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A Physical Layer Simulation for WiMAX MIMO-OFDM System Throughput Comparison Between 2x2 STBC and 2x2 V-BLAST in Rayleigh Fading Channel

A Physical Layer Simulation for WiMAX

MIMO-OFDM System Throughput Comparison Between 2x2 STBC and 2x2 V-BLAST

in Rayleigh Fading Channel

Hadj Zerrouki*, Mohammed Feham STTC Laboratory ,

Department of Electronics and Electrical Engineering, Faculty of Technology, Tlemcen University, Algeria.

zerrouki. hadj@gmail. com*, feham _ m@yahoo. fr

Abstract- WiMAX is a broadband wireless technology based on IEEE802.16 standards family, which defines the physical (PHY)

and medium access control (MAC) layers and makes several

possible configurations available along with non-mandatory

options. WiMAX is a new OFDM based technology and promises

to combine high data rate services with wide area coverage. In

this paper, the performance of Wi MAX PHY layer is investigated

for two MIMO (Multiple-Input Multiple-Output) PHY layer

modifications, (Space-Time Block Codes, STBC) and (Spatial

multiplexing, SM) to provide high suppression against multipath

fading, provide high bandwidth efficiency and high throughput

with high data rates. This work incorporates the model building

of the WiMAX Physical layer using MA TLAB simulation. The

results obtained for these modifications show that these

mechanisms enhance the performance of the WiMAX PHY layer

in fixed environments with high spectral efficiency.

Keywords-component; WiMAX; IEEE 802.16; OFDM; MIMO; STBC; V-BLAST; SNR; Physical Layer (PHy);

I. INTRODUCTION

Worldwide Interoperability for Microwave Access (WiMAX) is introduced by the Institute of Electrical and Electronic Engineers (IEEE) which is standard designated 802.16 d-2004 [1 ] (used in fixed wireless applications) and 802.16 e-2005 [2] (mobile wireless) to provide a worldwide interoperability for microwave access. The IEEE 802. 16 d-2004 air interface standard is basically based on technology namely Orthogonal Frequency Division Multiplexing (OFDM), that has been regarded as an efficient way to combat the InterSymbol Interference (lSI) for its performance over frequency selective channels for the broadband wireless networks.

In an OFDM system, the data is divided into multiple parallel sub-streams at a reduced data rate, and each is modulated and transmitted on a separate orthogonal subcarrier. This increases symbol duration and improves system robustness. OFDM is achieved by providing multiplexing on users' data streams on both Uplink and Downlink transmissions. A valuable solution consists of the introduction

of advanced digital signal processing techniques based on Multiple Input Multiple Output (MIMO) concept.

The key feature of MIMO is the capability to increase channel capacity without increasing transmitted power and RF bandwidth [3 ]. Nowadays, MIMO techniques present some well-promising applications in wireless standards like IEEE 802.11 n and IEEE 802.16 x (WiMAX). Different space-time processing techniques have been proposed in literature in order to fully exploit potentialities of MIMO systems. The most popular one is Space-Time Coding [4], in which the time dimension is complemented with the spatial dimension inherent to the use of multiple spatially-distributed antennas

Commonly used Space Time coding schemes are SpaceTime-trellis codes and Space-Time Block Codes (STBC). A well-known example of conceptually simple, computationally efficient and mathematically elegant STBC scheme has been proposed by Alamouti in [5]. Substantially Alamouti's coding is an orthogonal space-time block code, where two successive symbols are encoded in an orthogonal 2x2 matrix. The columns of the matrix are transmitted in successive symbol periods, but the upper and the lower symbols in a given column are sent simultaneously through the first and the second transmit antenna respectively.

The alternative solution to space-time coding is represented by Spatial Multiplexing (SM) [6 ]. Spatial multiplexing is a space-time modulation technique whose core idea is to send independent data stream from each transmit antenna. This is motivated by the spatially white property of the distribution which achieves capacity in MIMO i. i. d. Rayleigh matrix channels [7 ]. SM is addressed to push up link capacity rather than to exploit spatial diversity . Although various implementtation architectures for MIMO systems have been introduced since the BLAST (Bell Laboratories Layered Space-Time) system was proposed in [6 ] and [8], a variation of such system, V-BLAST still emerges as a promising architecture due to lower receiver complexity (V-BLAST receiver algorithm) and higher data rates in the case of large number of antennas.

