMAX using simulink. It also shows physical layer performance and scattered plot. It describes BER of different types of modulation in WiMAX. This chapter displays results of simulink also.
WiMAX growth and its economic valuation are described on Chapter six.
Chapter seven is about perspective of WiMAX in BANGLADESH.
Chapter eight contains conclusion and future works. 
This chapter describes the different steps the transmitter performs before transmitting the data. The functional blocks that compose the transmitter of the WiMAX simulator are depicted in Figure 2.1

Figure 2. – 1: Transmitter of the WiMAX system.
First of all, the data from the source is randomized and afterwards, coded and mapped into QAM symbols. The simulator implemented in the thesis works for the Wireless MAN-OFDM physical (PHY) layer of WiMAX. This PHY layer uses orthogonal frequency division multiplexing (OFDM) with 256 subcarriers. Each OFDM2 symbol is composed of 192 data subcarriers, 1 zero DC subcarrier, 8 pilot subcarriers, and 55 guard carriers. Therefore, a process of assembling the zero DC subcarrier, data, and pilots is needed to build the symbols. Furthermore, preambles consisting of training sequences are appended at the beginning of each burst. These training sequences are used for performing an estimation of the channel coefficients at the receiver. After the assembling process, a zero padding is performed. The signal is converted to the time domain by means of the inverse fast Fourier transform (IFFT) algorithm, and finally, a cyclic prefix (CP) with the aim of preventing inter-symbol interference is added.
2.1 Source
As described in the standard , the information bits must be randomized before the transmission. The randomization process is used to minimize the possibility of transmissions of non-modulated subcarriers. The process of randomization is performed on each burst of data on the downlink and uplink, and on each allocation of a data block (sub channels on the frequency domain and OFDM symbols on the time domain).In our case, instead of performing a randomization process, a binary source that produces random sequences of bits is used. The number of bits that are generated is specified to be frame-based and is calculated from the packet size required in each situation. The packet size depends on the number of transmitted OFDM symbols and the overall coding rate of the system, as well as the modulation alphabet.
 Equation 2.1 – 1 calculates the number of transmitted OFDM symbols in one frame. It depends on the total number of transmitted symbols, NTsym, which also includes the symbols used for the preamble, specified by Ntrain:

Furthermore, the total number of transmitted symbols is defined as

In the formula, Tsym is the OFDM symbol time, and Tframe denotes the frame duration. The expression that defines Tsym as well as the possible values specified for the frame duration. Once the number of OFDM symbols is known, the number of bits to be
sent by the source is calculated:

Here, R represents the overall coding rate, Ndata is the number of used data subcarriers, and Ma defines the modulation alphabet, which is specified by
the number of transmitted bits per symbol.
2.2 Encoder
As shown in Figure 2.2 – 1, the encoding process consists of a concatenation of an outer Reed-Solomon (RS) code and an inner convolutional code (CC) as a FEC scheme. That means that first data passes in block format through the RS encoder, and then, it goes across the convolutional encoder. It is a flexible coding process due to the puncturing of the signal, and allows different coding rates. The last part of the encoder is a process of interleaving to avoid long error bursts.

Figure 2.2.1: The coding process in WiMAX.
A variable-rate coding scheme that depends on the channel conditions is designed to offer optimal error protection levels to the users. The FEC options are paired with several modulation schemes to form burst profiles of varying robustness and efficiency. Table 2.2 – 1 gives the block sizes and code rates used for the different modulations.

Table 2.2 – 1: WiMAX modulation and coding schemes.
The users report the current channel condition to the base station (BS) and, based on this report, a specific coding rate is selected for the downlink data transmissions. Thus, users who experience a "bad" channel condition, i.e. low SNR, at a given time, will be provided with better error correction than those users experiencing "good" channel conditions at the same time.
This process is called adaptive modulation and coding (AMC)4. In the next sections, each one of the different encoder blocks will be explained in detail. It will be given a thorough description of how they work and are implemented in the simulator.
2.2.1 Reed-Solomon Encoder
The  randomized data  are  arranged  in block  format before passing  through  the encoder and a single 0X00  tail byte  is appended  to  the end of each burst. The  implemented RS encoder is derived from a systematic RS (N=255, K=239, T=8) code using GF (28 ). The following polynomials are used for code generator and field generator:
0 0 2T-1
G(x) = (x+λ0 )(x+λ0 )….. (x+λ2T-1), λ = 02HEX (2.2.1)
P(x) = x8 + x4 + x3 + x2 + 1      (2.2..2)                                                                                       
The encoder support shortened and punctured code to facilitate variable block sizes and
variable  error-correction capability. A  shortened  block of  k´  bytes  is obtained  through
adding  239-k´  zero  bytes before  the  data  block  and  after  encoding,  these  239-k´  zero bytes are discarded. To obtain the punctured pattern  to permit T´ bytes  to be corrected, the first 2T´ of the 16 parity bytes has been retained.

2.2.2 Convolutional Encoder
The  outer  RS  encoded  block  is  fed  to  inner  binary  convolutional  encoder.  The implemented encoder has native  rate of  1/2, a constraint  length of  7  and  the generator polynomial  in Equation  (2.2..3)  and  (2.2..4)  to  produce  its  two  code bits. The  generator  is shown in   
G 1= 171 OCT For X     (2.2.3)
G 2= 133 OCT For Y (2.2.4)
In order to achieve variable code rate a puncturing operation  is performed on the output
of  the convolutional encoder  in accordance  to Table 2.2.  In  this Table “ 1”  denotes  that the  corresponding  convolutional  encoder  output  is  used,  while  “ 0”   denotes  that  the corresponding output  is not used. At  the receiver Viterbi decoder  is used  to decode  the convolutional codes.

2.3 Interleaver
RS-CC  encoded  data  are  interleaved  by  a  block  interleaver.  The  size  of  the  block  is depended on the numbers of bit encoded per subchannel in one OFDM symbol, Ncbps. In IEEE  802.16,  the  interleaver  is defined  by  two  step  permutation. The  first  ensures  that adjacent coded bits  are mapped onto non-adjacent  subcarriers. The  second permutation ensures that adjacent coded bits are mapped alternately onto less or more significant bits of the constellation, thus avoiding long runs of unreliable bits .
The Matlab implementation of the interleaver was performed calculating the index value
of the bits after first and second permutation using Equation (2.2.5) and (2.2..6) respectively.
f k  = (N cbps /12).k mod12 +floor(k/2)        k = 0,1,2,… … ..N cbps -1                 (2.2..5)
s k  = s.floor(fk /s) + (m k  +N cbps  – floor(12.m k /N cbps ))mod(s)   k=0,1,2,… .… N cbps -1         (2.2..6)
where s= ceil(N cpc /2) , while N cpc  stands for the number of coded bits per subcarrier, i.e., 1,2,4 or 6 for BPSK,QPSK 16-QAM, or 64-QAM, respectively.
The default number of subchannels i.e 16 is used for this implementation.
The receiver also performs the reverse operation following the two step permutation
using equations (4.7) and (4.8) respectively.
fj = s. floor(j/s)+(j+floor(12.j/Ncbps))mod(s) j=0,1,… … ..Ncbps1(2.2..7)
sj = – (Ncbps 1).
floor( j=0,1,2… … ..Ncbps1(2.2..8)
2.4 Constalletion Mapper
The bit interleaved data are then entered serially to the constellation mapper. The Mat lab implemented constellation mapper support BPSK, grey mapped QPSK, 16QAM,and 64QAM as specified in Simulation results. The complex constellation points are normalized with the specified multiplying factor for different modulation scheme so that equal average power is achieved for the symbols. The constellation mapped data are assigned to all allocated data subcarriers of the OFDM symbol in order of increasing frequency offset index.
2.5 IFFT
The grey mapped data are then sent to IFFT for time domain mapping. Mapping to time
domain needs the application of Inverse Fast Fourier Transform (IFFT). In our case we
have incorporated the MATLAB ´ifft´ function to do so. This block delivers a vector of
256 elements, where each complex number clement represents one sample of the OFDM
2.6 Cyclic Prefix Insertion:
A cyclic prefix is added to the time domain samples to combat the effect of multipath.
Four different duration of cyclic prefix are available in the standard. Being G the ratio of
CP time to OFDM symbol time, this ratio can be equal to 1/32, 1/6, 1/8 and 1/4
Transmission channel
When communicating over a wireless radio channel the received signal cannot be simply modeled as a copy of the transmitted signal corrupted by additive Gaussian noise. Instead, signal fading, while caused by the time-varying characteristics of the propagation environment, appears. In this way, short-term fluctuations caused by signal scattering of objects in the propagation environment lead to a phenomenon known as multipath propagation. The time dispersion in a multipath environment causes the signal to undergo either flat or frequency-selective fading. Furthermore, the time dispersion is manifested by the spreading in time of the modulated symbols leading to inter-symbol interference (ISI). In order to avoid ISI in OFDM systems, the cyclic prefix time has to be chosen larger than the maximum delay spread of the channel. In addition, root-raised cosine (RRC) filters, usually used for band-limiting the transmitted signal, are utilized as interpolation filters in the simulator.
This chapter deals with the modeling, analysis, and simulation of the channel. It provides a description of the mentioned RRC filters as well as a brief explanation about the fading characteristics. As the simulation results depend strongly on the radio channel, it is very important to use accurate and realistic channel models in the simulation to enable realistic and reliable results. Thus, the well-known I-METRA channel model is introduced.
3.1 Filters
Data transmission over band limited channels requires a technique of pulse shaping at the transmitter. Since the pulse shaping filter does not cause inter-symbol interference (ISI), this implies the fundamental shapes of the pulses to be such that they do not interfere each other. A criteria that ensures non-interference specifies the shape of the pulses to be such that its amplitude decays rapidly outside the pulse interval. A widely used filter for this purpose is the well known raised cosine filter, which satisfies Nyquist’s first criterion1. However, in practical applications the overall magnitude response of the raised cosine spectrum is equally split between the transmitter and the receiver, thus obtaining square-root raised cosine filters, also known as root-raised cosine (RRC) filters. The advantage of such subsystems is that if the transmit side filter is stimulated by an impulse, then the receive one is forced to filter an input pulse with a shape that is identical to its own impulse response, therefore setting up a matched filter and maximizing the SNR while at the same time minimizing ISI [12]. The RRC filter is generally used in series pairs so that the total filtering effect is that of a raised cosine filter. Since the frequency response of the transmit and receive filters is multiplied at the receiver, the receiver sees a signal that has been filtered by a raised cosine filter overall:
 (3.1 – 1)
   (3.1 – 2)
Hrrc(f) defines the root-raised cosine filter frequency response, while Hrc(f) is used for defining the raised cosine filter. The ideal root-raised cosine filter frequency response is simply the square root of the frequency response of a raised cosine filter. The RRC frequency response is specified in Equation 3.1 – 3, and it consists of a unity gain at low frequencies, the square root of a raised cosine function in the middle, and a total attenuation at high frequencies.

(3.1 -3)
1Nyquist’s first criterion establishes the conditions the transmission pulse p(t) must
accomplish to avoid ISI. It specifies p(t) to be one for the sampling interval of the desired
symbol, and zero for the another symbols:

fN is the Nyquist frequency defined as

where Tsym is the modulation symbol duration, and Rsym is the symbol rate.
The width of the central frequencies is defined by the roll-off factor, _, which determines the sharpness of the frequency response and can take values comprised between 0 and 1. Specifically, _ governs the bandwidth occupied by the pulse and the rate at which the tails of the pulse decay. Figure 3.1 – 1 shows that when  the frequency response has a form of a rectangle offering the narrowest bandwidth but the slowest rate of decay in the time domain. However, when  the frequency response is completely round but the impulse response presents the added benefit of rapidly decaying time domain tails. Therefore, it can be deduced that the smaller the roll-off factor, the more efficient is the scheme since it gives the narrowest bandwidth.

