An Unknown Interference Suppression Scheme for Advanced Antenna Systems

An unknown interference suppression scheme for advanced antenna systems has been proposed to address critical challenges in enhancing wireless communication networks. This scheme focuses on improving beamforming capabilities and spectral efficiency while minimizing the impact of unknown interference. The ability to suppress unknown interference is achieved through a fitness function that does not rely on prior knowledge of interference characteristics. This function is designed based on the assumption that the desired signal is received through the main lobe, while interference predominantly resides in the sidelobes. By incorporating a constraint handling technique, specifically the static penalty method, the fitness function ensures that total output power is minimized only when interference power in the sidelobes is effectively reduced. Additionally, the optimization process is streamlined by reducing the number of optimization variables, focusing on uniform rectangular arrays with square element distributions. Metaheuristic algorithms, including the Binary Bat Algorithm, Binary Grey Wolf Optimization, and Binary Whale Optimization Algorithm, are applied to adaptively suppress unknown interference while reducing computational complexity. The proposed scheme significantly enhances advanced antenna systems performance by steering adaptive nulls toward unknown interference sources, ensuring robustness in dynamic wireless environments.