Optimal null steering of minimum variance distortionless response adaptive beamforming using particle swarm optimization and gravitational search algorithm

Abstract

Minimum Variance Distortionless Response (MVDR) adaptive beamforming technique commonly applies to cancel interfering sources and steer a strong beam towards the desired signal through its computed weight vectors. However, this method may have unsatisfactorily low nulling in various interference scenarios. Hence, adaptive beam pattern of MVDR can be considered as an optimization problem. The aim of this paper is to propose Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) to assist MVDR in improving its performance and overcoming both interferences and multipath fading. The simulation results show that the proposed GSA-MVDR algorithm offers higher Signal to Interference and Noise Ratio (SINR) than PSO-MVDR and conventional MVDR in different scenario of interferences and array elements. It is an effective solution for decreasing the effect of interference and increasing the desired signal simultaneously.