This paper presents a downlink reconfigurable intelligent surface (RIS)-assisted half-duplex (HD) cooperative rate splitting multiple access (C-RSMA) networks. The proposed system model is built up considering one base station (BS), one RIS, and two users. With the goal of minimizing the network energy consumption, a joint framework to optimize the precoding vectors at the BS, common stream split, relaying device transmit power, the time slot allocation, and the passive beamforming at the RIS subject to the power budget constraints at both the BS and the relaying node, the quality of service (QoS) constraints at both users, and common stream rate constraint is proposed. The formulated problem is a non-convex optimization problem due to the high coupling among the optimization variables. To tackle this challenge, an efficient algorithm is presented by invoking the alternating optimization technique, which decomposes the original problem into two sub-problems; namely, sub-problem-1 and sub-problem-2, which are alternatively solved. Specifically, sub-problem-1 is to jointly optimize the precoding vectors, common stream split, and relaying device power. Meanwhile, sub-problem-2 is to optimize the phase shift matrix at the RIS. In order to solve sub-problem-1, an efficient low-complexity solution based on the successive convex approximation (SCA) is proposed. Meanwhile, and with the aid of difference-of-convex rank-one representation and the SCA approach, an efficient solution for the phase shift matrix at the RIS is obtained. The simulation results demonstrate that the proposed RIS-assisted HD C-RSMA achieves a significant gain in minimizing the total energy consumption compared to the RIS-assisted RSMA scheme, RIS-assisted HD cooperative non-orthogonal multiple access (C-NOMA), RIS-assisted NOMA, HD C-RSMA without RIS, and HD C-NOMA without RIS.
翻译:本文展示了一个下行链条, 以智能表面( RIS) 辅助半双倍( HD) 合作率分割多个接入网络。 拟议的系统模型是在考虑一个基站( BS) 、 一个 RIS 和两个用户的情况下构建的。 为了最大限度地减少网络能源消耗, 一个优化BS预编码矢量的联合框架, 共同流分割, 中继设备传输电源, 时间档分配, 以及RIS 的被动波束, 但须受BS 和中继节点的电力预算限制、 用户的服务质量( QOS) 和通用流速率限制。 由于优化变量之间的高度组合, 开发的系统模型是一个非电流优化的问题。 为了应对这一挑战, 一个高效的算法, 将最初的问题分解成两个子问题; 即, 分流分流RISMRIS-1 和分流点-2, 正在解决的是, 低序- IMA 和 快速流- 数据- 工具- 工具- 工具- 流- 工具- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 至- 至- 至- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流- 流-流- 流- 流- 流- 流- 流-流- 流- 流- 流-