A Hybrid Adaptive Beamforming Algorithm for SINR Enhancement in Massive MIMO Systems

Abstract

With the extreme density of devices and fast change of their directions in massive MIMO networks, a fast adaptive beamforming algorithm is required to provide high directivity and an enhanced signal-to-interference and noise ratio (SINR). Blind adaptive beamforming is suitable but less efficient, while non-blind adaptive beamforming is more efficient but requires significant training time. This study proposes a hybrid adaptive beamforming algorithm that addresses these issues. The algorithm integrates an improved direction-finding method to estimate the directions of arrival (DoAs) of incident signals at the antenna array, even in coherent signals cases, and a cascading combination of a blind and non-blind algorithms. The proposed algorithm generates an accurate main beam toward the desired direction and deep nulls in the direction of interfering signals, resulting in enhanced SINR. Compared to other algorithms, our approach achieves better performance without requiring additional antenna elements.