On the Capacity of Reconfigurable Intelligent Surface Assisted MIMO Symbiotic Communications

Jia Ye, Shuaishuai Guo, Shuping Dang, Basem Shihada, Mohamed-Slim Alouini

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Reconfigurable intelligent surfaces (RISs) appear as one of the most promising paradigms for future wireless communications, because of their high adjustability for diverse communication demands and the additional information-carrying capability by reflecting patterns. This paper investigates the capacity of RIS-assisted multiple-input multiple-output (MIMO) symbiotic communications utilizing multiple reflecting patterns, where each reflecting pattern is non-uniformly activated to carry additional information. To enhance transmission performance, the reflecting patterns, reflecting activation probability, and the transmit covariance matrix are jointly designed. Since the exact expression of the system capacity is intractable, the lower and upper bounds on the capacity are derived and used for optimization in this paper. Based on the lower bound on the capacity, a gradient ascent algorithm is developed to find the optimal reflecting patterns, reflecting activation probability, and the transmit covariance matrix. By taking advantage of the concise-form upper bound on the capacity, closed-form solutions of the reflecting activation probability and transmit covariance matrix can be derived after optimizing the reflecting patterns. The superiority of the proposed design is investigated and verified by computer simulations. Some selected numerical results demonstrate that the proposed design can achieve a higher capacity than the benchmark adopting only one reflecting pattern.
Original languageEnglish (US)
Pages (from-to)1-1
Number of pages1
JournalIEEE Transactions on Wireless Communications
DOIs
StatePublished - 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-09-09
Acknowledgements: This work of J. Ye, B. Shihada, and M.-S. Alouini was funded by the KAUST Office of Sponsored Research. The work of S. Guo is supported by in part by the National Natural Science Foundation of China under Grant 62171262 and 61801266, and in part by Major Scientific and Technological Innovation Project of Shandong Province under Grant 2020CXGC010109. The associate editor coordinating the review
of this manuscript and approving it for publication was Dr. Sofie Pollin.

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