Robust probabilistic-constrained optimization for IRS-aided MISO communication systems

Le, Tuan Anh ORCID logoORCID:, Trinh, Van Chien and Di Renzo, Marco (2021) Robust probabilistic-constrained optimization for IRS-aided MISO communication systems. IEEE Wireless Communications Letters, 10 (1) . pp. 1-5. ISSN 2162-2337 [Article] (doi:10.1109/LWC.2020.3016592)

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Taking into account imperfect channel state information, this letter formulates and solves a joint active/passive beamforming optimization problem in multiple-input single-output systems with the support of an intelligent reflecting surface. In particular, we introduce an optimization problem to minimize the total transmit power subject to maintaining the users' signal-to-interference-plus-noise-ratio coverage probability above a predefined target. Due to the presence of probabilistic constraints, the proposed optimization problem is non-convex. To circumvent this issue, we first recast the proposed problem in a convex form by adopting the Bernstein-type inequality, and we then introduce a converging alternating optimization approach to iteratively find the active/passive beamforming vectors. In particular, the transformed robust optimization problem can be effectively solved by using standard interior-point methods. Numerical results demonstrate the effectiveness of jointly optimizing the active/passive beamforming vectors.

Item Type: Article
Research Areas: A. > School of Science and Technology
Item ID: 30808
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Depositing User: Tuan Le
Date Deposited: 14 Aug 2020 12:10
Last Modified: 29 Nov 2022 18:03

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