        (a) Impulse response hrrc(t).                                (b) Frequency response Hrrc(f).
Figure 3.1 – 1: Spectral shape and inverse Fourier transform of the RRC pulse.
The most commonly used design methodology for this kind of filters is the frequency sampling design, where the frequency response of the filter is sampled at constant intervals and an inverse fourier transform (IFFT) is applied to the frequency samples to obtain the filter coefficients. The more the number of frequency samples, the more wills the actual response match the desired response. That means that if more filter taps are used, a more accurate response is obtained, and therefore, better rejection is given.
3.2 Fading channel models
3.2.1 Description of the fading channel
In a realistic wireless radio environment, a single received signal is composed of a number of scattered waves, caused by the reflection and diffraction of the original transmitted signal by objects in the surrounding geographical area. These multipath waves are combined at the receiver to give a resultant signal that can widely vary in amplitude and phase. Physical factors influencing the characteristics of the fading experienced by the transmitter are multipath propagation, mobility of the reflecting objects and scatterers, and the relative motion between the transmitter and the receiver. The presence of reflecting objects and scatterers in the wireless channel causes a constant change in the propagation environment. This changing environment alters the signal energy in amplitude, phase, and time, and as a result, multipath propagation occurs causing signal fading. The transmitted signal arrives at the receiver via multiple propagation paths, each of which has an associated time delay. Because the received signal is spread in time due to the multipath scatterers at different delays, the channel is said to be time dispersive. The difference between the largest and the smallest among these delays defines the maximum delay spread. On the other hand, when the receiver and the transmitter are in relative motion, the received signal is subject to a constant frequency shift, called the Doppler shift (see Equation 3.2 – 1). Therefore, as it occurs in the time domain, the Doppler spread is defined as the difference between the largest and the smallest among these frequency shifts,
(3.2 – 1)
fM = fcv/c is the maximum Doppler shift,
v is the vehicle speed,
fc is the carrier frequency,
c is the speed of light, and is the arrival angle of the received signal component. Furthermore, a time-varying Doppler shift is induced on each multipath component if the reflecting objects and scatterers in the propagation channel are in motion, causing frequency dispersion.
As a result of such time variations, the response of the channel to any signal transmitted through it will change with time. Hence, physical channels with time-varying transmission characteristics may be characterized as time varying linear filters. Such linear filters are described by a time-varying impulse response,   which represents the response of the channel at time t due to an impulse applied at time  . Thus, the variable t specifies the time dependence in the variations of the impulse response due to motion, whereas _ represents the channel multipath delay for a fixed value of t.
Assuming that the pass-band input signal to a multipath fading channel is s(t), and ignoring the effects of AWGN, the pass-band output signal is given by
(3.2 – 2)
Where  represents the continuous-time convolution. The pass-band channel impulse response can also be written as
(3.2 – 3)
where  is the baseband equivalent impulse response of the channel, and fc is the carrier frequency of the pass-band input signal. When L discrete multipath components exist in the multipath fading channel, this baseband channel impulse response is written as
and  are the delay dependent instantaneous amplitude and
the time delay associated with the i-th multipath component, respectively. The instantaneous phase shift encountered by the i-th multipath component due to its delay is represented by the factor whereas any other phase alteration experienced by this multipath component is incorporated in To simplify Equation 3.2 – 4, the phase delays are lumped together
and represented by
3.2.2 Tapped delay line channel model
A general model for a time-variant multipath channel consists of a tapped delay line with uniformly spaced taps, as the one depicted in Figure 3.2 – 1. The spacing between adjacent taps is K/(MW), where W is the bandwidth of the signal that is being transmitted through the channel. Hence, K/(MW), defines the time resolution of the channel model implementation, where an interpolation factor of M/K is being used. Moreover, the tap coefficients, denoted as  are usually modeled as complex-valued Gaussian random processes which are mutually uncorrelated. The length of the delay line corresponds to the amount of time dispersion in the multipath channel, usually called the multipath spread, Tm = L/W, where L represents the maximum number of possible multipath signal components.

Figure 3.2 – 1: Model for a time-variant multipath channel based on a tapped delay line.
3.2.3 Delay spread and Doppler spread
As previously explained, two manifestations of the channel time variations are the delay spread and the Doppler spread. Depending on their values, the signal transmitted through the channel will undergo flat or frequency selective fading. On one hand, the delay spread is a measure of the spread in time over which the multipath signals arrive. It is a measure of the time dispersion of a channel, and is very important in determining how fast the symbol rate can be in digital communications. One of the most widely used measurements for characterizing the delay spread of a multipath channel is the rms delay spread,   . Furthermore, the inverse of the delay spread defines the coherence bandwidth, Bcoh. It is the frequency separation at which two frequency components of the signal undergo independent attenuations and a measure of the range of frequencies over which the multipath fading channel frequency response can be considered to be flat or not. On the other hand, the Doppler spread, Bd, is a measure of the spectral broadening caused by the time rate of change of the multipath components due to the relative motion between transmitter and receiver. Depending on how rapidly the multipath components change, the channel may be classified either as a fast or a slow fading channel. Inversely proportional to one another are the Doppler spread and the coherence time. The coherence time, Tcoh, is the time domain dual of Doppler spread and is used to characterize the time-varying nature of the frequency dispersive ness of the channel in the time domain. It is a statistical measure of the time duration over which the channel impulse response is essentially invariant quantifying the similarity of the channel response at different times.In 802.16-2004, the coherence time of the channel is assumed to be longer than the frame duration, leading to quasi-static scenarios.
3.2.4 Rayleigh and Ricean fading model
Wireless channels can be characterized with tap coefficients that are complex valued Gaussian random variables. A channel model where there are only non line-of-sight communications is characterized by a Rayleigh distribution. On the contrary, if dominating paths are present, the channel coefficients are modeled by a Ricean distribution. As already mentioned, a Rayleigh distribution is normally used to model NLoS communications. It is statistically characterized by a fading amplitude ,α(t) modeled with a Rayleigh probability distribution, which has zero-mean Gaussian components. Furthermore, the phase, φ(t) , is uniformly distributed over the interval  (0,2π) .The fading amplitude is described by the probability density function (PDF):
(3.2 – 6)
On the other hand, when the components of α(t)   are Gaussian with nonzero mean values and the phase is also non-zero mean, the amplitude is characterized statistically by the Rice probability distribution. In this case, the channel presents multipath propagation with some dominating paths, i.e. representing a major part of the channel energy. The PDF of the Ricean fading amplitude is given by
where the parameter  represents the power of the received non-fading signal component, and I0 is the modified Bessel function of first kind and order zero. The Ricean distribution is usually expressed with the K-factor defined as the ratio of the power of the deterministic signal to the variance of the multipath component:
(3.2 – 8)
If K approaches zero, then the Rice distribution degenerates in a Rayleigh distribution. Thus, when  has values near to 0, K is prone to  dB, and since the dominant path decreases in amplitude, the Rice distribution becomes a Rayleigh distribution. Furthermore, if K approaches infinity, one path will contain the whole channel energy, corresponding to a LoS scenario.
3.3 Flat fading
When considering the transmission of a specific signal, the properties of that signal play a role in determining whether the effects caused by the channel on it are invariant in any given domain. This relationship existing between the coherence of the channel and the properties of the signal is captured by the notion of selectivity. If the channel is selective, then the region of support2 of the transmitted signal is larger than the coherence interval. Therefore, the channel is not flat with respect to the signal in that domain. However, when the channel has a constant gain and linear phase response over a bandwidth that is greater than the bandwidth of the transmitted signal, the received signal undergoes flat fading. For this kind of fading, the spectral characteristics of the transmitted signal are preserved when it propagates through the channel, and only the received signal power fluctuates due to the multipath effects. For this reason, flat fading channels are also known as amplitude varying channels. Moreover, they are sometimes referred to as narrowband channels since the bandwidth of the applied signal is narrow as compared with the fading bandwidth.
To summarize, a signal undergoes flat fading if
(3.2- 9)
(3.2 – 10)
3.4 Frequency-selective fading
The frequency-selective behaviour of the wireless propagation channel can be obtained easily from the correlation between two signals (which have different frequencies) in the receiver. The existence of different delay spread for the different propagation paths cause the statistical properties of two carriers to be independent if they are sufficiently frequency spaced. The  maximum frequency difference for which a high correlation level between the signals are kept is known as the coherence bandwidth of the channel. That means that for frequency-selective fading the spectrum of the transmitted signal has a bandwidth which is greater than the coherence bandwidth of the channel. Under such conditions the channel impulse response has a multipath delay spread that exceeds the symbol period of the transmitted symbol. When this occurs, the received signal includes multiple versions of the transmitted waveform that are attenuated and delayed in time, and hence, the received signal is distorted. Frequency selective fading is due to time dispersion of the transmitted symbols within the channel, thus inducing to inter-symbol interference (ISI).
To summarize, a signal undergoes frequency-selective fading if
(3.2 – 11)
(3.2 – 12)
However, when communicating with OFDM techniques, the effects of frequency-selective channel conditions can be decreased. Since the signal is split into many narrowband subchannels, the channel can be considered as constant (flat) over each OFDM subchannel, provided that the respective conditions for flat fading channels are accomplished.
3.5 Channel model implementation
The goal of this section is to describe the different steps that have been performed to implement the channel in our simulator. The signal is firstly oversampled and filtered using an RRC interpolation filter at the transmitter. The resulting signal is resampled to 100 MHz, that is the channel simulator sampling frequency. After resampling, the signal is sent through the channel itself, characterized by the channel model. This channel model distinguishes three kinds of channels: a block fading channel, a time-variant channel, and a time-variant block fading channel. At the receiver, some noise is added, and the signal is decimated from the channel simulator sampling frequency. Finally, it is filtered and down sampled.
 3.5.1 Block fading channel
The block fading channel is used for simulating slowly-varying fading channels. That means that the fading varies slowly in time and the channel coefficient, hi, do not change during the transmission of one OFDM frame, as it is shown in Figure 3.2 – 2.

Figure 3.2 – 2: Block fading channel model.
Here, the channel realizations for consecutive frames are independent, which allows for fast BER simulations but not for simulations incorporating
adaptive modulation and coding (AMC).
3.5.2 Time-variant channel
As previously explained, the variation in time of the wireless channel is caused by user mobilityand multipath propagation. The impulse response of timevarying n channels is characterized as a time-variant linear filter,  , and a frequency shift appears in the received signal, fd, when users are in relative motion. The time-variant filtering is implemented in the function "tvfilter ", which convolutes every sample of the transmitted signal with the instantaneous impulse response. Since such a filtering operation is of very high complexity,
the "time-variant block fading" model was implemented. To generate the time-varying characteristic of the fading channel, the function "jakes" is used. It utilizes a so-called sum of sinusoids to perform this operation.
The assumptions of this model are :
The transmitter is fixed and employs an omni directional antenna, that has been vertically polarized.
The field incident on the receiver consists of N azimuthal plane waves.
Each of the N azimuthal plane waves has an arbitrary carrier phase and an arbitrary angle of arrival. The phase angles are assumed to be uniformly distributed.
The N azimuthal plane waves have equal average amplitudes, implying the absence of a LoS path.
The model assumes that N equal-strength rays arrive at a moving receive with uniformly distributed arrival angles, , such that ray n experiences a Doppler shift given by
 (3.2 – 13)
As a result, the k-th fading waveform, Tk(t), from a system that has M independent fading waveforms, each of which is composed of N sinusoids, can be expressed as in Equation
3.2 – 14:
(3.2 – 14)
where ,, and  represent the amplitude, frequency, and uniformly random phase of the n-th complex sinusoid in the k-th fader.For this situation,
, where n = 0, 1, 2, 3, …,N − 1, and
k = 0, 1, 2, 3, …,M −1.
Note that 'nk, that denotes the n-th arrival angle in the k-th fader, depends on both, the fading waveform and the sinusoid. The parameter Cnk can be reduced to a constant value by assuming a uniform antenna gain pattern and uniformly distributed incident power:
 (3.2 – 15)
Furthermore, different spectrum shapes are obtained depending on the values the parameters  and  take. Hence, a flat spectrum, a Jake’s spectrum, and a Clarke’s spectrum are defined. Flat spectrum
The parameter  takes the values  thus making null the operation
Therefore, the exponential describing the fading waveform follows the next expression:
(3.2 – 16) Jake’s spectrum
Finally, the Jakes spectrum takes into account all the parameters that have been previously described

3.5.3 Time-variant block fading channel
This kind of channels is a combination of block fading channels and time variant channels. The channel filtering operation is the same as in the block fading channel, i.e. a constant channel is assumed during one OFDM frame. The generated channel impulse responses in successive frames are changing in a time-varying manner, i.e. the channel changes steadily. The steadying changing channel allows for AMC simulations when the channel changes slowly compared to the OFDM frame duration.
Along with the above channel parameters, coherence distance, co channel interference, antenna gain reduction factor should be addressed for channel modeling.
Having the primary requirements for our channel model, we have two options to go with. Either we can use mathematical model for each of them or we can choose an empirical  model that care of the above requirements. We opted for the later one and chose the
Stanford University Interim (SUI) channel model for our simulation.
3.6 Stanford University Interim (SUI) Channel Models
SUI channel models are an extension of the earlier work by AT&T Wireless and Erceg etal . In this model a set of six channels was selected to address three different terrain types that are typical of the continental US . This model can be used for simulations, design, and development and testing of technologies suitable for fixed broadband wireless
Applications. The parameters for the model were selected based upon some statistical models. The tables below depict the parametric view of the six SUI channels.



