Meta‐heuristic optimization algorithms for placement of multiple nulls and minimization of side lobe level in quadrant symmetric sparse array antenna

Abstract

SummaryThe optimization of the non‐uniform planar array antenna parameter in order to minimize the signal interference in the electromagnetic environment through null placement is one of the most important areas of investigation in the field of wireless communication. This study deals with an effective method of synthesis of a quadrant symmetric sparse planar array antenna using the novel implementation of the well‐known meta‐heuristic optimization algorithms, namely, symbiotic organism search (SOS) and moth flame optimization (MFO) algorithms. The objective of this work is to place multiple small and wide nulls at the desired angles and simultaneously minimize the side lobe levels using a nonlinear mathematical approach. Three examples are presented with constraints that include the inter‐elemental distance, fixed number of array elements in the aperture, and the aperture size. The radiating antenna array elements are considered to have fixed uniform current distribution. The meta‐heuristic optimization approach offers the advantages of avoiding the infeasible solution while finding the best optimal set of element positions to reduce side lobe level in the desired radiation pattern. The radiation pattern characteristics and the computation time associated with each example and each algorithm are recorded and compared for arriving at the conclusion. The superiority of SOS is found in terms of the optimized side lobe levels. At the same time, both algorithms are found to be efficient in positioning the symmetric nulls in desired locations in the radiation pattern successfully. When compared with the published papers, proposed approach yields better results confirming the effectiveness of the performance of these algorithms.