Optimization On Antenna Selection Using Imperialist Competitive Algorithm

Nowadays, the multiple antenna transmission technique, which may be modeled as Multiple Input Multiple Output (MIMO) systems, is used for increasing the capacity ofthe wireless communication systems. However, complexities and cost are associated with MIMO systems. Here, we proposea technique based on Imperialist Competitive Algorithm (ICA) to reduce the computational complexity and hardware cost. A new suboptimal configuration on antenna selection both in receiver and transmitter sides is the outcome of applying our method on MIMO systems. Our algorithm achieves almost thesame outage capacity as the optimal selection technique while having lower computational complexity than the exiting nearlyoptimal antenna selection methods such as genetic algorithms. The antenna selection algorithm requires an exhaustive searchof all possible combinations and permutations to find theoptimum solution at the transmitter or receiver side, thus resulting in extremely high computational complexity. Toreduce the computational load while still maximizing channel capacity, the ICA method is adopted to determine thesuboptimum solution. The simulation results show that theICA method has better performance from the point of view of both computational and time complexities, when compared with the Genetic Algorithm (GA) and Exhaustive search method (ES).

کلیدواژه ها:

Antenna Selection ، Genetic Algorithm ، Imperialist Competitive Algorithm ، MIMO System