An Evolutionary Approach to Improve the Beam Steering Performance over Conventional Approach in CHAA

In this work, evolutionary algorithms are applied for the first time to achieve better radiation characteristics over the conventional beamforming algorithm in the concentric hexagonal antenna array (CHAA), which improves the performance of wireless communication. Multiple signal classification (MUSIC) algorithm is employed for direction of arrival (DoA) estimation. The conventional adaptive beam steering algorithm, least mean-square (LMS) algorithm, is used to steer the beam. Further, the proposed approach is employed by novel particle swarm optimization (NPSO) to reduce sidelobe level (SLL) even further. A six-ring CHAA with 126 elements for DoA estimation and beam steering is simulated. The simulation results of the MUSIC, LMS, NPSO, and particle swarm optimization (PSO) algorithms are provided for various DoAs.