Discrete-Phase Max-SINR Beam Steering for IRS-enabled Wireless Communications

This paper aims to improve coverage, signal quality, and spectral efficiency in multi-user wireless communication systems by performing angle-domain analysis for a reconfigurable intelligent surface (IRS)-assisted network. The system under study consists of a multi-antenna base station (BS) serving multiple single-antenna users, with an IRS deployed to enhance propagation conditions. We develop an optimal zero-forcing (ZF) beamforming precoder at the BS by exploiting the angle-domain characteristics of the propagation paths to suppress inter-user interference. An optimization framework is formulated to configure the IRS phase shifts to maximize each user’s signal-to-interference-plus-noise ratio (SINR). To overcome the non-convexity and complexity of this problem, we propose a quantization-based approximation approach, where the solution for continuous phase values is mapped to discrete quantized levels. This hybrid design ensures near-optimal performance while significantly reducing computational complexity. Simulation results show that the proposed IRS-aided beamforming and phase quantization algorithm achieves substantial gains in SINR, throughput, and spectral efficiency compared to random phase configurations. Furthermore, increasing the number of IRS elements effectively offsets the performance degradation caused by coarse phase quantization, confirming the robustness and scalability of the proposed approach.