Adaptive beamforming for uniform circular arrays

Beamforming in smart antennas is a highly effective technique that utilizes the flexible adjustment of antenna radiation characteristics, including main beam direction, interference nulling, and sidelobe level control. This paper proposes an adaptive beamforming solution based on the hybrid optimization algorithm combining Particle Swarm Optimization Grey Wolf Optimizer (HPSOGWO) and Bat Algorithm (BA) for Uniform Circular Arrays (UCA). The proposed approach demonstrates the ability to place nulls at interference directions and steer the main beam toward the desired direction. The modeling of circular antenna arrays, objective function, and evaluation scenarios will be presented. Additionally, the cumulative distribution function (CDF) and signal-to-noise ratio (SNR) will be addressed to assess system performance.