Low-Complexity Beamforming Optimization for IRS-Aided MU-MIMO Wireless Systems

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In this paper, we propose a cost-efficient beamforming optimization algorithm for multi-user wireless communication systems associated with the intelligent reflecting surface (IRS). From the baseline successive refinement algorithm, which gives a sub-optimal solution for the power minimization problem under the signal-to-interference-plus-noise-ratio (SINR) constraint at each user, several optimization techniques are proposed to reduce the computation complexity while maintaining the algorithm-level performance. To reduce the number of required multiply-accumulate (MAC) operations, we first simplify the complicated matrix inversion by utilizing the channel hardening effect. We also present the two-phase refinement process for the group-level optimization of phase-shift elements, further relaxing the computation complexity as well as the processing latency. Applying the proposed optimization techniques, as a result, numerical results show that the fully-optimized algorithm can reduce the computational costs by up to 89.4% while showing less than 1 dB power loss, leading to the practical solution for the next-generation IRS-aided communication.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2022-05
Language
English
Article Type
Article
Citation

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.71, no.5, pp.5587 - 5592

ISSN
0018-9545
DOI
10.1109/TVT.2022.3152253
URI
http://hdl.handle.net/10203/296916
Appears in Collection
EE-Journal Papers(저널논문)
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