AWGN Channel Performance Analysis of QO-STB Coded MIMO- OFDM System

AWGN Channel Performance Analysis of QO-STB Coded MIMO- OFDM System Pranil Mengane 1, Ajitsinh Jadhav 2 12 Department of Electronics & Telecommunication Engg, D.Y. Patil College of Engg & Tech, Kolhapur Abstract-The performance analysis ofquasi-orthogonal space time block coded MIMO-OFDM system is studied in this paper. The performance of MIMO-OFDM system is studied for AWGNchannel with different modulation schemes such as BPSK, QPSK, 8-QAM, 16-QAM, 32- QAM and 64-QAM. As a study, we have evaluated performance of MIMO-OFDM system for different combinations of Tx-Rx antennas such as 2x2, 4x4, 6x6 and 8x8. The parameters decided to analyse the system performance are BER, MSE and throughput. Keywords- MIMO, OFDM, QO-STBC, AWGN, MSE. I. INTRODUCTION The wireless technology is changing day by day with the ever increasing demand of data rate. So there is need to upgrade the technology which can fulfil the demand of high data rate. So to make up with this requirement, several approaches such as increasing modulation order or employing several antennas at both transmitter and receiver side. Multiple Input Multiple Output (MIMO) [1]. This paper is organised as follows. In Section II, background of such techniques is discussed. Here MIMO system, OFDM system and the Rayleigh Fading Channel are studied. In Section III, quasi-orthogonal 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). A. Multiple Input Multiple Output (MIMO) MIMO is nothing but a system where transmitter and receiver ends are accompanied with multiple antennas. The idea behind the MIMO system is that the signals on transmitter end and the receiver are combined in such a way that the quality (bit-error rate or BER) or the data rate (bits/sec), throughput of the communication for each MIMO user will be improved. This advantage can be used to increase the network s quality of service (Qos) and throughput [2]. The spirit of MIMO systems is space time signal processing in which time (the natural dimension of digitalcommunication 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 main future of MIMO is ability to use 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 @IJRTER-2016, All Rights Reserved 139

Fig. 1. MIMO Wireless Transmission System 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 frequencyselective.the use of multiple antennas allow MIMO systems to perform Precoding(multi-layer beamforming), Diversity coding (space-time coding), and Spatial Multiplexing. Beamforming is transmitting the same signal over all transmit antennas such with different gain and phases (called weights) such that the receiver signal is maximized. Diversity is a technique where a single spacetime coded stream is transmitted through all antennas. Spatial multiplexing increases network capacity by dividing a high rate signal into multiple lower rate streams and transmitting them through the different antennas [5]. Beamforming: Beamforming is nothing but a technique where a pair of transmitting and receiving antenna directstheir main beams at each other. This increases the receiver s received power and thus improves the SNR. Spatial Diversity: A signal can be coded through the transmit antennas, creating redundancy (Transmitting same signal, at same time through multiple antennas), which reduces the outage probability. Spatial Multiplexing: A set of streams can be transmitted in parallel, each using a different transmit antenna element. The receiver can then perform the appropriate signal processing to separate the signals [5]. Now consider use of diversity at both transmitter and receiver giving rise to MIMO system. For M transmitting antennas and N receiving antennas, capacity equation can be expressed as, [5]. C I HH b/s/hz (1) * EP log 2[det( N M )] where (*) denotes transpose conjugate, H is NM channel matrix, ρ is SNR of Rx antenna and suffix EP stands for equal power. The MIMO signal model is described as: r Hs n (2) Where r received vector of size N 1, H is a channel matrix of size N M, s is the transmitted vector of size M 1, and n is noise vector of size N 1. B. Orthogonal Frequency Division Multiplexing (OFDM) OFDM is becoming a very popular multi-carrier modulation technique for transmission of signals over wireless channels. It converts a frequency-selective fadingchannel into a collection of parallel @IJRTER-2016, All Rights Reserved 140

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-data-rate subcarriers, OFDM systems can provide a composite high-data-rate with a 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. 2. Spectra of Individual Sub-carriers in OFDM 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. C. Channel Air or space is used as a transmission medium in wireless communication. The signal is directly received from transmitting antenna as well as the received signal is combination of reflected, diffracted, and scattered copies of the transmitted signal. When the signal hits a surface where fractional energy is reflected and the remaining is transmitted into the surface, it is said to be as Reflection. Reflection coefficient determines the ratio of reflection and transmission depends on the material properties. When the signal is obstructed by a sharp object which derives secondary waves it is called as Diffraction. Scattering occurs when the signal impacts upon rough surfaces, or small objects. Sometimes received signal isstronger than the reflected and diffracted signal since scattering spreads out the energy in all directions and therefore provides additional energy for the receiver which can receive more than one copies of the signal in multiple paths with different phases and powers. Reflection, diffraction and scattering in combination give rise to multipath fading. Additive White Gaussian Noise Channel Additive white Gaussian noise (AWGN) channel is a universal channel model for analysing modulation schemes. In this model, the channel does add a white Gaussian noise to the signal @IJRTER-2016, All Rights Reserved 141