We assume the scenario [12] with the following parameters:
¨ Cell Size: 7Km
¨ BTS antenna height: 30 m
¨ Receive antenna height: 6m
¨ BTS antenna beamwidth: 1200
¨ Receive antenna beamwidth: omnidirectional
¨ Polarization: Vertical only
¨ 90% cell coverage with 99.9% reliability at each location covered
For the above scenario, the SUI channel parameters are tabulated in Table 4.5, 4.6 and
4.7 according to
As illustrated in Figure 4.0 – 1, the receiver basically performs the reverse operation as the transmitter as well as a channel estimation necessary to reveal the unknown channel coefficients. This section explains the different steps performed by the receiver to reconstruct the transmitted bits.

Figure 4.0 – 1: Receiver of the WiMAX system.
Firstly, the CP is removed and the received signal is converted to the frequency domain using, in this case, the FFT algorithm. As, an OFDM symbol is composed by data, pilots, a zero DC subcarrier, and some guard bands. Thus, a process to separate all these subcarriers is needed. First, the guard bands are removed, and then, a disassembling is performed to obtain pilots, data, and trainings. The training is used in the channel estimator, which calculates the channel coefficients. The estimated channel coefficients can be used in the demapper to perform an equalization of the data, and so, compensate the frequency selective fading of the multipath propagation channel. Once the data has been demapped, it enters the decoder block.
4.1 Fast Fourier Transform algorithm
As explained in Section 2.8, the IFFT algorithm represents a rapid way for modulating a group of subcarriers in parallel. Either the FFT or the IFFT are a linear pair of processes, therefore the FFT is necessary to convert the signal again to the frequency domain1. The number of points used to perform the FFT is also described in Section 2.8.
4.2 Removing the guard bands
When removing the subcarriers that correspond to the guard bands, the frequency structure has to be taken into account. Although zero padding acting as guard band is appended at the end of the subcarrier structure at the transmitter, a rearrangement of this subcarriers is performed when doing the IFFT operation, as shown in Figure 2.8 – 1. Thus, the guard bands are removed from the center of the OFDM symbol, that is where they are allocated after the arranging process.
4.3 Disassembler
The disassembler deals with the task of separating the signal, either in time or in frequency domain, to get data, training, and pilots. These three differentsymbol streams form the output of the disassembler.
4.4 Channel estimator
The message sent by the transmitter is modified when it passes through the channel, as some noise is added to the transmitted signal. Furthermore, if the channel is a wireless channel, the received signal is additionally affected by the multiple reflections due to multipath transmission. Thus, the receiver must determine, from the received signal, which of all possible messages was the transmitted one. On the other hand, detection algorithms at the receiver require knowledge of the channel impulse response (CIR). This knowledge can be provided by performing channel estimation. Usually, channel estimation is based on known sequences of bits, which are unique at the transmitter and repeated in every transmission burst. This way, the channel estimator is able to estimate CIR for each burst separately by exploiting the known transmitted bits and the corresponding received samples. In our case, channel estimation is based on the technique of leastsquares (LS) and is performed using one training symbol per carrier. The received signal on the k-th subcarrier yk can be expressed as follows:
(4.4 – 1)
 where hk is the channel coefficient for the k-th subcarrier, pk is the training symbol, and nk is a noise symbol.
The LS channel estimates can be obtained by finding the minimum squared error, as expressed in Equation 4.4 – 2:
(4.4 – 2)
If white Gaussian noise is assumed, Equation 4.4 – 2 results in
(4.4 – 3)
where the expressions (·)_ and (·)−1 denote conjugation and inverse operation, respectively. This estimator is implemented for all subcarriers where a pilot symbol unequal to zero is transmitted. In the simulator, channel estimation is implemented using either the short, the long or both training symbols. The use of one or another training sequence depends on the values of the averaging parameters. The long training used for channel estimation is PEVEN, and as described in Equation 2.5 – 2, it has null values for the odd indices. If only the long training sequence is used for channel estimation, Equation 4.4 – 3 results in
(4.4 – 4)
The short training has values different than zero only for the indices that are multiple of 4, as defined in Equation 2.5 – 1. Here, Equation 4.4 – 3 reduces to the expression
(4.4 – 5)
A better channel estimate can be achieved if averaging in the frequency domain is performed. This way, the averaging parameter defines how many subcarriers are taken into account when performing the cited averaging. While small averaging factors improve the performance in strongly frequency selective channels, large averaging factors improve the performance in flat fading channels.
The two parameters defining the described averaging factors are called Long Averaging and Short Averaging, and can be zero or positive. A value of "zero" means that no averaging over the corresponding training sequence is performed, and so, the corresponding training symbol is not used while performing the channel estimation. In this way, it can also be determined if
only the short or long training sequence, or both training sequences are used
for channel estimation.
4.5 Demapper
At the receiving end of the communication link the demapper provides the interface between the transmission channel and the functions that compute and deliver estimates of the transmitted data bits to the user. Furthermore, the demapper operates on the waveform that is received in each separate transmission symbol interval and produces a number or a set of numbers that represent an estimate of a transmitted binary or M-ary symbol. Thus, the demapping methods are used for decision metrics with the aim of making a decision about which bit, "zero" or "one", was transmitted. This decision metric can be as simple as hard decision, or more sophisticated, being then a soft decision.
Hard demapping methods output a hard decision as a function of the input, and this form of output is application-dependent. However, the soft demapping outputs a real number, in the form of a log-likelihood ratio. This is the logarithm of the ratio between the likelihood that the target produced the speech input and the likelihood that a non-target produced the input. In contrast, this form of output is application-independent in the sense that this likelihood ratio output can theoretically be used to make optimal decisions for any given target prior.
4.5.1 Hard Demapping
Hard demapping is based on the minimum Euclidean distances between the received symbol and all allowed points in the constellation map. This method involves calculating all cited distances and selecting as the received symbol the point in the constellation map with the smallest Euclidean distance. Equation 4.5 – 1 gives the formula to calculate the Euclidean distance from which the decision metric is obtained. As it can be seen, the knowledge of the
channel coefficients, or its estimates, is needed to implement hard demapping:
(4.5 – 1)
dE is the Euclidean distance, y denotes the received symbol, h represents the channel coefficients, and s is used to denote the transmitted symbols.
Thus, the decision metric is calculated as follows:
(4.5 – 2)
4.5.2 Soft demapping
Soft demapping uses log-likelihood ratios to propose a decision metric. This log-likelihood ratios are calculated for every bit of the symbol. The method gives probabilities of well receiving a bit or not. These probabilities can be further used to improve the performance of  he succeeding Viterbi decoder. In the simulator, the so-called max-log-MAP was implemented.
The log-likelihood ratio (LLR) of decision is defined in Equation 4.5 – 3:

The conditional pdf2 of the received bit, which is complex Gaussian, is defined as follows:

where  is the noise variance of the signal, and  the standard deviation. Thus, Equation 4.5 – 3 yields

Since the calculation of Equation 4.5 – 4 is of very high complexity a logsum approximation is used. This approximation is good as long as the sum in the left-hand side is dominated by the largest term
Thus, the computational complexity is reduced, and the LLR is calculated as in Equation 4.5 – 5:

At the end, the algorithm consists on calculating the minimum distance between the received symbol and all symbols in the constellation map where the bit bk is equal to "one", the minimum distance between the received symbol and the constellation points where the bit bk is equal to "zero" in this position, and then, taking the difference between both distances:
(4.5 – 6)
A positive LLR corresponds to a "zero", and a negative LLR corresponds to a "one". Therefore, the larger the LLR is in absolute term the higher is the probability that a "zero" or a "one" was transmitted. An example of how the LLR calculation works is going to be shown next. The example uses a 4-QAM constellation map, and the received symbol has
been represented with an "x". Moreover, channel coefficients equal to "one"have been assumed to make the example easier to explain.
The example begins with the calculation of the LLR for the bit b0, situated
on the right side, as shown in Figure 4.5 – 1.

Figure 4.5 – 1: Example of calculating the LLR for the bit b0. In subfigure
(a), the minimum distance between the received bit and b0 = 1 is calculated.
Subfigure (b) makes the same calculation for b0 = 0.
  d1 is the minimum distance between the received bit and the points in the constellation map that have a bit equal to "one" in the position of the bit b0. The same operation is performed for the bit b0 equal to "zero", obtaining the distance d2. The numerical values for these distances are d1 = 1.56 and d2 = 0.92. The LLR can be calculated as the difference between both distances: LLR = d1 − d2. Replacing the numerical values, it has been obtained a result of 0.64 for LLR(b0).
The same steps must be followed to get the LLR value for the bit b1. This process is depicted in Figure 4.5 – 2. In this case, d1 = 1.43, d2 = 0.92, and LLR(b1) = 0.51.

Figure 4.5 – 2: Example of calculating the LLR for the bit b1.
Both LLR(b0) and LLR(b1) have positive values. Therefore, it can be concluded that the symbol "00" is the one that have been transmitted with the highest probability.
4.6 Decoder
The final stage of receive processing is the decoder. A block diagram of the decoder is depicted in Figure 4.6 – 1.

Figure 4.6 – 1: Block diagram of the decoding process.
  The decoder accepts the sequence of bits or LLRs from the demapper and, in accordance with the encoding method that was used, attempts to reproduce the information originally generated by the source. Like in the encoder block, the decoder is also composed of four steps, which perform diverse operations with the aim of reversing the process done by the encoder.
4.6.1 Deinterleaving
The deinterleaver rearranges the bits from each burst in the correct way by ordering them consecutively as before the interleaving process. It consists of two blocks, a general block deinterleaver and a matrix deinterleaver. These blocks work similarly as the ones used in the interleaver. The general block deinterleaver rearranges the elements of its input according to an index vector. The matrix deinterleaver performs block deinterleaving by filling a matrix with the input symbols column by column, and then, sending its contents to the output row by row. The parameters used in both blocks are the same as those ones used in the interleaving process3.
4.6.2 Inserting zeros
The block named "Insert Zeros" deals with the task of reversing the process performed by the "Puncture" block. As previously explained in Section 2.2.3, the puncturing process consists of deleting bits from a stream. The receiver does not know the value of the deleted bits but it can know their position from the puncturing vectors. Thus, zeros are used to fill the corresponding hollows of the stream in order to get the same code rate as before performing the puncturing process. The inserted zeros can also be seen as erasures from the channel. They have no influence on the metric calculation of the succeeding Viterbi decoder described in the following section.
4.6.3 Viterbi decoder
The Viterbi algorithm reduces the computational load by taking advantage of the special structure of the trellis code. Another advantage is its complexity, which is not a function of the number of symbols that compose the codeword sequence. The Viterbi algorithm performs approximate maximum likelihood decoding. It involves calculating a measure of similarity or distance between the received signal at time ti, and all the trellis paths entering each state at the same time. The algorithm works by removing those trellis paths from consideration that could not possibly be candidates for the maximum likelihood choice. When two paths enter the same state, the one that has the best metric is chosen as the "surviving" path. The selection of the different "surviving" paths is performed for all the states. The decoder continues in this way to advance deeper into the trellis making decisions by eliminating the least likely paths. The early rejection of unlikely paths is the fact that reduces the complexity. The goal of selecting the optimum path can be expressed equivalently as choosing the codeword with the maximum likelihood metric, or as choosing the codeword with the minimum distance metric. Furthermore, the delay introduced in the decoding process has to be taken into account. The rejection of possible paths does not really begin until the third step in the representation in the trellis diagram. This is due to the fact that until this time two branches can not have converged in one state, and thus, no decision can be done. This delay effect is considered in a parameter called traceback depth, which specifies how many symbols may preceed the beginning of the algorithm. For code rates of 1/2, a typical value for the traceback depth is about five times the constraint length of the code.
 Another parameters of the Viterbi decoder block of Simulink are the trellis structure used in the convolutional encoder, the decision type of decoding, and the operation mode. They are defined as follows:
 The type of signals that can support the Viterbi decoder block are based on the decision type parameter. This parameter can have three values: unquantized, hard-decision, or soft-decision.  As the decision process has been implemented in the demapper, the last kind of decision type, that is the "unquantized", is the one used in our simulator. It accepts real numbers as inputs for the decoder block. The positive numbers are interpreted as a logical zero, and the negative ones, as a logical one. However, when this parameter is set to "soft-decision", the entries of this block are integers between 0 (most confident decision for logical zero) and 2b (most confident decision for logical one), being b the number of soft-decision bits.
The operation mode parameter controls which method the block uses for transitioning between successive frames. The "truncated" mode, in which each frame is treated independently and the traceback depth parameter starts at the state with the best metric and ends in the all-zeros state, is the operation mode used in the simulator. Other values for this parameter are the "continuous" and "terminated" modes.
For more details about these parameters consult the documentation help of Matlab,
4.6.4 Reed-Solomon decoder
The last part of the decoding process is the Reed-Solomon decoding. It performs the necessary operations to decode the signal, and get, at the end, the original message sent by the source. As in all the receiver blocks, the RS decoder reverses the different steps performed by its corresponding encoding block, explained in Section 2.2.1. Thus, the RS decoder takes codeword of length n, and, after decoding the signal, it returns messages of length k, being n = 255 and k = 239, the same as the ones described in the RS encoder. Furthermore, the implementation for the RS decoder block has been performed with a Matlab S-function using a C-file4.
The block diagram of the RS decoder is depicted in Figure 4.6 – 2.

