Reflecting Modulation

Shuaishuai Guo, Shuheng Lv, Haixia Zhang, Jia Ye, Peng Zhang

Research output: Contribution to journalArticlepeer-review

78 Scopus citations


Reconfigurable intelligent surface (RIS) has emerged as a promising technique for future wireless communication networks. How to reliably transmit information in a RIS-based communication system arouses much interest. This paper proposes a reflecting modulation (RM) scheme for RIS-based communications, where both the reflecting patterns and transmit signals can carry information. Depending on that the transmitter and RIS jointly or independently deliver information, RM is further classified into two categories: jointly mapped RM (JRM) and separately mapped RM (SRM). JRM and SRM are naturally superior to existing schemes, because the transmit signal vectors, reflecting patterns, and bit mapping methods of JRM and SRM are more flexibly designed. To enhance transmission reliability, this paper proposes a discrete optimization-based joint signal mapping, shaping, and reflecting (DJMSR) design for JRM and SRM to minimize the bit error rate (BER) with a given transmit signal candidate set and a given reflecting pattern candidate set. To further improve the performance, this paper optimizes multiple reflecting patterns and their associated transmit signal sets in continuous fields for JRM and SRM. Numerical results show that JRM and SRM with the proposed system optimization methods considerably outperform existing schemes in BER.
Original languageEnglish (US)
Pages (from-to)1-1
Number of pages1
JournalIEEE Journal on Selected Areas in Communications
StatePublished - 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The work of S. Guo, S. Lv, J. Ye, and P. Zhang was supported in part by the National Natural Science Foundation of China under Grant
61801266 and in part by the Shandong Natural Science Foundation under Grant ZR2018BF033. The work of H. Zhang was supported by National Natural Science Foundation of China under Grant No. 61860206005 and No. 61671278


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