Artificial-Intelligent-Enhanced Adaptive Vertical Beamforming Techniques for 5G Networks

Abstract

The advances of 5G era systems and technology throughout the years suggests new uses for Adaptive beamforming and Digital Signal Processing (DSP) strategies in the communication systems to determine the transformational capacity of 5G wireless technology. This article evaluates the performance metrics of phase shift beamforming in a system of phased Uniform Rectangular Array (URA) aided with Artificial Intelligence (AI) to improve the link and communication quality in dense user urban environments. We use the conventional Quadrature Amplitude Modulation (QAM) for evaluating its robustness through a series of simulations for Bit Error Rate (BER) under different Signal to Noise Ratio (SNR) values. This study describes the opposition of theoretical and empirical BER to confirm the beamforming algorithm’s operation in the communication system. We propose a spatial spectrum technique for a clear visualization of the Direction of Arrival (DoA) that gives the details of signal movement of users in the network and array behavior in the base station (BS). So, these results not only confirm the proposed methods effectiveness in the mobile network, but also highlight the importance of a creative AI system embedded with beamforming in achieving the expected performance metrics and reliability for future 5G communication networks and beyond.