passing through it. This suggests that the channel s amplitude frequency response is flat (thus with unlimited or infinite bandwidth) and phase frequency response is linear for all frequencies so that modulated signals pass through it without any amplitude loss and phase distortion of frequency components. Fading does not exist. The only distortion is introduced by the AWGN. AWGN channel is a theoretic channel used for analysis purpose only.the received signal is simplified to: r( t) s( t) n( t) (3) Where n(t) is additive white Gaussian Noise.[8] 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. Also it was proposed codes with 3/4 of the full transmission rate for the specific cases of three and four transmit antennas. 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, at the decoder, cannot separate all transmitted symbols from each other. Instead, in our proposed structure, 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 x2 A12 * * (6) x2 x1 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] x1 x2 x3 x4 * * * * A12 A34 x2 x1 x4 x3 A * * (7) * * * * A34 A12 x3 x4 x1 x 2 * * x4 x3 x2 x1 Here a diversity of 2M is achieved while the rate of the code is one. The proposed matrix for N=M=8 antenna configurations is given as: s1 s2 s3 s4 s5 s6 s7 s 8 * * * * * * * * s2 s1 s4 s3 s6 s5 s8 s7 * * * * * * * * s3 s4 s1 s2 s7 s8 s5 s 6 s4 s3 s2 s1 s8 s7 s6 s5 (8) * * * * * * * * s5 s6 s7 s8 s1 s2 s3 s 4 s6 s5 s8 s7 s2 s1 s4 s3 s7 s8 s5 s6 s3 s4 s1 s 2 * * * * * * * * s8 s7 s 6 s5 s 4 s 3 s2 s 1 IV. SIMULATION RESULTS The system discussed above has been designed and results are shown in the form of SNR vs. BER plot for different modulations. Also MSE vs. SNR and Throughput of the MIMO-OFDM system is studied.the results below are analysed with AWGN channel with 2x2, 4x4, 6x6 and 8x8 antenna configurations. The same results are taken for above mentioned antenna configurations @IJRTER-2016, All Rights Reserved 142

considering the AWGN channel and different modulation techniques like BPSK, QPSK, QAM-8, QAM-16 and QAM-32, QAM-64. The results are arranged in three parts viz BER vs SNR, MSE and Throughput. A. BER vs SNR: Fig. 3. BER vs. SNR performance of system with BPSK for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 4. BER vs. SNR performance of system with QPSK for 2x2, 4x4, 6x6 and 8x8 antenna configuration @IJRTER-2016, All Rights Reserved 143

Fig. 5 BER vs. SNR performance of system with 8-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 6. BER vs. SNR performance of system with 16-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 7. BER vs. SNR performance of system with 32-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration @IJRTER-2016, All Rights Reserved 144

Fig. 8. BER vs. SNR performance of system with 64-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration B. Mean Square Error (MSE): Fig. 9. MSE performance of system with BPSK for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 10. MSE performance of system with QPSK for 2x2, 4x4, 6x6 and 8x8 antenna configuration @IJRTER-2016, All Rights Reserved 145

Fig.11. MSE performance of system with8-qam for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 12. MSE performance of system with 16-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 13. MSE performance of system with 32-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration @IJRTER-2016, All Rights Reserved 146

Fig. 14. MSE performance of system with 64-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration C. Throughput: Fig. 15. Throughput performance of system with BPSK for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 16. Throughput performance of system with QPSK for 2x2, 4x4, 6x6 and 8x8 antenna configuration @IJRTER-2016, All Rights Reserved 147

Fig. 17. Throughput performance of system with 8-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 18. Throughput performance of system with 16-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration Fig. 19. Throughput performance of system with 32QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration @IJRTER-2016, All Rights Reserved 148

Fig. 20. Throughput performance of system with 64-QAM for 2x2, 4x4, 6x6 and 8x8 antenna configuration V. CONCLUSIONS In this paper, MIMO-OFDM system using QO-STB coding technique in AWGN channel is studied for performance for different modulation schemes. From the results, it can be concluded that 4x4 system gives us better output in terms of BER, MSE and throughput as well as compared to other antenna configurations. Also for 4x4 antenna configuration, the proposed system gives better performance for 16-QAM and 32-QAM modulation. The possible reason may be that as we go for higher order antenna configuration scheme, as no. of symbols are increased there are chances that no. of errors introduced in the system may also increases. 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 2002. 3. Luis Miguel Cortes-Pena, MIMO Space-Time Block Coding (STBC): Simulations and Results, Design Project: Personal And Mobile Communications, Georgia Tech (Ece6604), Pp. 1-8, April 2009 4. L. Kansal, A. Kansal and K. Singh Performance Analysis of MIMO-OFDM System Using QOSTBC Code Structure for M-QAM, Canadian Journal on Signal Processing Vol. 2, No. 2, pp. 2-15, May 2011. 5. S. Alamouti, A simple transmit diversity technique for wireless communications, IEEE Journal on Selected Areas Comm., vol.16,no. 8, pp. 1451 1458, October 1998. 6. V. Tarokh, H. Jafarkhani, and A. R. Calderbank, Space-time block codes from orthogonal designs, IEEE Transactions on Information Theory, vol. 45, pp. 1456 1467, July 1999. 7. H. Jafarkhani, A quasi-orthogonal space time block code, IEEE Transaction on Communication., vol. 49, no. 1,pp. 1 4, January 2001.V. Tarokh, N. Seshadri, and A.R. Calderbank, Space-Time Codes for High Data Rate Wireless Communications: Performance Criterion and Code Construction, IEEE Transactions on Information Theory, vol. 44, no. 2, pp. 744-765, March 1998. 8. J. J. V. de Beek, O. Edfors, M. Sandell, S.K. Wilson and P. O. Borjesson, On channel estimation in OFDM systems, In proceedings of 45th IEEE Vehicular Technology Conference,Vol. 2, Issue 7, pp 815-819, (Chicago, IL)1995. 9. R. Saltzburg, Performance of an efficient parallel data transmission systems, IEEE Trans. on Comm. Tech., pp. 805-811, Dec. 1967. @IJRTER-2016, All Rights Reserved 149