Performance Study of MIMO-OFDM System in Rayleigh Fading Channel with QO-STB Coding Technique

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1 e-issn Volume 2 Issue 6, June 2016 pp Scientific Journal Impact Factor : Performance Study of MIMO-OFDM System in Rayleigh Fading Channel with QO-STB Coding Technique Pranil S. Mengane1, Ajitsinh N. Jadhav2 1,2 Department of Electronics & Telecommunication Engg, D. Y. Patil College of Engg & Tech., Kolhapur, Abstract In 4G of wireless communication to increase data speed several techniques are use. Among these OFDM and MIMO are prominent. In this paper, performance study of combined OFDM and MIMO system which is quasi orthogonal space time block coded in Rayleigh fading channel is done. The parameters considered for evaluation are BER, MSE and throughput. For this study, the system is modulated using digital modulation techniques like BPSK, QPSK, 8-QAM, 16QAM, 32-QAM and 64-QAM. Keywords OFDM, QO-STBC, MIMO, NLoS, BER, MSE, Throughput. I. INTRODUCTION Wireless communication systems have become a vital part of our lives, especially during the last decade. The evolution of Mobile Wireless communication started long back in 1994 as 1G. As system evolved, we also witnessed 2G, 3G, and 4G wireless communication standards as well. 2G, 3G stands for second generation, third generation wireless communication systems, and 4 G similarly, stands for 4th generation wireless communication systems. So this report is about the system used for 4G communication wireless system; that is 4th generation wireless communication system. To get a better idea of what 2G, 3G and 4G systems are, let us start with a brief description of the 2nd generation systems, so that we can understand, the nature of it. Then we can proceed on to study more about, 3rd generation wireless systems & upcoming 4th generation wireless systems [1]. This paper is organized as follows. In Section II, background of such techniques is discussed. Here OFDM system, MIMO system and the Rayleigh Fading Channel are studied. In Section III, quasiorthogonal space time block code technique is discussed. Finally in Section IV, the simulated results based on system have been shown in the plots of BER vs. SNR for QPSK and M-QAM modulation. Section V concludes this paper. II. BACKGROUND Before moving further, let s revise the concepts of Multiple Input Multiple Output (MIMO), Orthogonal Frequency Division Multiplexing (OFDM). 2.1 Orthogonal Frequency Division Multiplexing (OFDM) It is a digital multi-carrier modulation scheme where large number of closely spaced orthogonal sub-carriers is used. Each subcarrier is modulated with a modulation scheme at a low symbol rate where data rates remains similar to conventional single carrier modulation schemes in the same bandwidth. OFDM signals are generated using the Fast Fourier transform algorithm. Due to its features, for transmission of signals over wireless channels it is becoming a very popular multicarrier modulation technique. It converts a frequency-selective fading channel into a collection of parallel flat fading sub-channels, which greatly simplifies the structure of the receiver. The time domain waveform of the subcarriers are orthogonal yet the signal spectral corresponding to different subcarriers overlap in frequency domain. Hence, the available bandwidth is utilized very efficiently in OFDM systems without causing the ICI (inter-carrier interference). By combining multiple low 190

2 data-rate subcarriers, OFDM systems can provide a composite high-data-rate with long symbol duration. That helps to eliminate the ISI (inter-symbol interference), which often occurs along with signals of a short symbol duration in a multipath channel [9]. Fig. 1. Spectra of Individual Sub-carriers in OFDM H Tx Rx Fig. 2 Block Diagram of MIMO System One of the main advantages of OFDM is its effectiveness against the multi-path delay spread, frequently encountered in Mobile communication channels. Also OFDM is very effective over channel distortion. OFDM also exhibit some advantages like low receiver complexity, high spectral efficiency, robustness against inter symbol interference (ISI), ease of implementation using Fast Fourier Transform (FFT) and simple equalization techniques. Like MIMO, OFDM also shows few disadvantages. One of the most serious problems with OFDM transmission is that, it exhibits a high peak-to-average ratio (PAPR). OFDM is sensitive to frequency offsets, timing errors and phase noise. 2.2 Multiple Input Multiple Output (MIMO) MIMO Communication systems are the latest advances in the wireless communication system. Such systems can provide higher data rate and better performance without any cost on the radio spectrum side. Figure 3 shows a typical block diagram for a MIMI communication system. In this model multiple copies of symbols are transmitted by transmitter through an antenna array and are received by multiple antennas at receiver side. This transmission scheme makes use of rich scattering environment (fading paths) over wireless medium (channel). We can think about channel matrix of the MIMO system as a N-SISO sub-channels where N is the min (Nt, Nr), where Nt is the number of transmitter antennas and Nr is the number of receiver antennas. The spectral efficiency formula for such model is given in Equation (1) for no CSI at transmitter side. So power is divided equally among all channels. N 2) CMIMO log 2 (1 P k Nt k 1 bps/hz (1) MIMO systems can be defined simply, given an arbitrary wireless communication system, consider a link where there are multiple antenna elements for transmitting end as well as the receiving end. 191