The input of the RS decoder block of Simulink accepts vectors, with a length that are integer multiples of ln. Its output is, in this case, a vector with a length that is the same integer multiple of lk. Hence, a process to get the correct amount of bytes that enter the RS decoder block, and afterwards, rearranges these bytes, needs to be performed firstly. After the encoding process, a data block with size (k + 2t) × NRS is obtained, as it can be appreciated in Figure 2.2 – 2. Nonetheless, the structure that will enter the decoder block has to be the same as the one that outputs the encoder block, before discarding the corresponding added bytes from the shortening and puncturing process. "Reshape 1" deals with the task of rearranging the data in a matrix form, with the specified size (k+2t)×NRS, being k and t the parameters listed in Table 2.2 – 1. The block "Insert zeros 1" adds 239 − k zero-bytes at the beginning of the structure with the aim of constructing the zero prefix. The 16 − 2k parity bytes are obtained from "Insert zeros 2". "Unbuffer" arranges the data from the matrix structure in a row vector. It has to be taken into account that this block introduces a delay equal to one frame in the system. Finally, "Select rows" has the task of selecting only the k original data bytes, and the "Buffer"-block redistributes its input samples in a new frame size, kNRS.
Simulation Results
In this chapter the simulation results are shown and discussed. In the following sections, first we will present the structure of the implemented simulator and then we will present
the  simulation  results  both  in  terms  of  validation  of  implementation  and  values  for various parameters that characterize the performance of the physical layer. Finally using the Simulik we will show the block diagram of OFDM based PHY layer WiMax simulations.
5.1 The Simulator
We have developed the simulator in Matlab™ using modular approach. Each block of the transmitter, receiver and channel is written in separate ´m´ file. The main procedure call each of the block in the manner a communication system works. The main procedure also contains initialization parameters, input data and delivers results. The parameters that can
be  set  at  the  time  of  initialization  are  the  number  of  simulated  OFDM  symbols,  CP length, modulation  and  coding  rate,  range of  SNR  values  and  SUI  channel model  for simulation. The input data stream is randomly generated. Output variables are available in Matlab™ workspace while BER and BLER values for different SNR are stored in text files which facilitate to draw plots. Each single block of the transmitter is tested with its counterpart of the receiver side to confirm that each block works perfectly.
5.2 Physical layer performance results
The objective behind  simulating  the physical  layer  in Matlab™  was  to study BER and BLER  performance  under  different  channel  conditions  and  varying  parameters  that
c h a r a c t e r i z e  t h e  p e r f o r m a n c e .  B u t ,  i n  o r d e r  t o  r e l a y  o n  a n y  r e s u l t s  from   P H Y  la y e r simulation we must have  some  results  that can do  some validation  in  terms of  general trends. The next section presents a set of scatter plot to identify trends in reception quality as we vary different parameters.
5.2.1 Scatter Plots
Figure 5.1 to 5.7 shows the scatter plots for different coding and modulation schemes as
SNR values are changed on SUI-1 channel model. The '+' symbol denotes the transmitted data and the '*' symbol denotes the received data. These plots are obtained by sending the same frame data from transmitter to receiver through the channel repeatedly 1000 times.
The input frame was taken from section of IEEE standard 802.16d. But, this does not confirm the presence of all constellation points, as it can be seen from the scatter plot  of  64-QAM modulation  (Figure.  5.6 and 5.7) where  few  constellation  points  are missing. It  can  be  observed  from  these  plots  that  spread  reduction  is  taking  place  with  the increasing values of SNR. This scenario validates the implementation of channel model. It  is  also  very  important  to  note  that  the  scatter  spread  gives  a  strong  hint  about  the BER/BLER statistics as SNR values are varied.
In Figure 5.8, we have observed the effect of channel model on scatter plot at an SNR of 35 dB. It can be seen that severe variation is introduced in SUI-4, 5,6 channel model even at high SNR value. It is clear that equalization is required for those three channel models.
Figure  5.9  shows  the  effect  of  CP  length  on  scatter  plot with  fixed  SNR  value. The differences are clearly visible that the scatter plots are less scattered for higher values of CP length.  Because,  the  capabilities  to  absorb multipath  effects  increases  with  higher value of CP length These  results  provide  some  interaction  of  the  PHY  layer with  channel model.  In the following subsections we will observe error rate statistics in the form of BER and BLER from our simulation. We will also observe the performance of different error correction capabilities of the implemented simulator.

Figure 5.2:  Scatter Plots for QPSK modulation (RS-CC 1/2) in SUI-1 channel model

Figure 5.3: Scatter Plots for QPSK modulation (RS-CC 3/4) in SUI-1 channel model

Figure 5.4: Scatter Plots for 16-QAM modulation (RS-CC 1/2) in SUI-1 channel model

Figure 5.5: Scatter Plots for 16-QAM modulation (RS-CC 3/4) in SUI-1 channel model

Figure 5.6: Scatter Plots for 64-QAM modulation (RS-CC 2/3) in SUI-1 channel model

Figure 5.7: Scatter Plots for 64-QAM modulation (RS-CC 3/4) in SUI-1 channel model

Figure 5.8: Scatter Plots for 64-QAM modulation (RS-CC 2/3) in different SUI channel model
5.2.2 Effect of Forward Error Correction
An  interesting  simulation  of  FEC  is  that without  the  concatenated Reed-Solomon  and Convolutional coder, how much performance degradation will appear  in this design. To figure out how much improvement of the concatenated code, the QPSK ½ modulation and coding profile is chosen on SUI-3 channel model. Figure 5.18 shows the performance of RS-CC compared to no FEC. FEC improves the BER performance by almost 6dB at -3 BER level of 10-3. Figure 5.19 shows the BLER performance for the same scenario. 10 dB SNR improvements is observed at BLER level of 10-2.
The observations made in Figure 5.18 and Figure 5.19 is repeated for 16-QAM 1/2 and 64-QAM 2/3 modulation and coding profiles also.  It can be seen  from  the Figure 5.20-3 and  5.21  that  FEC  gains  7  dB  improvement  at  BER  level  of  10-3  w h i l e  11.8dB improvement at BLER level of 10-2 .  In case of 64-QAM 2/3, Figure 5.22 shows 4.5 dB  improvement  is  observed  at  BER  level  of  10-3   and  Figure  5.23  shows  10  dB  improvement is observed at BLER level of 10 -2.

Figure 5.18: Effect of FEC in QPSK 1/2 on SUI-3 channel model
Figure 5.19: Effect of FEC in QPSK 1/2 on SUI-3 channel model

Figure 5.20: Effect of FEC in 16-QAM 1/2 on SUI-3 channel model
Figure 5.21: Effect of FEC in 16-QAM 1/2 on SUI-3 channel model


Figure 5.22: Effect of FEC in 64-QAM 2/3 on SUI-3 channel model
Figure 5.23: Effect of FEC in 64-QAM 2/3 on SUI-3 channel model
5.3  Simulink Analysis:
This demo represents an end-to-end base band model of the physical layer of a wireless metropolitan area network (WMAN) according to the IEEE 802.16-2004 standard [ 1 ]. More specifically, it models the OFDM-based physical layer called Wireless MAN-OFDM, supporting all of the mandatory coding and modulation options. It also illustrates Space-Time Block Coding (STBC), an optional transmit diversity scheme specified for use on the downlink

Fig IEEE802.16.2004 Wireless MAN-OFDM PHY Downlink
5.3.1. Structure of the Demo
 This demo showcases the main components of the WMAN 802.16-2004 OFDM physical layer using two models: one with STBC and one without, which has all the mandatory coding and modulation options. The tasks performed in the communication system models include:
Generation of random bit data that models a downlink burst consisting of an integer number of OFDM symbols.
Forward Error Correction (FEC), consisting of a Reed-Solomon (RS) outer code concatenated with a rate-compatible inner convolutional code (CC).
Data interleaving.
Modulation, using one of the BPSK, QPSK, 16-QAM or 64-QAM constellations specified.
Orthogonal Frequency Division Multiplexed (OFDM) transmission using 192 sub-carriers, 8 pilots, 256-point FFTs, and a variable cyclic prefix length.
Space-Time Block Coding using Alamouti's scheme. This is implemented using the Embedded MATLAB fcn block for both the encoder at the transmitter and the combiner at the receiver.
A single OFDM symbol length preamble that is used as the burst preamble. For the optional STBC model, the single symbol preamble is transmitted from both antennas.
A Multiple-Input-Single-Output (MISO) fading channel with AWGN for the STBC model. A choice of non-fading, flat-fading or dispersive multipath fading channel for the non-STBC model.
OFDM receiver that includes channel estimation using the inserted preambles. For the STBC model, this implies diversity combining as per .
Hard-decision demodulation followed by deinterleaving, Viterbi decoding, and Reed-Solomon decoding.

Fig OFDM Transmitter

Fig OFDM receiver
Both models also use an adaptive-rate control scheme based on SNR estimates at the receiver to vary the data rate dynamically  based on the channel conditions. The models use the standard specified set of seven rates for OFDM-PHY, each corresponding to a specific modulation and RS-CC code rate as denoted by  rate_ID (see Table below )

Rate_ID Modulation RS-CC Rate
0 BPSK 1/2
1 QPSK1/2
2 QPSK 3/4
3 16 QAM 1/2
4 16QAM 3/4
5 64QAM 2/3
6 64 QAM 3/4
The STBC link model uses a MISO fading channel to model a two transmitter, one receiver (2×1) system. The fading parameters specified are assumed to be identical for the two links. The Space-Time Diversity Combiner block uses the channel estimates for each link and combines the received signals as per [ 2 ]. The combining involves simple linear processing using the orthogonal signaling employed by the encoder.
Furthermore, the models include blocks for measuring and displaying the bit error rate after FEC, the channel SNR and the rate_ID. A scatter plot scope is used to display the received signal, which helps users visualize channel impairments and modulation adaptation as the simulation runs.
The subsystems and blocks used in the models are color-coded to make viewing easier. The communication system operations are in blue, control systems and signals are in orange and the performance evaluation, displays and plots are in yellow.
5.3.2. Simplifications and Assumptions
         For simplicity, the models in this demo:
Set the number of OFDM symbols to be constant for all data bursts generated. As a result, for any given profile, the frame duration in Simulink remains the same.  Also, within the downlink frame only the downlink bursts are modeled, i.e. the long preamble and the FCH burst are not modeled.
Do not model the Randomization specified as a part of the channel coding as the data is randomly generated. The library file has blocks which cover this functionality.
Assume perfect synchronization between the transmitter and receiver. As a consequence, they only use a short preamble for every downlink burst.
At the receiver, estimate the channel using only the inserted preambles and not the pilot sub carriers. This assumes that the channel is not changing very rapidly (or is constant for the number of OFDM symbols in a burst).
5.3.3. Exploring the Demo
The Simulation Settings configuration block on both models allows you to choose and specify system parameters such as channel bandwidth, number of OFDM symbols per burst and the cyclic prefix factor. Varying these parameter values allows you to experiment with the different WiMAX profiles as defined by the WiMax Forum [ 4 ], and gauge the system performance for each.
 The other parameter of interest is the Low SNR thresholds for rate control parameter, as it directly affects the adaptive-rate control in the two models. This parameter is a six-element vector representing the boundaries between the adjoining seven SNR ranges that correspond to the seven rates. Ideally, the simulation should us   the highest throughput mode that achieves the desired bit error rate.
Another area of variability includes the channel blocks in the two models. The models allow you to vary the fading parameter and the AWGN variance (in SNR mode) added to the signal. As a result, you can examine how well the receiver performs with different fade characteristics (choosing the appropriate maximum Doppler shift, number of paths, path gains) and generate BER curves for varying SNR values.
5.3.4. Results and Displays
When either of the two models are simulated, windows come up automatically to display the spectrum plots of the transmitted signal per antenna and a scatter plot of the received signal prior to demodulation.

