A novel adaptive beamforming with reduced side lobe level using GSA. Issue 6 (5th November 2018) - Sharma, Abhinav; Mathur, Sanjay
Abstract : Purpose: The purpose of this paper is to present and solve the problem of adaptive beamforming (ABF) for a uniform linear array (ULA) as an optimization problem. ABF mainly concerns with estimation of weights of antenna array so as to direct the major lobe in the direction of desired user and nulls in the direction of interfering signals with reduced side lobe level (SLL). Design/methodology/approach: The potential of gravitational search algorithm is explored to optimize multi-objective fitness function for ABF using MATLAB software. Findings: The performance of the algorithm has been compared by considering different number of interference signals at different power levels. The proposed algorithm presents good convergence rate and accurate steering of main lobe and nulls with reduced SLL compared to the well-known ABF technique, namely, minimum variance distortionless response (MVDR) and previously reported results. The simulation results are presented in tabular form. Research limitations/implications: The present work is limited to simulation. The researchers are encouraged to solve the problem of ABF using the proposed approach in hardware. Originality/value: The application of proposed algorithm is to optimize multi-objective function for ABF with reduced SLL in linear antenna arrays.