信道估计误差下超越对角可重构智能表面赋能的RSMA-SWIPT系统鲁棒设计
Robust Design of Beyond-Diagonal Reconfigurable Intelligent Surface Empowered RSMA-SWIPT System Under Channel Estimation Errors
AI总结：
本文研究了信道估计误差下BD-RIS赋能的RSMA-SWIPT系统，提出基于交替优化的鲁棒设计框架，联合优化发射预编码、功率分割及散射矩阵，显著提升了系统总速率与收敛速度。
摘要：
本研究探讨了速率分割多址接入（RSMA）、同时无线信息与功率传输（SWIPT）以及超越对角可重构智能表面（BD-RIS）的集成，以增强未来第六代（6G）通信网络的频谱效率、能量效率、覆盖范围和连接性。具体而言，针对多用户BD-RIS赋能的RSMA-SWIPT系统，在不完美信道状态信息（CSI）的假设下，我们联合优化了发射预编码向量、用户的公共速率比例、功率分割比以及BD-RIS节点的散射矩阵。此外，为了更好地捕捉实际硬件行为，我们在能量收集约束下引入了非线性能量收集模型。我们设计了一个鲁棒优化框架以最大化系统总速率，同时明确考虑了CSI不确定性的最坏情况影响。进一步，我们引入了一个交替优化框架，将该问题划分为多个模块进行迭代优化。更具体地说，通过逐次凸逼近（SCA）将问题重构为凸半定规划来优化发射预编码向量，而功率分割问题则使用支持MOSEK的CVX工具箱求解。随后，为了优化BD-RIS的散射矩阵，我们首先采用SCA将问题重构为凸形式，然后设计了一种基于共轭梯度法的流形优化策略。最后，数值仿真结果表明，所提方案相比现有基准提供了显著的性能提升，并在合理的迭代次数内展现出快速收敛性。
英文摘要：
This work explores the integration of rate-splitting multiple access (RSMA), simultaneous wireless information and power transfer (SWIPT), and beyond-diagonal reconfigurable intelligent surface (BD-RIS) to enhance the spectral-efficiency, energy-efficiency, coverage, and connectivity of future sixth-generation (6G) communication networks. Specifically, with a multiuser BD-RIS-empowered RSMA-SWIPT system, we jointly optimize the transmit precoding vectors, the common rate proportion of users, the power-splitting ratios, and scattering matrix of BD-RIS node, under the assumption of imperfect channel state information (CSI). Additionally, to better capture practical hardware behavior, we incorporate a nonlinear energy harvesting model under energy harvesting constraints. We design a robust optimization framework to maximize the system sum-rate, while explicitly accounting for the worst-case impact of CSI uncertainties. Further, we introduce an alternating optimization framework that partitions the problem into several blocks, which are optimized iteratively. More specifically, the transmit precoding vectors are optimized by reformulating the problem as a convex semidefinite programming through successive-convex approximation (SCA), whereas the power-splitting problem is solved using the MOSEK-enabled CVX toolbox. Subsequently, to optimize the scattering matrix of the BD-RIS, we first employ SCA to reformulate the problem into a convex form, and then design a manifold optimization strategy based on the Conjugate-Gradient method. Finally, numerical simulation results reveal that the proposed scheme provides significant performance improvements over existing benchmarks and demonstrates rapid convergence within a reasonable number of iterations.
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