3 The idea behind the MIMO is that the signals on the transmit antennas at one end and the receiver antennas at the other end are combined in such a way that the quality BER or the data rate (bits/sec) of the communication for each MIMO user will be improved. This can be used to increase the network s quality of service [2]. The heart of MIMO systems is space time signal processing in which time (the natural dimension of digital communication data) is complemented with spatial dimension which is inbuilt in the use of multiple spatially distributed antennas. Thus it can be said that MIMO system is an extension of popular smart antennas. The key future of MIMO is ability to exploit multipath propagation for the benefit of user. The major advantages of MIMO system are high data rate transmission, robust communication, making use of variety of signal paths, higher spectral efficiency, reduction in bit error rate thereby increase in SNR. However, there are several limitations to MIMO system. Such as how to obtain perfect channel state information (CSI) accurately and promptly, system complexity increases with the increase in order of MIMO system, multipath character of the environment causes the MIMO channel to be frequency-selective. 2.3 Rayleigh Fading Channel Constructive and destructive nature of multipath components in flat fading channels can be approximated by Rayleigh distribution if there is no line of sight (NLOS) which means when there is no direct path between transmitter and receiver. The received signal can be simplified to: (3) r (t ) [s(t ) h(t )] n(t ) where h(t) is the random channel matrix having Rayleigh distribution and n(t) is the additive white Gaussian noise. The Rayleigh distribution is basically the magnitude of the sum of two equal independent orthogonal Gaussian random variables and the probability density function (pdf) given by: r2 r 2 p ( r ) e 2 2 (4) 0 r where 2 is the time-average power of the received signal [7]. III. QUASI ORTHOGONAL SPACE TIME BLOCK CODE It is proved in [6] that a complex orthogonal design and the corresponding space time block code which provides full diversity and full transmission rate is impossible for more than two antennas. So authors of [6] proposed space time block codes which achieve half of the full transmission rate for any number of transmission antennas. Therefore a code with 3/4 of the full transmission rate for the specific cases of three and four transmit antennas was proposed. So in [7], author proposed a different strategy for designing of space time block codes. So author designed rate 1 codes that provide half of the maximum possible diversity. The decoder of the new codes processes pairs of transmitted symbols instead of single symbols. Author proposed structures that are not orthogonal designs and, therefore, cannot separate all transmitted symbols from each other at decoder. Instead, in proposed coding technique, the transmission matrix columns are divided into groups. While the columns within each group are not orthogonal to each other, different groups are orthogonal to each other. Such a structure is called as quasi-orthogonal design. An example of a full-rate full-diversity complex space time block code is Alamouti scheme [5], which is defined by the following transmission matrix: x1 A12 x 2 x2 x1 (5) Here the subscript 12 is used to represent the indeterminate x1 and x2 in transmission matrix. Now, let us consider the following space time block code for N=M=4: [7] 192

4 A12 A 34 A x1 x2 x3 A34 x2 x1 x4 A12 x3 x4 x1 x4 x3 x2 x4 x3 x2 (6) x1 Here a diversity of 2M is achieved while the rate of the code is one. The proposed matrix for N=M=8 antenna s is given as: s2 s s 1 2 s s 4 3 s s3 4 s5 s6 s6 s5 s8 s7 s8 s7 s3 s4 s4 s3 s2 s5 s6 s7 s6 s5 s8 s7 s8 s5 s2 s7 s8 s8 s7 s2 s6 s3 s8 s7 s2 s4 s5 s6 s6 s5 s3 s4 s4 s3 s2 s8 s7 s6 s5 s4 s3 s2 (7) IV. SIMULATION RESULTS The system discussed above has been designed, simulated using MATLAB and results are shown in the form of SNR vs. BER, MSE and Throughput. For simulation of the system along with OFDM different antenna s such as 2x2, 4x4, 6x6 and 8x8 are considered for different digital modulation techniques like BPSK, QPSK, QAM-8, QAM-16, QAM-32 andqam-64. A quasi-orthogonal space time block coding technique is used for MIMO. For the simulation of system the medium considered is Rayleigh channel. 4.1 BER vs SNR: Fig. 3. BER vs. SNR performance of system with BPSK for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 4. BER vs. SNR performance of system with QPSK for 2x2, 4x4, 6x6 and 8x8 antenna 193

5 Fig. 5 BER vs. SNR performance of system with 8QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 8. BER vs. SNR performance of system with 64QAM for 2x2, 4x4, 6x6 and 8x8 antenna 4.2 Mean Square Error (MSE): Fig. 6. BER vs. SNR performance of system with 16QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 7. BER vs. SNR performance of system with 32QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 9. MSE performance of system with BPSK for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 10. MSE performance of system with QPSK for 2x2, 4x4, 6x6 and 8x8 antenna 194

6 Fig.11. MSE performance of system with8-qam for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 14. MSE performance of system with 64-QAM for 2x2, 4x4, 6x6 and 8x8 antenna A. Throughput: Fig. 12. MSE performance of system with 16-QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 13. MSE performance of system with 32-QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 15. Throughput performance of system with BPSK for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 16. Throughput performance of system with QPSK for 2x2, 4x4, 6x6 and 8x8 antenna 195

7 Fig. 17. Throughput performance of system with 8QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 18. Throughput performance of system with 16QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 19. Throughput performance of system with 32QAM for 2x2, 4x4, 6x6 and 8x8 antenna Fig. 20. Throughput performance of system with 64QAM for 2x2, 4x4, 6x6 and 8x8 antenna V. CONCLUSIONS From the results obtained it can be concluded that combined MIMO-OFDM system provides much better results as compared with alone MIMO or OFDM system. Also it is observed that BER, MSE and throughput performance of system is improved for higher antenna s. It can be also noted that, as compared to lower order modulation schemes, higher order modulation schemes provides better results for all parameters considered for simulation. REFERENCES [1] D. Gesbert, M. Shafi, D. Shiu, P. J. Smith and A. Naguib From Theory to Practice: an Overview of MIMO Space Time Coded Wireless Systems, IEEE Journal on Selected Areas in Communications, Vol.21, No.3, April 03. [2] S. Catreux, P.F. Driessen, and L. J. Greenstein, Data Throughputs Using Multiple Input Multiple Output (MIMO) Techniques in a Noise Limited Cellular Environment, IEEE Transactions On Wireless Communications, Vol. 1, No. 2, April

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