Performance analysis of particle swarm optimization and genetic algorithm in MIMO systems

The Multi-input multi-output (MIMO) technique is very useful for increasing the transmission reliability, high date rate, robustness and channel capacity in the modern radio communication systems. As many algorithms inspired from the nature have been proposed to evaluate the performance of MIMO system parameters like channel capacity, bit error rate and the best fitness value of channel capacity. But this technique delivers some issues such as increases the cost and complexity of hardware due to increasing number of antennas. To solve this issue, an effective optimal transmit antenna subset selection method is described in this paper with the aid of PSO. For each position of the particle, corresponding fitness function is evaluated and from there global best fitness values are chosen. The implementation of proposed work is done in the working platform MATLAB and the performance of MIMO are evaluated with various selection of transmit antenna subsets. Moreover, Improvement in Channel Capacity and BER with increasing SNR are discussed Hence, with the aid of proposed work, the selection of transmit antenna with the maximum capacity and minimum BER are made and which leads to the reduced hardware complexity and decrease number of antennas in the MIMO system.