Robust Adaptive Beamformer using Improved Coprime Array for Wireless Communication Application

Abstract

In this paper, we present an innovative approach to beamforming that combines the strengths of blind and non-blind algorithms using Co-Prime Sensor Arrays (CPSA). By cascading the Least Square Constant Modulus Algorithm (LS-CMA) and the Least Mean Square (LMS) method, we achieve enhanced performance in terms of convergence speed, robustness, and signal quality. The initial stage involves employing the LS-CMA to obtain a preliminary estimate of the beamforming weights without requiring a reference signal. Subsequently, the LMS algorithm refines these weights to minimize the mean square error using a reference signal. The use of CPSA further improves the spatial resolution and reduces the number of sensors required. Simulation results demonstrate the effectiveness of the proposed method in various signal conditions, showcasing its potential for advanced communication systems and radar applications.