Use the spectrum plots to verify the channel bandwidth in use and the subcarrier spacing. Use the scatter plots to gauge which modulation type is in use, as the plot resembles a signal constellation of 2, 4, 16, or 64 points under good channel conditions.
 The following blocks display numerical results:
The Bit Error Rate Display block shows the bit error rate, number of errors and the total number of bits processed.
The Est. SNR (dB) display block at the top level shows an estimate of the SNR based on error vector magnitude. The  SNR block in the Channel subsystem shows the SNR based on received signal power.
The RateID display block shows the  rate_ID that corresponds to the specific modulation RS-CC rate currently in use.
Wimax Growth and economics
6.1 Why WiMAX?
Besides the technology advantage of WiMAX that has be discussed, we would like to present below some other factors for the emerging of such technology. First, DSL and cable mode access is extremely expensive for current and potentialsubscribers. It is highly costly and time consuming to set up connections by laying the land-based facilities to exurban or backland. Moreover, the deployment speed is very low with high investment venture and limitation of terrain. WiMAX can be applied as a better choice. Low cost and easy deployment of WiMAX are considerable features for most of wireless operators. On the other hand, the emerging of 3G has shown great advantage to mobile communication market for providing personal voice and data service to customer through mobile phone. But the development situation of 3G is not ideal as we expected. The majority of services are still concentrated on voice and SMS applications. One of the reason is that 3G is not enforced in providing high speed data service. WiMAX can support very high bandwidth solutions with various spectrum deployment choices. Third, Wi-Fi application has been serving wireless broadband market for a few years and has been widely spread around the world, due to the feature of low cost and easy deployment. But Wi-Fi aims for the connectivity in local area network. It has limitation of coverage to support long distance services. It could only transmit data up to a few hundreds feet. WiMAX provides wide range coverage and quality of service (QoS) capabilities for applications.
One of the reasons that we should pay attention to WiMAX is that it gives an answer to mobile applications. It provides broadband wireless access in metropolitan area which fills the gap between wireless wide area network (WWAN) and wireless local area network (WLAN).This allows operators to have special market segments for WiMAX, for instance, the wireless broadband access service in rural area as an alternative of DSL and cable modem.At last, it is a trend of telecommunication industry, rather than a technology that presents at the market transitorily, because of the strong backing of WiMAX forum,which is formed by around 400 market players. The dedication of many market actors brings in tons of opportunities to this both now and in the future.All this factors promote the development and emerging process of WiMAX.
6.1.1  WiMAX, Wi-Fi and 3G
WiMAX, Wi-Fi and 3G can be regarded as three different types of wireless access technology according to the coverage area of data transmission as shown in figure,

Wi-Fi—-Wi-Fi is Wireless Local Area Network (WLAN) technology, which enables customers to set up wireless connections within a certain local area such as home, office building, airport, etc. It only focuses on fixed and portable wireless access applications, as shown in the figure.
WiMAX—–as I mentioned before, is Wireless Metropolitan Area Network (WMAN) technology that enables users to establish wireless connections between multiple locations within metropolitan area such as the connectivity between central office building and branch office, or campus. It covers all the kinds of applications by fixed and mobile WiMAX.
3G—–3G is Wireless Wide Area Network (WWAN) technology. It enables user to connect to the high speed mobile Internet through mobile device, like mobile phone and PDA. It provides ubiquitous applications and supports various types of multimedia communications.
6.1.2 WiMAX & Wi-Fi Introduction of Wi-Fi
Wi-Fi is the short name of wireless fidelity, designed based on IEEE802.11 standards. It is a big family with various versions, and generally refers to 802.11b and 802.11g which is widely used in the current market. 802.11b uses 2.4GHz ISM band frequency which is universally adopted by most of the countries around the world. This makes 802.11 spread rapidly and widely. 802.11b could offer high speed data transmission at a speed up to 11Mbps. There are 14 channels available in 2.4GHz with only three non-overlapping channels. It could offer coverage of maximum 300 feet in the outdoor environment and 100 feet in the indoor environment. Wi-Fi provides reliable data transmission and network bandwidth by using kinds of connective protocols and data package validations that are similar to Ethernet. The design of 802.11g version is based on and backwards compatible with 802.11b. 802.11g imported security enhancements to work at the same frequency band as 802.11b. It adopted OFDM modulation scheme technology to support the data transmission at a speed up to 54Mbps30. The standard was certified by Wireless Ethernet Compatibility (WEC) Alliance which was renamed as well-know Wi-Fi alliance in 2003. This alliance is organized by leading wireless equipment and software providers like Nokia, 3COM and so on. The initial motivation of Wi-Fi alliance is to focus the solution of interoperability challenges and testing of Wi-Fi system. Wi-Fi Alliance holds the  Wi-Fi CERTIFIED logo, a registered trademark, which is permitted only on compliant equipment. Since the start of this certification in March 2000, more than 3300 types of products have been granted with Wi-Fi CERTIFIEDTM31. This has strongly prompted the fully expansion of Wi-Fi products and services in consumer and enterprise market. The similarity between WiMAX and Wi-Fi
Both WiMAX and Wi-Fi are technologies for wireless broadband. We could consider WiMAX as a big brother of Wi-Fi. They have some similarity if we compare them with each other.Both of them are designed to run with IP network, and mainly targeted for data transmission. WiMAX and Wi-Fi standards both belong to IEEE wireless standard. Both of them are supported and promoted by the alliances which are formed by numbers of industry actors. WLAN and WiMAX alliances are promoting the development of these two standards in nearly the same way. They are addressed to handle interoperability and take prevision testing by the contribution from hundreds of members. The products for Wi-Fi and WiMAX could be respectively compliant with each other by certification procedure from these two organizations. Some members of WLAN alliance have become the member of WiMAX forum. The Difference Between WiMAX and Wi-Fi
The comparison (superposition) between WiMAX and Wi-Fi standard is mainly focused on the comparison of IEEE 8021.16d and 802.11a/b/g standards.
Technology Difference
The first difference is transmission range. As mentioned, Wi-Fi enables connectivity in local area. WiMAX addresses on the wireless access in metropolitan area. Wi-Fi is basically designed for preferable indoor environment wireless access. While, WiMAX have both LOS and NLOS access performance, it has promised remarkable connectivity in both indoor and outdoor environment. IEEE802.16d promises to offer wide range wireless connection up to 30 miles with expected transmission rate around 75Mbps from a single station. While, 802.11g could provide a wireless access around 300feet with speed up to 54Mbps. Wi-Fi hotspots could typically reach about 1000 feet (300m) outdoor or 328 feet (100m) indoors due to the network interference. The difference is mainly because they have different design idea and technology adoption of PHY (physical layer) and MAC (Medium Access Control layer) layers. The technology adoption of 802.11 in MAC layer is not appropriate to use of long distance transmission for the WMAN environment. The bandwidth used in PHY structure has limitation of transmission power. WiMAX was defined with more robust PHY and MAC technology than Wi-Fi. The second difference is bandwidth. 802.16d provides wider bandwidth than Wi-Fi since it works on both licensed and licensed-exempt frequency bands. WiMAX network operator could feel free to allocate channel bandwidth. 802.16g system uses unlicensed bands of 2.4GHz frequency with a few non-overlapping channels, which means that traffic jamming could happen if many users use it at the same time. The third difference is number of users per network. WiMAX MAC protocol is designed to support thousands of subscribers; contrastively the design of Wi-Fi MAC protocol could only support around 10’s users according the 802.11g specification with 8-10 non-overlapping channels34. The last different point is the support to QoS. Both of the standards have defined QoS into their feature list. Wi-Fi although introduce QoS at 802.11e version, the specification is still not standardized by now. QoS is designed into 802.16 from the beginning, and has been differentiated into different service types. It is much matured in WiMAX then in Wi-Fi. Figure 13 shows the main technology feature between 802.11 and 802.16.
(2) Business and Application Difference
The most fundamental difference between WiMAX and Wi-Fi is that they are designed for different application mode. The idea of Wi-Fi focuses on the wireless connectivity within smaller area than WiMAX. It provides broadband wireless access for home and office local area network. WiMAX mainly is used for the service of high speed data access in both fixed and mobile environments. Wi-Fi only focuses on the connectivity of fixed wireless access.
6.2. WiMAX & 3G
6.2.1 Technology Comparison
Mobile WiMAX is based on the advanced technology OFDM which is considered as the core technology of 4G. The technology offers scalability in both radio access and WiMAX network architecture; it provides flexibility of network deployment and good service offerings. WCDMA and CDMA2000 are widely used 3G standards in the current mobile communication market. To compete with WiMAX and upgrade the system performance of 3G technology, 3GPP has developed the HSDPA enhancement for WCDMA. 3GPP2 has developed 1xEVDO-Rev 0 and 1xEVDO-Rev enhancement for CDMA2000 to provide throughput improvement for data traffic. WiMAX has some advantages to 3G, such as the larger coverage and higher transmission speed. The transmission coverage of a WiMAX base station is around ten times of the coverage as a 3G tower. WiMAX support scalable channel bandwidth to efficiently utilize spectrum. WiMAX support smart antenna technology to eliminate multi-path propagation to offer better quality of service. WiMAX offers QoS control for each service flow over the air interface. QoS in 3G is limited to priority system on all the service flows. During heavy load period of network, high priority traffic might starve the low priority traffic in 3G, but this will NOT happens in WiMAX. The Spectral Efficiency and Sector Throughput of WiMAX are better than 3G. The figure shows the comparison of spectral efficiency and sector throughput between 3G standards and mobile WiMAX. As we can see from figure, mobile WiMAX presents the obvious advantage over the enhancement standard of 3G in both sector throughput and spectral efficiency in both downlink and uplink directions. The sector throughput or WiMAX are even 2 times better than other two 3G standards
6.2.2 Market Possession Comparison
3G technologies have been serving the mobile market around many years. It was designed for the universal mobile communications. The development market is more mature than WiMAX. Especially, along with the development of WiMAX technology, the evolution of 3G standards becomes threats to the success of WiMAX. Mobile operators have present less passion to deploy WiMAX and more willingness to upgrade their 3G network which they have already spent lots on. HSDPA technology is standing on more advantage position than mobile WiMAX in the mobile market. It was launched to the market at later 200539, while mobile WiMAX are still not commercially roll-out to the market. HSDPA was depending on the strong technology and market support by the strong standard background. The change from WCDMA to HSDPA could be easily achieved by upgrading the relative software. The growth of Mobile WiMAX technology will need an uncertain period to get mature after launching to the market. Mobile WiMAX and 3G will coexist for some years. These two technologies will finally get converged and integrated together towards 4G. Mobile operators could deploy WiMAX as overlay network to help 3G reduce the network congestion. They also could combine 3G and WiMAX network to offer high quality cellular backhaul service to increase user ARPU.
6.2.3 Spectrum Cost and Operating Cost Comparison
Mobile operators who owns 3G network have not only spent hundreds of billion dollars on acquiring 3G operating licenses. But also, they are spending tens of billion dollars in order to operate the network. Whereas, WiMAX license fee is much lower comparing with 3G. Take example for the situation in Germany, at the end of last year, Germany government has auctioned a few WiMAX licenses to operators. The result is 360 million euros per licensee. It is quite a bargain to 50 billion euros bill spent for UMTS licenses.40 One of the advantages of WiMAX standard is that the system can work on the licensed-exempt frequency bands. This could highly reduce the initial capital expense. At the same time, high performance of system helps to lower down the deployment expenses. WiMAX network has larger coverage than 3G. One base station could transmit signal up to 30 miles, which is ten times of the transmission coverage through a 3G tower. This means broad coverage with deploying fewer base stations. Until now, there is no clear IPR (Intellectual Property Rights) policy for WiMAX standard. WiMAX IPR fee would be divided into several minor segments. WiMAX is an open standard and have healthy ecosystem. The core technology will be hold by different vendors. As benefit from the result, there would not be any vendors to monopolize the core technology and ask for a high price as happened in 3G.
6.3. WiMAX Applications and Usage
According to the specification from WiMAX forum, WiMAX supports many types of wireless broadband connections, and thus, can be used for broadband applications in public, fixed and mobile networks. It can handle the services that Wi-Fi offers, since they have similar technology infrastructure beneath. WiMAX supports smart antenna technology which utilizes frequency band in efficient manner. The typical usage that WiMAX can address involves last mile problem, backhaul and some other application for private and public network. For personal applications, WiMAX could handle VOIP, IPTV, Video conference, online gaming, and so on.
6.3.1. Applications Focus
WiMAX provides very high capacity of connection and at the same time supports Ethernet, IP and many other advanced protocols. The high performance WiMAX network with high QoS can be used for many real-time applications. As shown in the table, these applications include interactive gaming, VOIP, Video Conference and streaming media, for example IPTV. Meanwhile, high-speed Internet and media content download, such low time and QoS demanding services are also covered in the application range.

