Low-Power B5G Communication Technology Based on Digital Beamforming and DOA Estimation

This study explores advancements in Beyond 5G (B5G) communication systems, focusing on improving signal quality, system efficiency, and energy management. We assess the impact of Digital Beamforming (DBF), Direction of Arrival (DOA) estimation, and Deep Learning (DL) algorithms across three configurations: without advanced technology, with DBF and DOA, and with DBF, DOA, and DL integration. Numerical simulations confirm that incorporating DL significantly enhances signal integrity and energy efficiency, particularly in long-range scenarios. The proposed DL model achieves competitive performance metrics, with MSE, MAE, and RMSE values all below 0.1, indicating its effectiveness in optimizing spectral and energy efficiency. These findings highlight the potential of DL in real-time beamforming and underscore its role in the future development of B5G networks.