Optimized Hybrid Beamforming for RIS-Assisted Multi-User MIMO in 6G mmWave Networks: A Low-Complexity Approach to Spectral Efficiency and Interference Mitigation

The joint optimization of hybrid beamforming and reconfigurable intelligent surface (RIS) phase shifts in multi-user millimeter-wave (mmWave) MIMO systems is a challenging problem, mainly due to high computational complexity and the lack of adaptive interference management. Existing approaches typically rely on fixed Zero-Forcing (ZF) or Maximum-Ratio Transmission (MRT) designs or require iterative optimization with high overhead, limiting their practical use in dense 6G environments. To overcome these challenges, this research proposes a RIS-Aided Adaptive Zero-Forcing and Maximum-Ratio Transmission Hybrid Precoding (RA-ZMHP) framework for 6G mmWave multi-user MIMO systems. The main novelty of the method lies in an adaptive ZF–MRT mixing strategy that dynamically balances interference suppression and beamforming gain based on real-time channel conditions. Unlike conventional hybrid beamforming schemes, the proposed framework jointly optimizes the digital baseband precoder, the analog RF precoder, the RIS phase shifts, and the power allocation using a weighted minimum mean-square error (WMMSE) formulation. To keep computational complexity low, closed-form updates based on Karush–Kuhn–Tucker (KKT) conditions are derived for power allocation, MMSE receiver design, and the adaptive ZF–MRT mixing factor. This ensures stable and fast convergence while avoiding complex iterative procedures. Simulation results show that the proposed RA-ZMHP scheme achieves lower MMSE, higher SINR, and faster convergence compared to conventional ZF, MRT, and fixed hybrid beamforming methods. Furthermore, performance improves with increasing transmit power and with a larger number of RIS elements, confirming the effectiveness and practicality of the proposed framework for interference mitigation and performance enhancement in future 6G wireless networks.