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Sum-Rate Maximization in MISO IRS Multiuser System Using Adaptive Linear Precoding Technique
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DOI：10.1109/lcomm.2026.3713668.png)
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Abstract
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This letter proposes a new beamforming technique, Adaptive Regularized OLP (AR-OLP), by jointly optimizing transmit beamforming and IRS phase shifts to enhance spectral efficiency in downlink wireless communications. We provide a comparative analysis of AR-OLP with two key precoding algorithms: Optimal Linear Precoding (OLP) and Regularized Zero-forcing (RZF) to evaluate their performance under varying network parameters, including the number of transmit antennas, users, and IRS passive elements. Simulation results demonstrate that the proposed AR-OLP algorithm consistently achieves higher average sum rates per user compared to conventional OLP and RZF methods. The performance gains grow with increasing antenna count and IRS size, showing robust interference management and effective resource utilization across different transmit powers. These findings highlight the potential of adaptive hybrid precoding in IRS-aided MISO multiuser systems for next-generation wireless networks.
Keywords:
MISO
IRS
beamforming techniques
multiuser
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