[论文解读] Performance Comparison between Reconfigurable Intelligent Surface and Relays: Theoretical Methods and a Perspective from Operator
本文通过使用交替加权最小均方误差(MMSE)优化方法,对可重构智能表面(RIS)与主动中继(FDR/HDR)在MIMO系统中的性能进行了公平比较,旨在最大化端到端吞吐量。RIS在频谱效率方面可与HDR相媲美,在能量效率方面优于FDR,且其性能可通过增加反射单元数量进行扩展,从运营商视角来看,是一种低功耗、灵活的6G网络替代方案。
Reconfigurable intelligent surface (RIS) is an emerging technique employing metasurface to reflect the signal from the source node to the destination node without consuming any energy. Not only the spectral efficiency but also the energy efficiency can be improved through RIS. Essentially, RIS can be considered as a passive relay between the source and destination node. On the other hand, a relay node in a traditional relay network has to be active, which indicates that it will consume energy when it is relaying the signal or information between the source and destination nodes. In this paper, we compare the performances between RIS and active relay for a general multiple-input multiple-output (MIMO) system. To make the comparison fair and comprehensive, both the performances of RIS and active relay are optimized with best-effort. In terms of the RIS, transmit beamforming and reflecting coefficient at the RIS are jointly optimized so as to maximize the end-to-end throughput. Although the optimization problem is non-convex, it is transformed equivalently to a weighted mean-square error (MSE) minimization problem and an alternating optimization problem is proposed, which can ensure the convergence to a stationary point. In terms of active relay, both half duplex relay (HDR) and full duplex relay (FDR) are considered. End-to-end throughput is maximized via an alternating optimization method. Numerical results are presented to demonstrate the effectiveness of the proposed algorithm. Finally, comparisons between RIS and relays are investigated from the perspective of system model, performance, deployment and controlling method.
研究动机与目标
- 对RIS与主动中继(FDR/HDR)在MIMO系统中的性能进行公平、全面的比较。
- 采用尽力而为、收敛性有保障的算法,优化RIS与中继的端到端吞吐量。
- 从运营商视角评估系统模型、性能、部署方式与控制方法。
- 评估频谱效率、能量效率与部署灵活性之间的权衡。
- 展示RIS作为低功耗、可扩展的主动中继替代方案在6G网络中的可行性与优势。
提出的方法
- 将RIS辅助MIMO系统的端到端吞吐量最大化问题建模为一个非凸问题,涉及发射波束成形与RIS反射系数的联合优化。
- 将RIS优化问题转化为加权均方误差(MSE)最小化问题,以确保收敛性。
- 采用交替优化算法,联合优化波束成形与反射系数,确保收敛至驻点。
- 同时考虑半双工中继(HDR)与全双工中继(FDR),采用类似的交替优化方法以实现吞吐量最大化。
- 采用3GPP城市微(UMi)路径损耗模型,结合瑞利衰落与实际系统参数(如43 dBm发射功率、3 GHz、100 MHz带宽)。
- 通过仿真评估,比较不同RIS单元数量与部署距离下的频谱效率与能量效率。
实验结果
研究问题
- RQ1在MIMO系统中,RIS在端到端频谱效率方面与HDR和FDR相比如何?
- RQ2在实际部署约束下,RIS与主动中继之间的能量效率权衡如何?
- RQ3RIS能否在无需有线电源供电的情况下,实现与中继相当或更优的性能?
- RQ4反射单元数量与部署位置如何影响RIS相对于中继的性能?
- RQ5从运营商的运营视角来看,RIS与中继在系统建模、控制复杂度与部署灵活性方面有何关键差异?
主要发现
- RIS在频谱效率方面可与HDR相媲美,在能量效率方面优于FDR,尤其在反射单元数量较多时更为显著。
- 可实现速率随RIS反射单元数量的增加而提升,且更高的发射功率(43 dBm)可进一步增强频谱效率。
- RIS的能量效率保持较高水平,与FDR相比相当或更优,尤其在靠近源或目的节点部署时表现更佳。
- 尽管FDR的原始频谱效率更高,但RIS在能量效率方面仍优于FDR,凸显其在功率受限场景中的优势。
- 将RIS部署在靠近源或目的节点的位置(如d₁ = 50 m)可显著提升性能,表明其为最优部署位置。
- RIS可实现无源或半无源部署,无需有线供电,支持灵活、按需部署——对6G网络的网络深度覆盖至关重要。
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