In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted two-way relay network, in which two users exchange information through the base station (BS) with the help of an RIS. By jointly designing the phase shifts at the RIS and beamforming matrix at the BS, our objective is to maximize the minimum signal-to-noise ratio (SNR) of the two users, under the transmit power constraint at the BS. We first consider the single-antenna BS case, and propose two algorithms to design the RIS phase shifts and the BS power amplification parameter, namely the SNR-upper-bound-maximization (SUM) method, and genetic-SNR-maximization (GSM) method. When there are multiple antennas at the BS, the optimization problem can be approximately addressed by successively solving two decoupled subproblems, one to optimize the RIS phase shifts, the other to optimize the BS beamforming matrix. The first subproblem can be solved by using SUM or GSM method, while the second subproblem can be solved by using optimized beamforming or maximum-ratio-beamforming method. The proposed algorithms have been verified through numerical results with computational complexity analysis.
翻译:在本文中,我们考虑的是可重新配置的智能表面(RIS)辅助双向中继网络,其中两个用户在RIS的帮助下通过基站交换信息。通过联合设计RIS的阶段转换和BS的波形矩阵,我们的目标是在BS的传输功率限制下,使两个用户的最小信号-噪音比最大化。我们首先考虑单电脉冲双向中继系统,并提议两种算法来设计RIS阶段转换和BS动力放大参数,即SNR-上线-带式混合法(SUM)和遗传-SNR-MXIM(GSM)法。当BS有多个天线时,最优化问题可以通过连续解决两个分解的子问题来解决,一个是优化RIS阶段的转换,另一个是优化BS的组合矩阵。第一个子问题可以通过使用SUM或GSM系统的方法加以解决,而通过采用最优化的算法,然后用最优化的算法来解决。