Hybrid Meta-Heuristic Algorithms Based Optimal Antenna Selection for Large Scale MIMO in LTE Network
Abstract
MIMO is a type of antenna technology which utilizes multiple antennas to separate signals traveling in various paths as a result of reflections, etc., to be separated and their ability utilized to enhance the throughput of data and the signal to noise ratio which in return enhances the performance of the system. For providing enhanced signal performance and enhanced data rates, MIMO is utilized within LTE. When the quantities of antennas are increased, there is increase in the probability that deep fading is experienced by at least some antennas, which affects the overall efficiency of the MIMO system. To handle these issues, a reliable technique has been presented that involves selection of antenna subset. The proposed technique incorporates combination of SBO and PSO for antenna selection. Antenna selection’s main concept is to utilize a bounded quantity of analog chains that are adaptively switched to subset of the available antennas capable of preserving the selection diversity gains and also can minimize the quantity of radio frequency chains needed. The maximum channel capacity of the channel has been considered as the objective function for selecting optimal antennas. The comparison of the proposed approach’s performance and the existing approaches’ performance is done. From the simulation result, it has been shown that the presented approach’s performance has been better than the performance of the existing approaches in terms of BER, energy efficiency, spectral efficiency and optimal transmit power.
