# PERFORMANCE ANALYSIS OF MIMO WIRELESS SYSTEM WITH ARRAY ANTENNA

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3 3. ARRAY ANTENNA Antenna array on a single structure can achieve better performance than the use of multiple antennas. Since the electromagnetic signal received by each antenna array element differs from the signals received by other array elements in terms of amplitude and phase, they must be combined coherently to achieve the desired output. Though it is more complex to set up an antenna array compared to a single antenna, weighting the signals before combining them enables enhanced performance features. In linear antenna array, all the antenna elements are rearranged in a single line with equal spacing between them. The array factor for N number of elements were considered and assumed that the elements of an array are spaced linearly and separated by λ/2 λ is the wave length [11-12]. The basic linear array structure for N number of elements is shown in the Figure-2. between the elements. This improves the performance greatly to achieve the maximum reduction in side lobe level and provide the maximum directivity towards the direction. This technique proved its effectiveness in improving the performance. The computation of the ideal beam pattern is performed on MATLAB using the beam pattern equation. All beam pattern plots shown in this chapter have been normalize with reference to the beam pattern s maximum value. Figure-2. Basic linear antenna array. 4. RESULT AND DISCUSSIONS Radiation pattern of antenna array is most important problem in communication applications. In many communication applications, it is required to design a highly directional antenna. Array antennas have high gain and directivity compared to an individual radiating element. Antenna array is formed by assembling of radiating elements in an electrical or geometrical configuration that can be compact as compared to multiple antennas. In this work, the linear array antenna has been verified. In case of linear antenna array, all the antenna elements a rearranged in a single line with equal spacing between them. According to the antenna array synthesis and design it is often desired to achieve the minimum side lobe level apart from the narrow beam and efficiency. In Antenna Theory, the radiation pattern response is constructed based on a realization of an analytical or desired model by an antenna model. It has been implemented on various Array configurations (with 4, 8, and 16 elements) and their response as the radiation pattern as shown in Figure-3. The radiation patterns have been observed for different phase shift in excitation Figure-3. Radiation pattern of linear antenna arrays with 4, 8, and 16 elements respectively. Figure-4 shows the performance capacity in the wireless channel. The result is measured according to the various SNR values. The capacity of the MIMO channel has been simulated for number of transmitter and receiver 808

4 antennas, such as 2 x 2, 3 x 3, 4 x 4, and 8 x 8 MIMO systems. It is observed that capacity gradually increases with the number of antennas. The proposed analysis allows evaluation of the capacity and the outage capacity for MIMO systems. The system capacity with respect to the outage probability has been shown in Figure-5. It is noticed that low probability means low capacity. We can increase the number of antennas to increase capacity for a given outage probability. As BER is one of the performance parameters, it has been verified with various modulation techniques such as BPSK, QPSK, and QAM. BER performance for QPSK has been shown in Figure-6, i.e., BER versus SNR, with different number of transmitting and receiving antennas (2 x 2, 3 x 3, 4 x 4, and 8 x 8). We find that antenna array pattern is a promising approach for improving the robustness at a reasonable complexity and feasibility. Radiation pattern of antenna array is most important problem in communication applications. Capacity x 2 3 x 3 4 x 4 8 x 8 Capacity of different Tx and Rx antennas SNR Figure-4. Performance of capacity with respect to SNR. cummulative distribution function x2 3x3 4x capacity Figure-5. System capacity as a function of outage probability. 8x8 BER SNR(dB) Figure-6. Performance of BER with correlation coefficient = X 2 3 X 3 4 x 4 8 x 8 5. CONCLUSIONS MIMO systems with reduced complexity are now being used for third-generation cellular systems (W- CDMA), and are discussed for future high-performance mode of wireless networks. The multiple antennas in MIMO systems can be exploited in two different ways. One is the creation of a highly effective antenna diversity system; the other is the use of the multiple antennas for the transmission of several parallel data streams to increase the capacity and increase the BER performance of the system. Multiple antenna communications technologies offer significant advantages over single antenna systems. These advantages include extended range, improved reliability in fading environments and higher data throughputs. REFERENCES [1] Akhilesh Kumar and Anil Chaudhary Channel Capacity Enhancement of Wireless Communication using Mimo Technology. International Journal of Scientific and Technology Research. 1(2), March. [2] Mahesh Kusuma, Mohan Amgothu and Bhadru Amgothu. Capacity Analysis of Mimo Systems. International Journal of Advances in Computer Networks and its Security. [3] Deeparani Mishra, Sikha Mishra and Mihir N. Mohanty Estimation of MIMO-OFDM Based Channel for High Data Rate Wireless Communication. IJCSIT. 2(3): [4] Syed M. Tabish Qaseem and Adel A. Ali Effect of Antenna Correlation and Rician Fading on Capacity and Diversity Gains of Wireless MIMO Channels. International Symposium on Wireless Communications (ISWSN'05). 809

5 [5] Marco Chiani, Moe Z. Win and Alberto Zanella On the Capacity of Spatially Correlated MIMO Rayleigh-Fading Channels. IEEE Transactions on Information Theory. 49(10): , October. [6] Michael A. Jensen and Jon W. Wallace A Review of Antennas and Propagation for MIMO Wireless Communications. IEEE Transactions on Antennas and Propagation. 52(11): , November. [7] Persefoni Kyritsi, Donald C. Cox, Reinaldo A. Valenzuela and Peter W. Wolniansky Correlation Analysis Based on MIMO Channel Measurements in an Indoor Environment. IEEE Journal on Selected Areas in Communications. 21(5), June. [8] Andreas F. Molisch and Moe Z. Win MIMO Systems with Antenna Selection - An Overview. First printing, TR , March. [9] G. J. Foschini and M. J. Gans On limits of wireless communications in a fading environment when using multiple antennas. Wireless Pers. Commun. 6: , March. [10] J. G. Proakis Digital Communications. 4 th Edition, McGraw-Hill, New-York, India. [11] J. D Kraus and R.J Marhefka Antennas for All Applications. Tata McGraw-Hill. [12] C. A Balanis Antenna Theory. John Wiley and Sons, Inc. 810

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