RIS-Based Opposite Phase Index Modulation and Its DNN-Assisted Joint Sequence Detection

Abstract

Reconfigurable intelligent surface (RIS), a key technology for future wireless communications, allows intelligent reflection of signals and information transmission. The RIS-based modulation is considered a prospective information transmission mechanism. In this paper, a RIS-based opposite phase index modulation system is proposed, in which RIS can enhance the received power of user signals while transmitting additional data bits for near-end internet of things devices via opposite phase reflection pattern index without any additional radio frequency chain. To reduce the computational complexity of receiver detection, a deep neural network-assisted joint sequence detection method is proposed, in which the reflection pattern index and the symbol index are jointly detected. In addition, we derive the theoretical upper bound performance of the proposed modulation scheme in terms of the average bit error rate (BER) with the maximum likelihood detection. The theoretical and simulation results show that the proposed scheme has better BER performance and lower detection complexity than existing RIS-based modulation schemes.