6.3.2. VoIP over WiMAX
VoIP application is expected to be one of the dominating WiMAX services in the future. The value proposition of VoIP is that this low-price service could immediately bring VoIP application is expected to be one of the dominating WiMAX services in the future. The value proposition of VoIP is that this low-price service could immediately bring benefit to most of users with voice and data connection solution. VoIP calls can be received or set up at a very low or zero additional cost for the customers. So that the service providers could get returns from the initial increasing ARPU. At the same time, to provide VoIP over WiMAX network will not challenge the voice revenues from mobile operators. 3G technology (CDMA and WCDMA) is designed to offer intensive coverage of voice communications which WiMAX is not able to substitute. However, mobile operator may move some voice traffic to WiMAX infrastructure and offer some high quality service to some important customers due to some performance limitations of 3G network capacity. WiMAX has QoS features built in mind at the time of design. As one of the most crucial sustainment for VoIP service, low latency and connection stability are well supported through QoS in WiMAX. After years of application among huge number of customers, VoIP becomes a big competitor of traditional voice services by offering the low price and good quality of conversation. Voice is transferred by this service as data package through personal broadband network or public Internet. This solution makes VoIP service provider able to avoid the high operation cost of PSTN by using the cheap resource of Internet. Through providing VoIP service, service providers could not only lower the cost but also cooperate with traditional telecom operator to enrich the content of service and get benefit from web-based voice and video control. Currently, VoIP can be transmitted via PC, IP network, laptop, and Wi-Fi handset. Although the highlighted application of WiMAX is to provide high quality data service across broadband wireless network, it is not out of expectation that VoIP service is still needed to be sustained as basic application, especially by the dramatically increasing demand of VoIP. In order to preempt the market of VOIP over WiMAX, at present, some service providers have already launched this service to customers. For instance Vonage, one of the leading VoIP providers, has started their cooperation with TowerStream, a WiMAX provider, to launch WiMAX VoIP service in some of the areas in American. The competitions with traditional telephony background are emerging. Some other operators are also attempted to offer such service in the near future. According to the report from IN-Stat/MDR say that WiMAX subscribers will reach 8.5 million in 2009, It is about 3% of whole broadband market, and among this number, the subscribers who order VoIP services will exceed over half. WiMAX accelerates the popularization of VoIP. VoIP over WiMAX solution is the combination of wireless technology and the low price VoIP. WiMAX provides extremely cost-effective and high-quality voice or video conversion with data service. It adopts point-to-multipoint air interface QoS as technique foundation, which supports a highly ensured low-latency network. This kind of network is the key to a successful VoIP deployment that requires the voice and video are transmitted in high quality, and at the same time, with low-latency Wireless VoIP network is much less expensive to set up, install and maintain at home than wired network. People could feel free to make phone call at the place where WiMAX has been covered with. Moreover, mobile VoIP is also not far away from us, which brings more flexibility and mobility. Even though there are some technology barriers that people need to solve, such as, lack of perfect network structure and reliability, security and authentication, the QoS problem in mobile environment, and so on. But it is the trend in the near future. Microsoft, Intel and Nokia, such leading companies have been attempting to develop relevant equipment, such as WiMAX phone and chips. Nokia has clearly announced that Nokia WiMAX phone will be put into production in 2008. And at the same time, WiMAX base stations will also be pushed into operation for broadband service providers. As forecasted, it could offer 2.5GHz bandwidth at the end of 2007, and rise up to 3.5GHz at the first quarter of 2008. We will witness this in the coming two years. Rural Connectivity
The universal broadband access connectivity is even a problem in developed countries, due to the poor coverage in rural areas. Rural areas typically are defined as small city or towns that are located far from a metropolitan area. These areas are typically underserved or have not been deployed with wired infrastructure. The complex landform and physiognomy of rural area is difficult and extremely expensive for telecom operators to deploy wired broadband connection. While, wireless technology is the best choice for them from economical point of view. Other early emerging wireless access technology such as LMDS、MMDS、Wi-Fi does not offer wider coverage which is indispensable for rural environment. WiMAX solution could offer up to 30miles coverage, and the base station sectors could cover numbers of residential in town or village. WiMAX provides opportunities for many wireless Internet service providers. These big or small service providers could provide backhaul service for rural area or suburban outskirts of cities. As illustrated in the figure, the residential CPEs could receive data from subscribers or directly from the centre base station according to the situation of different locations.

Figure 14 WiMAX Solution in Rural Areas70
The deliver of rural connectivity is critical in many developing countries and underserved areas of developed country. WiMAX QoS feature ensures the real-time voice transmission and low latency, so that WISPs can even offer VoIP service and IPTV services to the rural areas. The deliver of rural connectivity is critical in many developing countries and underserved areas of developed country. WiMAX QoS feature ensures the real-time voice transmission and low latency, so that WISPs can even offer VoIP service and IPTV services to the rural areas.
6.4 Overview of WiMAX Market
At the beginning of 2006, WiMAX forum issued its first certificate which is used to mark products that comply with 802.16-2004 wireless standard. From then on, fixed WiMAX market starts to get rapid market growth all over the world. The investments in global WiMAX market have reached up to nearly six hundred million dollars in 2006, most of which are used for fixed WiMAX market. On the other hand, mobile WiMAX system could provide mobility solution and at the same time support fixed and portable connectivity. In year 2007, mobile WiMAX market will be rising quickly, for the reason that the operation of mobile WiMAX service could bring more revenue for operators and vendors than fixed WiMAX. The statistic of TeleGrography shows that there are more than 200 operators in the world, 72which are planning their WiMAX strategy. They are either planning WiMAX rollouts or have already deployed trial or commercial systems.

Figure 15 WiMAX Development by Region 73
As shown from the figure, WiMAX is rolling out all over the world. Most of the deployments and plans for WiMAX network are concentrated on developed country. It is also apparent that Asia-Pacific area presents a huge market potential by a high percentage in both deployment and applied trial. Companies in Europe and Asia-pacific have already launched commercial services over fixed WiMAX network, such as WiMAX telecom in Europe, Yozan in Japan, and Enforta in Russia. Around the world, there are 24 WiMAX networks built in the phase of commercial use. The licensed WiMAX network deployment is mainly concentrated in Europe. According to the statistical report from In-star, there are around 22.2 thousand subscribers using WiMAX network by the end of 2006
6.5 Analysis of WiMAX Market Potential
Based on the discussion from above chapters, we are going to analyze the market potential of WiMAX in this chapter. SWOT methodology is used here as an analysis tool due to the reason that we need to find out the strategy of deploying WiMAX in different markets as the result of analysis, and this method is good at deriving strategy at the end. We will not go through the strategy analysis for all the market players, on account of the limitation of this report. The analysis will mainly study the strategy for operators and service providers, since they are the forerunner and key players of WiMAX market
6.6 Strengths and Weaknesses

As listed in the table, WiMAX service has many advantages due to the adoption of advanced technology and the well-defined value proposition. The main advantage of WiMAX technology is the well-design of PHY and MAC layer, especially the adoption of OFDM and OFDMA technology as we have mentioned in the former chapter. Besides this strength, other strengths include:
The adaptation of MIMO smart antenna technology could efficiently eliminates the adverse effects of multi-path propagation and thus improves the service quality of WiMAX network.
WiMAX technology supports both LOS and NLOS connection, and can be deployed with multiple access mode by its flexible network infrastructure. These access modes include Wi-Fi hotspots access, mesh access and so on. WiMAX network could either combine other wireless network to provide services or provides its own network solution. These flexible designs also provide cost-effective solution in some markets.
 Mobile WiMAX system supports scalable higher bandwidth (mobile WiMAX: 1.25-20MHz, 3G: 5MHz) and higher throughput than 3G network. Fixed WiMAX also provides larger coverage than other BWA technology such as Wi-Fi today.
 It support QoS guarantee mechanism to ensure low latency IP connection such as VOIP service. This advantage also makes good sense in transmitting real-time multimedia data such as for IPTV streaming service.
The development of WiMAX technology does not have expensive spectrum problem which ever happened in 3G history. Governments have been aware that the costly 3G spectrums have blocked the operation of 3G services for operators at certain degree. So undoubtedly, costly spectrum acquirement would not possibly happen in WiMAX market. The government also present active attitudes towards flexible manage spectrum resource for innovation technology.
 The standardization of CPE can bring interoperability and low cost solutions. The operator can get benefit from wide device availability of the new technology with multi-choice of vendors.
 WiMAX could work on both licensed and unlicensed bands, and these bands are already available in most of countries. Supporting multi bands allows WiMAX to provide multi-level services through different condition of frequency bands Even though the deployment cost of fixed WiMAX is more expensive than DSL in developed market, along with the enhancement of hardware and software standardization, the cost will drop down fast to compete with DSL. Especially, the cost of using WiMAX to upgrade DSL is much less expensive than using fiber
6.6.2 Weaknesses
WiMAX secure issue is still a problem. The authentication mechanism and the quality of secret key are not good enough for operating high-secure network despite that WiMAX has security feature.
Currently, fixed WiMAX network could not be fully compatible with mobile WiMAX network. This will result in limitation for service providers to upgrade their fixed WiMAX network to mobile network.
Various deployment and development path could be targeted for new innovation of WiMAX technology. The revenue model and profit share model for carriers are complex and not matured yet. There is still no ready model for WiMAX services. Some small service providers may not invest on it before they are certain about their market position and their future vision.
WiMAX supports multiple bands in both licensed and unlicensed frequency, this is a double-edged knife. The advantage is that WiMAX can work on multi bands and is flexible for providing multi-level services. Disadvantage is the lack of available uniform and harmonized spectrum. This may become a barrier for international roaming and decrease the value of interconnection of WiMAX service.

