Design Approach of a Wideband Non-Uniformly Spaced Linear Array Based on Reinforcement Learning to Suppress Multiple Interference Signals

Abstract

In this paper, we present a novel design approach for a wideband non-uniformly spaced linear array (NUSLA) to suppress the effect of interference signals. Notably, a uniform linear array (ULA), which is easy to handle, is widely utilized to generate nulls over a wide band; however, its beamforming performance is limited owing to the ULA structure. Although a NUSLA with nonlinear spacing addresses nonlinear problems that are difficult to handle mathematically, it can exhibit performance improvements surpassing those of ULA structures. However, an additional constraint is required to generate nulls at a specific position, and this has not yet been studied for null generation using wideband NUSLA. In this paper, we propose a novel cost function for designing a wideband NUSLA, which generates a null at the desired position, and we utilize the modified reinforcement learning algorithm (MORELA), which is a heuristic optimization algorithm based on reinforcement learning (RL), to minimize the proposed cost function and analyze the optimized antenna array and weights. Further, we compare the performance of the proposed MORELA based on RL with that of existing heuristic optimization algorithms via computer simulations.