Hybrid Beamforming for Massive MIMO Antenna Array Processor in 5G Wireless Communication

Abstract

In order to overcome limitations in available frequency ranges, regulatory agencies such as the FCC are actively searching for ways to maximize the efficiency of bandwidth usage and improve customer satisfaction within the field of radio communication. This study highlights the crucial significance of Massive Multiple Input Multiple Output (MIMO) systems in addressing these problems in 5G wireless networks, resulting in improved spectrum efficiency and stability. The study presents a geometric channel model for massive MIMO systems that make use of Uniform Linear Array (ULA), Uniform Rectangular Array (URA), and Uniform Circular Array (UCA). Following that, a hybrid beamforming system is introduced, which integrates enhanced algorithms in both digital and analog precoders. This innovative methodology significantly minimizes approximation errors, thus improving spectral efficiency (SE). A comparative analysis is performed by implementing the hybrid beamforming algorithm on different array topologies to evaluate the differences between fully digital and hybrid systems. Although there is a slight decrease in SE, the hybrid model offers a notable benefit by requiring fewer antenna components upto 98.43%, making it an attractive choice in terms of performance and cost. Moreover, the study emphasizes the exceptional efficacy of the hybrid approach in the URA system, particularly when combined with specific array configurations and found 38.72 bits/s/Hz SE.