Javad Zeraatkar Moghaddam
Hamid Farrokhi

The topic of power allocation in MIMO systems for wireless communication in order to reach high capacity or low bit error rate has gained some attention. In this paper, heuristic algorithms, including genetic and particle swarm optimization algorithms, are applied to find the optimal power allocation for achieving best capacity benefit. Two cases of un-polarized and cross-polarized antennas of spatial MIMO channel modeling are studied. We demonstrate that the performance of genetic and particle swarm optimization algorithms is optimal compared with a perfect search at a reduced computational complexity. These algorithms have fast convergence and can handle large number of sub-channels without performance degradation. Both simulation and numerical results confirm that, compared to other mathematical methods, the proposed algorithms are more efficient in terms of complexity and power assignment to antennas in a MIMO system.

MIMO systems, en, Channel capacity, Genetic Algorithm, particle swarm optimization algorithm, cross-polarized antennas, spatial channel model