978-1-4799-3824-7/14/$31.00 2014 IEEE

The paper is organized as follows: Model of WiMAX PRY layer is explained in section 2. Explanation of the results obtained via simulation is done in Section 3 . At the end conclusion is given in section 4.

II. MODEL OF WIMAX PRY LAYER

Physical layer set up the connection between the communicating devices and is responsible for transmitting the bit sequence. It also defines the ty pe of modulation and demodulation as well as transmission power. WiMAX physical layer is based on the orthogonal frequency division multiplexing (OFDM). OFDM is a good choice of high speed data transmission, multimedia communication and digital video services. [t even can maintain very fast data rate in a non line of sight condition and multipath environment. [n the following subsection we provide a detailed description of the OFDM.

The role of the PRY -layer is to encode the binary digits that represent MAC frames into signals and to transmit and receive these signals across the communication media. The proposed block diagram of WiMAX-MIMO-OFDM PRY system is given in Fig. I.

, , : m' - ' < , m' '

,-'

' .

--------- ---------

MIMO En coder STB C / SM

..... _ ... -- - -------- .......

, ... ' : z ' "" s: : :3: ga:

Figure 1. Block diagram of WiMAX-MIMO-OFDM PHY system

The random binary signal information is first generated and grouped in symbols, then coded for error correction. Digital modulation system is used because different modulation scheme is needed for different data rates. Then multiple antennas are used, the M[MO space-time diversity encoder is implemented. After that guard band is inserted and the Inverse Fast Fourier Transform (IFFT) block transforms the data sequence into time domain. Then a cyclic prefix is used which is chosen larger than the expected delay spread to avoid intersymbol and inter-carrier interferences (lSI and ICI). The channel is considered to be a multipath fading channel followed by addition of white Gaussian noise.

At the receiver, the FFT is used to transform the data back to frequency domain. Adaptive filtering technique is used for channel estimation. The FFT is taken in each of receives antenna. Each antenna receives a different noisy superimposetion of the faded versions of the transmitted signals. Lastly, the binary information data is obtained back after the demodulation and channel decoding. In following sections, we will take each block one by one in detail.

A. Channel Encoding

The radio linle is a quickly vary ing linle, often suffering from great interference. Channel coding, whose main tasks are to prevent and to correct the transmission errors of wireless systems, must have a very good performance in order to maintain high data rates. The 802.16 channel coding chain is composed of three steps: Randomizer, Forward Error Correction (FEC) and [nterleaving. They are applied in this order at transmission.

1) Randomization: The Randomizer performs randomization of input data on each burst on each allocation to avoid long sequence of continuous ones and zeros. This is implemented with a Pseudo Random Binary Sequence (PRBS) generator which uses a 1 5 stage shift register with a generator polynomial of 1 + Xl4 + XiS with XOR gates in feedback configuration as shown in Fig. 2.

D Data O u t

D _"t_"_l n ____ ---I -------

Figure 2. Randomization generator.

Forward Error Correction (FEC) codes: The bits issued from the randomizer are then applied to the FEC encoder. FEC techniques ty pically use error-correcting codes that can detect with high probability the error location. These channel codes improve the bit error rate performance by adding redundant bits in the transmitted bit stream that are employed by the receiver to correct errors introduced by the channel.

The FEC is achieved using Convolutional Codes (correct independent bit errors) and Reed Solomon codes (correct burst errors at byte level) to provide the additional coding gain which measures the amount of additional SNR that would be required to provide the same BER performance for an uncoded message signal in the same channel conditions.

The Reed Solomon (RS) codes are mandatory codes on both sides i. e. Uplink and Downlink. These are non-binary cyclic codes that add redundancy to the data that improves the probability of block errors.

The outer RS encoded block is fed to inner binary convolutional encoder (see Fig. 3 ). The implemented encoder has native rate of 112, a constraint length of 7 (m = 7 ). The generator polynomials used to derive its two output code bits, denoted X and Y , are specified in the following expressions: G 1 = 1330cT for X and G2 = 17 10cT for Y .

X=1330CT

Figure 3. Convolutional encoder (rate = 112, m = 7).

Coding rate is defined as the ratio of the input bits to the output bits. Higher rates like 2/3 and 3/4, are derived from it by employing "puncturing. " Puncturing is a procedure that involves omitting of some of the encoded bits in the transmitter thus reducing the number of tr