可重构全息表面用于同时无线信息和功率传输
Reconfigurable Holographic Surface for Simultaneous Wireless Information and Power Transfer
- Shanghai Jiao Tong University（上海交通大学）
- Xi’an Jiaotong University（西安交通大学）
- Beijing University of Posts and Telecommunications（北京邮电大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出利用可重构全息表面（RHS）提升同时无线信息和功率传输（SWIPT）性能，通过联合优化基站数字与RHS全息波束成形，并采用低复杂度算法，在保证能量收集需求的同时显著提升加权和速率。
AI中文摘要：
本文提出利用一种新型可重构全息表面（RHS），通过利用全息干涉原理所实现的额外空间自由度（DoFs），来提升同时无线信息和功率传输（SWIPT）的性能。具体而言，我们研究了一个由RHS赋能的SWIPT系统，其中基站（BS）处的数字波束成形器和RHS处的全息波束成形器被联合优化，以在保证每个能量收集（EH）用户最低收集能量要求的同时，最大化信息解码（ID）用户的加权和速率。由于优化问题的非凸性，加权和速率最大化问题难以求解。我们首先采用加权最小均方误差（WMMSE）方法将目标函数转化为更易处理的形式。随后，我们开发了一个迭代优化框架，其中基站数字波束成形和RHS全息波束成形子问题通过最大最小化（MM）方法求解。由于随着变量维度的增加，求解每个子问题可能产生过高的复杂度，我们进一步基于交替方向乘子法（ADMM）方法论，为这两个子问题提出了低复杂度解决方案。数值结果验证了所提算法的收敛行为，并表明RHS辅助的基站相较于传统全数字基站基准取得了显著的性能提升。此外，所提出的低复杂度算法在保持几乎相同性能的同时，大幅降低了计算复杂度。
英文摘要：
In this paper, we propose to use a novel reconfigurable holographic surface (RHS) to improve the performance of simultaneous wireless information and power transfer (SWIPT) by exploiting the additional spatial degrees of freedom (DoFs) enabled by the holographic interference principle. Specifically, we study an RHS-empowered SWIPT system in which the digital beamformer at the base station (BS) and the holographic beamformer at the RHS are jointly optimized to maximize the weighted sum-rate of information-decoding (ID) users while guaranteeing a minimum harvested energy requirement for each energy-harvesting (EH) user. Due to the non-convexity of the optimization problem, the weighted sum-rate maximization problem is challenging to solve. We first adopt the weighted minimum mean squared error (WMMSE) method to transform the objective into a more tractable form. We then develop an iterative optimization framework, where the BS digital beamforming and the RHS holographic beamforming subproblems are solved via the majorization-minimization (MM) method. Since solving each subproblem can incur prohibitive complexity as the variable dimension increases, we further propose low-complexity solutions for the two subproblems based on the alternating direction method of multipliers (ADMM) methodology. Numerical results validate the convergence behavior of the proposed algorithms and demonstrate that the RHS-aided BS achieves significant performance gains over a conventional fully-digital BS benchmark. Moreover, the proposed low-complexity algorithms substantially reduce computational complexity while maintaining nearly the same performance.