Table 8 Opportunities and Threats
6.7 Opportunities in Developed Market
The converged network infrastructure needs the combination of cellular and broadband network, since both of them have advantages on the network performance. Wireless broadband technology is the best choice with higher transmission speed than wired access mode for developed market to achieve the goal.
The design of short coverage Wi-Fi services limits the speed and coverage of wireless Internet access. The laptop with embedded Wi-Fi chips could only get access to Internet within 300 feet. This limitation provides opportunity for WiMAX to extend the wireless connectivity up to 30 miles with high transmission speed.
 In developed market, such as Korea, Japan, multimedia, online gaming and IPTV applications become more and more popular. These applications need high transmission speed and possible large area mobility which WiMAX technology could provide.
 In developed market. Most governments in US, Europe and Asia present active attitude on WiMAX regulation aspects. They have allocated both licensed and unlicensed bands to allow operator and various service providers to develop appropriate applications.
 Under the good regulation environment, the major vendors have first promoted the deployment of operators and service providers in these markets. Intel, Motorola, Alvarion and other powerful vendors are the advocates of OFDM technology and WiMAX advantages. Their supports drive the development of WiMAX service and push the standardization process in a certain degree. The support of these vendors includes development, production and research.
6.8 Opportunities in Developing Market
 Most developing countries have limited DSL broadband access or even no broadband access at all. Along with the increasing of economy scale, there exists huge market potential for WiMAX service, which would bring economical solution, flexible and fast installation for this market.
Governments in developing market also holds active attitude from allocation and regulation aspects. They believe WiMAX network could bring low cost and fast deployment broadband wireless solution to increase the average of broadband access and satisfy the increasing needs of customers.
The user requirements in these markets have been highly pent-up, since underserved broadband network infrastructure somehow impeded the increase of economy. This presents huge opportunities for deploying widespread WiMAX network.
3G haven’t been issued until now in some developing markets. Thus, mobile WiMAX might have chance to become a big competitor and wide deploy in these markets due to the timing advantage.
For WiMAX players, especially international and local vendors, developing market have huge potential to become the major market for WiMAX, because of the high demands and poor support of network infrastructure.
Last mile access problem has been the biggest challenges for other BWA technologies to be the alternative of DSL and provide wireless DSL solution. WiMAX could solve this problem and thus have opportunities to be the most appropriate BWA technology for these markets.
6.8.1 Threats in Developed Market
DSL broadband access widely deployed in developed market gives very limited opportunities for fixed WiMAX deployment. Especially the cost of fixed WiMAX services is higher than DSL. Also as a new comer, WiMAX could get less trust from customer than DSL.
 2G/3G network is widely rolled-out in these markets. 3G subscribers are growing, and the upgrading version – HSDPA has been launched to the market as well. In the contrary, the launch of mobile WiMAX is expected to happen at some day in next year. This factor will threaten the development of mobile WiMAX.
Lack of the support from many mobile operators is another barrier for the market growth of mobile WiMAX. Mobile operator might only consider to deploy mobile WiMAX as supplementary network or even would not deploy it at all since they regards mobile WiMAX more as a competitive technology then a complement.
6.9 Analysis of Market for WiMAX Service CICT
Threats in Developing Market
Some governments in developing market perform strict regulatory policies to telecom industry. They consider telecom as the nation-related industry. In these markets, most of telecom companies are controlled directly or indirectly by the government. The emerging of WiMAX brings threats and competitions to the current wired incumbent operators. The governments may only allow wired and wireless incumbent operators to deploy WiMAX services and thus control the operation of WiMAX. And other providers might have no chance at all to enter this market.
 Mobile operators may still wait for the unissued 3G licenses. Since the operation of 3G service could be national wide and incumbent service for personal communication which WiMAX network could not exceed. Even they have motion on trail and test WiMAX network, but WiMAX is still considered as backup network or complement network. This negative consideration may lower down the development process of WiMAX service in these markets.
The low density of population may not bring significant ARPU to service providers compared with the developed market. The deployment of WiMAX without suitable prepare may get negative effect.
Perspective of Wimax in Bangladesh
Agni Systems Deploys WiMAX in Bangladesh for Wireless Internet Access
12/6/06 – Motorola, Inc. (NYSE: MOT) announced that Agni Systems Ltd, an Internet service provider (ISP) in Bangladesh, has started a phased WiMAX deployment to provide wireless broadband access in Dhaka, the capital of Bangladesh, and then gradually to other metropolitan cities. The 11-year old ISP's deployment builds upon Motorola's momentum in delivering commercial WiMAX networks around the world.
Commercial services are expected to start in January 2007 and the entire deployment is expected to be completed by mid-2008. Phase one of the deployment will be a fixed outdoor solution using Motorola's Access Point (AP) 100 series system. Phase two, expected to start in Q3 2007, will extend Agni's system to an 802.16-2005 mobile WiMAX system using Motorola's WiMAX Access Point (WAP) 400 series system with MIMO techniques.
Agni's managing director, Mohammed Abdus Salam, said that Motorola's AP 100 series system provides a quick, cost-effective way for Agni to roll out wireless broadband services to areas with high subscriber density in order to quickly realize its ROI objectives. He said: "This will allow Agni to justify its future migration to the carrier class WAP 400 platform that supports fixed, nomadic and mobile subscribers." Salam said he considers the AP 100 series system a first step in enabling Agni to gain experience in preparation for managing a full-fledged WiMAX deployment.
Jay Andersen, vice president, sales for Motorola Networks & Enterprise, South and East Asia, said WiMAX is key to providing high speed wireless broadband in emerging countries like Bangladesh that have a huge population spread over a small area. "With WiMAX, existing operators like Agni can provide wireless high speed data that will be able to support rich applications using voice and data. It also allows operators to connect under- served and un-served markets that represent the next potential growth area in the broadband market."
The Agni Systems WiMAX deployment will also include Motorola's WiMAX subscriber devices, Motorola's wi4 fixed point to point solutions, as well as a suite of services that span planning, installation, operations and maintenance.
Agni's investment in Motorola's equipment is being funded by World Wide Opportunity Fund (WWOF), a global investment fund managed by Terra Partners, Ltd., a New York money manager. Harold Golden, Chairman of Agni Systems and CEO of Terra Partners said that WWOF has formed the world's first Bangladesh country fund with the specific purpose of funding Agni's use of Motorola's WiMAX solution to overcome Dhaka's significant last mile challenges.
"The knowledge and support Motorola agreed to provide to Agni was a significant factor in Terra's decision to support Agni's expansion plan," said Golden. "Agni's purchase of Motorola equipment is thus backed by one of the first major investments in Bangladesh by a foreign institutional investor and shows confidence in both Motorola's WiMAX solution and the future of Bangladesh."
Motorola's wi4 WiMAX products are part of the MOTOwi4(TM) portfolio of wireless broadband solutions and services that create, complement and complete IP networks. Delivering coverage to virtually all spaces, MOTOwi4 includes wi4 WiMAX, wi4 Fixed Broadband, wi4 Mesh, and wi4 Broadband over Power Line solutions for private and public networks.
How Does it works in Agni:
Basically, WiMAX system mainly consists of two parts – base station and WiMAX receiver. Base station is a tower which is similar to the concept of cell-phone tower that works together with a set of indoor electronics. A single WiMAX tower can provide widely coverage up to 30 miles radius at maximum, depending on the tower height, ntenna gain and transmission power. Typically, the deployments will use cells of radius from 2 to 6 miles, so that the wireless node could get access within this range.
The center base station is connected with a number of subscriber’s station, which is referred as customer premise equipment (CPE) receiver. The WiMAX communication network utilizing base station and CPE to build up wireless communication system areshown in figure 6. WiMAX receiver could be either installed as a small box out door of
house and building, or integrated in the personal computer as memory card, or built into a laptop as the way Wi-Fi access does today

