Fairness-Oriented Multiple RIS-Aided mmWave Transmission: Stochastic Optimization Methods

Zhou, Gui, Pan, Cunhua, Ren, Hong, Wang, Kezhi and Renzo, Marco Di (2022) Fairness-Oriented Multiple RIS-Aided mmWave Transmission: Stochastic Optimization Methods. IEEE Transactions on Signal Processing, 70. pp. 1402-1417. ISSN 1053-587X

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Official URL: https://doi.org/10.1109/TSP.2022.3158026


In millimeter wave (mmWave) systems, it is challenging to ensure reliable communication links due to the high sensitivity to the presence of blockages. In order to improve the robustness of mmWave systems in the presence of random blockages, we consider the deployment of multiple reconfigurable intelligent surfaces (RISs) to enhance the spatial diversity gain, and the design of robust beamforming schemes based on stochastic optimization methods that minimize the maximum outage probability among multiple users so as to ensure fairness. Under the stochastic optimization framework, we adopt the stochastic majorization–minimization (SMM) method and the stochastic successive convex approximation (SSCA) method to construct deterministic surrogate problems at each iteration, and to obtain closed-form solutions of the precoding matrix at the base station (BS) and the beamforming vectors at the RISs. Both stochastic optimization methods are proved to converge to the set of stationary points of the original stochastic problems. Simulation results show that the proposed robust beamforming for RIS-aided systems can effectively compensate for the performance loss caused by the presence of random blockages, especially when the blockage probability is high.

Item Type: Article
Additional Information: Funding information: This work was supported in part by the National Key Research and Development Project (2019YFE0123600), National Natural Science Foundation of China (62101128), Basic Research Project of Jiangsu Provincial Department of Science and Technology (BK20210205), High Level Personal Project of Jiangsu Province (JSSCBS20210105), and the Natural Science Foundation of Shanghai under Grant 22ZR1445600. The work of M. Di Renzo was supported in part by the European Commission through the H2020 ARIADNE project under grant agreement number 871464 and through the H2020 RISE6G project under grant agreement number 101017011.
Uncontrolled Keywords: Reconfigurable intelligent surface (RIS), intelligent reflecting surface (IRS), millimeter wave communications, stochastic optimization, robust beamforming design
Subjects: G400 Computer Science
G700 Artificial Intelligence
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 31 Mar 2022 13:02
Last Modified: 31 Mar 2022 13:15
URI: http://nrl.northumbria.ac.uk/id/eprint/48793

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