发表机构
McGill University; China Telecom, P.R. China（麦吉尔大学; 中国电信）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文研究RIS辅助多向通信系统，提出三种SIC排序方法，并通过仿真验证：小规模RIS时均方误差排序最优，大规模时优化方法最优。
AI 中文摘要
本文研究了采用QPSK调制的可重构智能表面（RIS）辅助多向通信系统。该系统的目标是利用RIS的全双工能力，允许多个用户交换信息。所考虑的系统包含K个用户终端和一个具有N个反射单元的RIS。每个用户终端配备一个发射天线和M个接收天线。为了减轻由RIS全双工操作引起的用户间干扰，考虑了三种连续干扰消除（SIC）技术。我们研究了三种SIC排序方法：1）信道方差降序，2）均方误差递增，3）最大化系统内组合信道增益的优化方法。通过广泛的蒙特卡洛模拟，针对不同数量的RIS单元（从4到64）和不同数量的发射用户（从1到5），评估了这三种SIC方法的误码率（BER）性能。此外，还考虑了一种针对具有不同幅度反射单元的RIS的相移优化方法。在这种情况下，之前的SIC优化技术被调整以处理RIS反射单元中相位依赖的幅度。仿真结果表明，在理想和变幅度场景下，当RIS单元数量较少时，基于均方误差递增排序的SIC实现了最佳的BER性能。然而，随着RIS单元数量的增加，基于优化方法的SIC排序实现了最佳的BER性能。
英文摘要
This work considers reconfigurable intelligent surface (RIS) aided multi-way communication systems employing QPSK. The objectives of such system is to allow multiple users to exchange information, exploiting the full-duplex capabilities of RIS. The system under consideration comprises $K$ user terminals and an RIS with $N$ reflective elements. Each user terminal is equipped with one transmit and $M$ receive antennas. To mitigate inter-user interference caused by the full-duplex operation of the RIS, three successive interference cancellation (SIC) techniques are considered. We investigate three SIC ordering methods: $1)$ descending channel variances, $2)$ increasing mean square error, $3)$ optimization approach which maximizes the combined channel gain within the system. The bit error rate (BER) performance of these three SIC methods are evaluated using extensive Monte-Carlo simulations for different numbers of RIS elements, ranging from 4 to 64, and a varying number of transmitting users, ranging from 1 to 5. Additionally, an RIS phase shift optimization method for RIS with reflection elements of varying amplitudes is considered. In this case the previous SIC optimization technique is adapted to address phase-dependent amplitudes in RIS reflection elements. Simulation results indicate that in both ideal and varying amplitude scenarios, when the number of RIS elements is small, SIC with ordering based on increasing mean square error achieves the best BER performance. However, as the number of RIS elements increases, SIC ordering based on the optimization method achieves the best BER performance.