Figure 5 WiMAX 802.16 Network Source: Intel
Figure5 shows the basic concept of fixed WiMAX. First, a subscriber sends a wireless access query from the fixed antenna on top of a building or using indoor CPE. The base station receives transmissions from multiple sites and sends the traffic over NLOS or LOS links to a switching centre by using 802.16d protocol. Then the switching centre sends traffic to the ISP or PSTN to access Internet.
While in mobile WiMAX network, the terminal such as laptop, PDA and WiMAX phone that are embedded with WiMAX chips inside could directly receive the signal from nearest tower, and the user could be portable and move within a certain region up to 30 miles.
Backhaul refers to both the connection from access point (or cell site) to switch center and the connection from switch center to core network, i.e., from a remote site to a central site. Backhaul is used to transmit data through backbone system. Backhaul network is the intermediate of telecom network infrastructure; it is deployed between access points to core network and provides fundamental connection for them. For instance: the customer intends to set up a connection to Internet through WI-FI, but WI-FI equipment must connect to service provider side for further connection. This connective role could be played by WiMAX system. By adopting such technology, service provider could cut back operating cost and provide better quality, wide range and high speed connections. There are several driving factors that could propel relative operators to move towards WiMAX.
First of all, the amount of customer demands for wireless broadband and cell network is increasing progressively. WI-FI WLAN applications are kept on expanding. More and more operators need backhaul mode to enhance the interpretability. Second, WiMAX joints several base stations to one another by using high speed backhaul microwave links. This allows subscribers to roam from one base station to another in the covered range of network, like the way that cell phone roaming in mobile network.
Third, the cellular operators could consider using the WiMAX NLOS connection between base stations to extend network coverage range when they intend to deploy wireless access network in bigger range.
Fixed WiMAX is an appropriate choice to use for three backhaul application areas – cellular backhaul, WI-FI hotspots, and WI-FI mesh network. WiMAX backhaul have advantages like high bandwidth, long distance transmission, high speed and reasonable cost. It can provide point-to-point links with the coverage up to 30 miles. With the data rates capable of support multiple T1/E1 service, cellular operator will have opportunity reducing the cost of T1/E1 backhaul by using WiMAX equipment and build up backhaul base station traffic to their network operation and Switch center.58Another feature of WiMAX that I need to mention is WiMAX QoS feature. Cellular traffic is a mix of voice and data. The QoS defined in WiMAX is helpful to ensure the quality of voice and data transmission for cellular backhaul traffic.
Wireless service providers (WSPs) could use WiMAX equipments to build wireless backhaul traffic from base station in their access network. The access network may be based on WI-FI, WiMAX or any proprietary wireless access technology.59 The benefit of using WiMAX as access network is because WiMAX system is easy to deploy and cost-effective compared with high expense of DSL sort. Especially, it enables QoS which could prioritize and optimize the backhaul traffic.
In USA and Europe, the situation of backhaul operation is different. Internet backbone providers lease lines to third-party service providers in order to reduce the costs of wired backhaul. There are only 20% of cellular towers are backhauled wirelessly in USA. Along with the termination of lease agreement, which will probably be passed by FCC, the cellular service providers in USA would use 802.16d wireless backhaul as an economical and high efficiency alternative, such as WI-FI hotspots and point-to-point backhaul application In Europe, the local exchange operators rarely lease lines to third-party competitors.
Thus, service providers must find another way to offer economical solutions. The result is that there are around 80% cellular tower in Europe adopted wireless backhaul61. The existing wired and wireless backhaul services have already hold a huge number of subscriber groups. This fact somewhat limits the needs and exploitation of WiMAX backhaul solution. But there also exist lots of opportunities, in respect that it could still play a role as an overlay network which enables mobile operators to extend backhaul capacity to support wide range of new mobile services without bring the risk to the operation of existing services. The advantages of using WiMAX as cellular backhaul are:
Low cost solution than traditional wired line backhaul Widely coverage spread and high rate of data transmission Serve multiple cell sites High-capacity to expand for future new mobile service QoS feature help optimize the backhaul traffic Actually, since both are designed to transmit data through IP network, WiMAX could be easily deployed for Wi-Fi hotspots backhaul solution. The base station which connects to Internet/MAN could transmit data by air to terminal station CPE through WiMAX wireless link. Then transmit through CPE to Wi-Fi hotspot, in order to accomplish the last 100 meters coverage
Some features of Wimax implementation in Agni System Ltd. Frequency range in Mz: The rang that used are 3400 to 3600 MHz Among this ranges they use 3422.75MHz,3426.25MHz,Connectivity : In Agni Systems among different NOC(network operation center)it uses Backhaul for connection .
Non Line of Sight(Nos): In Agni Systems Nos or near line of sight is used . Equipments supplied: All the equipments are supplied by Motorola. Here Motorola CANOPY
8.1P_DES  software is used.
Agni Systems faces the following problems in implementation of Wimax Alignment problem between the base station. Frequent power outage or voltage up-down disrupts the connection. Low throughput also a problem for WiMAX. Huge amount of data transmission beyond the capacity of the receiver can hang the system. 
The wireless communications industry is gaining momentum in both fixed and mobile applications. The continued increase in demand for all types of wireless services (voice, data, and multimedia) is fueling the need for higher capacity and data rates not only in fixed but also in mobile applications. WLANs and 3G cellular networks are experiencing several difficulties for reaching a complete mobile broadband access, bounded by factors such as bandwidth, coverage area, or infrastructure costs. In this context, WiMAX appears to fulfil these requirements, providing vehicular mobility and high service areas and data rates. Defined to provide broadband wireless access, it  is increasingly gaining interest as an alternative last mile technology to DSL lines and cable modems, and a complementary technology where wireless networks are not sufficiently developed. This thesis is devoted to the study of the WiMAX system. More specifically, it examines the implementation of a WiMAX simulator, targeted to the 256-point FFT OFDM PHY layer, built with Matlab Simulink. With this purpose, the different parts of then simulator have been analyzed.
The flexible and parametrizable OFDM transmitter was explained in Chapter 2. Specifically, the length of the cyclic prefix, the coding scheme, the modulation alphabet, the channel bandwidth, and the frame duration, can be freely chosen by setting appropriate parameter values. Chapter 3 has focused on the channel implementation. Changes in the environment due to the movement of not only objects but also receiver and transmitter introduce time-varying fading on the communication channel.
The multipath channel propagation manifests itself by different echoes of possibly different transmitted symbols overlapping at the receiver, which leads to error rate degradation. The effects of ISI on the transmission error mstatistics are negligible as long as the delay spread is shorter than the cyclic prefix. The simulator implements three different kinds of channels, block fading, time-variant, and time-variant block fading channels. If the block fading channel is selected for simulation, one impulse response is generated randomly for every frame transmitted. The time-variant channel model is implemented as a Jake’s model and a time-variant convolution of the transmit signal with the impulse response. The time-variant block fading channel is a combination of the block fading and the time-variant channel model with time-invariant channel filtering. This model can be used as a low complexity approximation for the time-variant channel model if only slow speeds are considered. The receiver was studied in detail in Chapter 4. Particularly, demapping algorithms and channel estimation methods were discussed. On one hand, it was shown that soft demapping outperforms hard demapping by 2 dB of gain in SNR. The information given by the demapper can contain not only the demodulated message (hard output) but also the degree of confidence in the decision (soft output). Performing the exact calculation of the bitwise metric in a soft demapper with a MAP algorithm is very tedious work. In order to reduce the complexity of the MAP algorithm for LLR calculation I replaced the mathematical logarithm function of the LLR expression with simple max or min functions, leading to the max-log-MAP approximation. On the other hand, the system BER with channel estimates from training sequences was
evaluated. Results showed that simple least-squares channel estimation costs 1 dB in SNR when compared with a perfect channel knowledge. Therefore,since soft demapping gives a higher gain in the channel SNR, more efforts should be spent on implementing a soft demapper than a better channel estimation.  SUI channel models are an extension of the earlier work by AT&T Wireless and Erceg et al. In this model a set of six channels was selected to address three different terrain types that are typical of the continental US. This model can be used for simulations, design, development and testing of technologies suitable for fixed broadband wireless applications
Chapter five is of performance analysis of WiMAX using simulink. It also shows physical layer performance and scattered plot. It describes BER of different types of modulation in WiMAX. This chapter displays results of simulink The main objective of thesis is to focus on performance analysis of WiMax and to implement and simulate the IEEE 802.16 OFDM physical layer using Mat lab in order to have better understanding of the standard and the system performance.  This involves studying,  through  simulation,  the  various  PHY modulation,  coding  schemes  and  interleaving  in  the  form  of  bit-error-rate  (BER)  and effects of FEC  on the transmission side. The Stanford University Interim (SUI) channel models are selected for the wireless channel in the simulation. The evaluation was done in simulation developed in MATLAB. The influence of these parts on the system performance is shown and analyzed great detail in Simulink also.  Finally the market evaluation of WiMax around the world and its prospects in Bangladesh under the basis of the work of technical advancement, present status, its possible implementation are also focused.
Future Work:
The implemented PHY layer model still needs some improvement. The channel estimator can be implemented to obtain a depiction of the channel state to combat the effects of the channel using an equalizer.
The IEEE 802.16 standard comes with many optional PHY layer features, which can be implemented to further improve the performance. The optional Block Turbo Coding (BTC) can be implemented to enhance the performance of FEC. Space Time Block Code
(STBC) can be employed in DL to provide transmit diversity. The ability to transmit and receive through multiple antennas enables us, while applying spatial diversity, to combat fading and ultimately have substantially improved reliability and increased capacity. The increased capacity, under proper coding, eventually translates into increased throughput. Specifically, the concepts of maximum ratio combining (MRC) and space-time coding (STC) can be introduced. It is necessary for simple decoding of STC systems that the channel must be slowly varying (remain constant over two consecutive time steps). The simulator implements MIMO up to two transmit and/or receive antennas. Simulated results showed that the degree of diversity achieved, and hence the increase in throughput, is proportional to the number of antennas with which the communication system is equipped. Furthermore, it was found that a gain of 3 dB in the channel SNR appears in the BER curves when two antennas are used at the receiver instead of at the transmitter.
3G                   Third Generations
3GP                 Third Generation Partnership Project
4G             Fourth Generation
AAS           Adaptive Antenna System
AMC          Adaptive Modulation and Coding
AP             Access Point
ARQ          Automatic Retransmission Request
AWGN       Additive White Gaussian Noise
BER           Bit Error Rate
BS              Base Station
BTC            Block Turbo Coding
CC              Convolutional Coding
CIR             Channel Impulse Response
CP              Cyclic Prefix
CSI             Channel State Information
CTC            Convolutional Turbo Coding
DC               Direct Current
DFS             Dynamic Frequency Selection
DL                DownLink
DSL              Digital Subscriber Line
FCH             Frame Control Header
FDD             Frequency Division Duplexing
FDM             Frequency Division Multiplexing
FEC             Forward Error Correction
FFT              Fast Fourier Transform
GF                Galois Field
HSDPA         High Speed Downlink Packet Access
ICI                Inter-Carrier Interference
i.i.d.              Independent Identically Distributed
IEEE             Institute of Electrical and Electronics Engineers
IFFT             Inverse Fast Fourier Transform
I-METRA      Intelligent Multi-Element Transmit and Receive Antennas
IMT               International Mobile Telecommunications
IP                  Internet Protocol
IQ                  In-phase Quadrature-phase
ISI                 Inter-Symbol Interference
LGPL            Lesser General Public License
LLR               Log-Likelihood Ratio
LoS               Line of Sight
LS                 Least Squares
LSE               Least Squares Estimation
MAC              Medium Access Control
MAN              Metropolitan Area NetworkMAP            
MEA              Multi-Element Antenna
MIMO            Multiple-Input Multiple-Output
MISO             Multiple-Input Simple-Output
MRC              Maximum Ratio Combining
MS                 Mobile Station
MSS               Mobile Subscriber Station
NLoS             Non Line of Sight
OFDM            Orthogonal Frequency Division Multiplexing
OFDMA          Orthogonal Frequency Division Multiple Access
PAM               Pulse Amplitude Modulation
PDA               Personal Digital Assistant
pdf                  Probability Density Function
PDP               Power Delay Profile
PRBS             Pseudo-Random Binary Sequence
QAM              Quadrature Amplitude Modulation
QoS               Quality of Service
RRC               Root-Raised Cosine
RF                  Radio Frequency
RMS               Root Mean Square
RS                  Reed-Solomon
SC                  Single Carrier
SIMO              Single-Input Multiple-Output
SINR               Signal-to-Interference-plus-Noise Ratio
SISO               Single-Input Single-Output
SNR                 Signal-to-Noise Ratio
SOHO             Small-Office Home-Office
SS                    Spread Spectrum
SS                    Subscriber Station
STBC               Space-Time Block Coding
STC                  Space-Time Coding
TDD                  Time Division Duplexing
TDM                 Time Division Multiplexing
TDMA               Time Division Multiple Access
UL                     UpLink
UMTS               Universal Mobile Telecommunications System
VoIP                  Voice over IP
WCDMA            Wide-band Code Division Multiple Access
Wi-Fi                 Wireless-Fidelity
WiMAX              Worldwide Interoperability for Microwave Access
WLAN                Wireless Local Area Network
WMAN               Wireless Metropolitan Area Networ
E.2 List of symbols
a                       Binary inversion of the sequence a
As                     Vector that represents the points in the constellation map
bk                      Bit on position k
Bcoh                  Coherence bandwidth
Bd                      Doppler spread
BER0                  Target BER
BW                     Nominal channel bandwidth
c                         Speed of light
ci(t)                     Tap coefficients
C                        Amplitude of the fading component
Cm                     Normalization factor in the modulation map
C                        Set of complex numbers
dE                       Euclidean distance
E{}                       Mathematical expectation
Eb/                      N0 Bit energy to noise rate
Fc                        Carrier frequency
fd                        Doppler frequency
fM                        Maximum Doppler shift
fN                         Nyquist frequency
f Ray(a)                Rayleigh fading distribution
fRice(a)               Rice fading distribution
fsam                    Sampling frequency of the channel simulator
Fs                       Sampling frequency of the OFDM symbol
G                         Ratio of the CP time to the useful symbol time
G                         Channel gain matrix
h                          Vector of channel coefficients
h(t)                       Channel impulse response
h(t, _ )                  Channel time-varying impulse response
hb(t, _ )                Baseband equivalent impulse response of the channel
H                          Channel matrix
Hrc(f)                    Raised cosine filter frequency response
Hrrc(f)                   Root-raised cosine filter frequency response
HR(f)                     Frequency response of the receive filter
HT(f)                     Frequency response of the transmit filter
H_                         Virtual channel matrix
k                            Number of uncoded bits that enter the RS encoder
K                           Rice distribution factor
NT                         Number of transmit antennas
Ma                       Number of transmitted bits per symbol (modulation alphabet)
en                        Modified noise vector
nf                         Sampling factor, used in the definition of the OFDM symbol
NR                       Number of receive antennas
Nc                        Number of subbands the OFDM signal is divided in
Ncolumns            Number of columns in the interleaving matrix
Ncpc                    Number of transmitted bits per symbol
Ndata                   Number of used data subcarriers
NFFT                   Number of points used when performing the FFT algorithm
NOFDM               Number of transmitted OFDM symbols in one frame
Npath                  Number of paths of the time-variant channel model
Nrows                  Number of rows in the interleaving matrix
NRS                    Number of blocks used in the RS encoder
Ntcb                     Total number of coded bits
Ntrain                  Number of training symbols per frame
Ntx-data               Number of transmitted data symbols
Ntx-sym               Total number of transmitted OFDM symbols
NTsym                 Total number of transmitted symbols in one frame
Nused                  Number of used non-zero subcarriers
NC(0, 1)               Set of complex numbers, with zero mean and unit variance
ps                         Vector containing the pilot subcarriers
p(y|s)                    Conditional probability, probability of y given s
Pb                         Probability of bit error
Pbc                       Probability of bit error per carrier
PALL                    Frequency domain sequence from which are derived all full bandwidth preambles
PEVEN                 Frequency domain sequence for long training symbols constructed
                              with even subcarriers of PALL
PODD                   Frequency domain sequence for long training symbols constructed
                              with odd subcarriers of PALL
PSHORT               Frequency domain sequence for short training symbols
Q(x)                       Complementary Gaussian error function
r                             Vector of received symbols
R                           Overall rate
Re{}                       Operation to extract the real part
RMIMO                  Spatial correlation matrix of the MIMO channel
RR                         Transmit correlation matrix
Rsym                     Symbol rate
RT                         Receive correlation matrix
bs                       Transmit symbol estimates
Spacket                  Packet size, in bits, that is transmitted by the source
S                         Symbol block matrix
t                          Number of bytes a RS encoder can correct
Tb                       Useful symbol time
Tcoh                    Coherence time
Tg                       CP symbol time
Tframe                  Frame duration
Tm                       Multipath spread
Ts                        Sampling time of the OFDM symbol
Tsym                    OFDM symbol time
v                          Vehicle speed
wk                        Output of the PRBS generator
W                         Signal bandwidth
y                           Vector containing the received symbol
[1] S. Sampei: ”Applications of Digital Wireless Technologies to Global
Wireless Communications,” Prentice Hall, 1997.
[2] Intel White Paper, Wi-Fi and WiMAX Solutions: ”Understanding Wi-
Fi and WiMAX as Metro-Access Solutions,” Intel Corporation, 2004.
[3] J. Pino Lacosta: ”WiMAX: una alternativa d’accés a les xarxes,” Master
Thesis, Universitat Oberta de Catalunya, Enginyeria Informàtica, June
[4] LAN/MAN Standards Committee: ”802.16 IEEE Standard for Local and Metropolitan Area Networks. Part 16: Air Interface for Fixed Broadband Wireless Access Systems,” IEEE Standards, October 2004.
[5] C. Eklund, R. B. Marks, K. L. Stanwood, and S.Wang: ”IEEE Standard 802.16: A Technical Overview of the WirelessMAN Air Interface for Broadband Wireless Access,” IEEE Communications Magazine, pp. 98-107, June 2002.
[6] WiMAX Forum: ”Mobile WiMAX. Part I: A Technical Overview and
Performance Evaluation,” August 2006.
[7] T. Cooklev: ”Wireless Communication Standards. A Study of IEEE
802.11TM, 802.15TM, and 802.16TM,” Standards Information Networks
IEEE Press, 2004.
[8] P. Stavroulakis: ”Third generation mobile telecommunication systems:
UMTS and IMT-2000,” Springer, 2001.
[9] A. M. Michelson, and A. H. Levesque: ”Error Control Techniques for
Digital Communications,” Wiley-Interscience Publications, 1985.
 [10] S. B. Wicker: ”Error Control Systems for Digital Communication and
Storage,” School of Electrical and Computer Engineering, Georgia Institute
of Technology, Prentice Hall, 1995.
[11] E. P. Lawrey: ”Adaptive Techniques for Multiuser OFDM,” Ph. D. Thesis,
School of Engineering, James Cook Univeristy, December 2001.
[12] K. V. Ramasami: ”A Primer on Root Raised Cosine Filter Design,”
December 2004. rvc/documents/rcdes.pdf
[13] T. S. Rappaport: ”Wireless Communications: principles and practice,”
Prentice Hall, 1996.
[14] R. J. McEliece, and W. E. Stark: ”Channels with block interference,”
IEEE Transactions on Information Theory, vol. 46, no. 2, pp. 325-343,
March 2000.
[15] W. C. Jakes: ”Microwave Mobile Communications,” IEEE Press, 1994.
[16] L. Staphorst: ”Viterbi decoded linear block codes for narrowband and
wideband wireless communication over mobile fading channels,” Master
Thesis, Department of Electrical, Electronic and Computer Engineering,
University of Pretoria, July 2005.
[17] C. Mehlführer, F. Kaltenberger, M. Rupp, and G. Humer: ”A Scalable
Rapid Prototyping System for Real-Time MIMO OFDM Transmissions,”
Institute of Communications and RF Engineering, Vienna University
of Technology, and ARC Seibersdorf Research GmbH, Tech Gate
Vienna, Proceedings on the second IEE/EURASIP on DSP enabled Radio,
September 2005.
[18] Ki Seol Kim et al.: ”General Log-Likelihood Ratio Expression and
its Implementation Algorithm for Gray-Coded QAM Signals,” ETRI
Journal, vol. 28, no. 3, pp. 291-300, June 2006.
[19] ”The Matlab help: Communications Blockset,”