STAR-RIS Assisted Opportunistic Cognitive Radio Networks

To support the ever-increasing wireless traffic, cognitive radio (CR) has been identified as one of the most promising spectrum-sharing technologies in future wireless networks. In this paper, we study a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted opportunistic CR network, where the primary transmitter, secondary transmitter, and secondary receiver are located on one side of the STAR-RIS while the primary receiver is located on the other side. To improve the spectrum efficiency, we investigate a reflection and transmission coefficient optimization problem to maximize the average achievable rate of the secondary user (SU) while satisfying the rate requirement of the primary user (PU). Particularly, we propose a two-stage reflection and transmission coefficient optimization framework to decouple the considered optimization problem in the sensing and transmission stages. Specifically, in the sensing stage, the reflection and transmission coefficients are optimized to assist the transmission of the PU while realizing target detection and false alarm probabilities. In the transmission stage, the reflection and transmission coefficients are optimized to maximize the average achievable rate of the SU while satisfying the rate requirement of PU. Finally, extensive simulation results are provided to evaluate the performance of the STAR-RIS-assisted opportunistic CR network.