RIS辅助RSMA通感一体化系统的波束赋形设计

林颖; 崔苗; 张广驰

doi:10.12052/gdutxb.240087

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RIS辅助RSMA通感一体化系统的波束赋形设计

信息与通信工程 | 更新时间：2026-05-27

- RIS辅助RSMA通感一体化系统的波束赋形设计
- Beamforming Design in RIS-assisted RSMA Integrated Sensing and Communication System
- 广东工业大学学报 2025年42卷第6期页码：95-103
- 作者机构：
  
  广东工业大学信息工程学院,广东,广州,510006
- 作者简介：
  
  林颖(1999–)，男，硕士研究生，主要研究方向为可重构智能表面在通感一体化系统中的应用，E-mail：1332142295@qq.com
  崔苗(1978–)，女，副教授，博士，主要研究方向为电子信息与无线通信技术，E-mail：cuimiao@gdut.edu.cn
- 基金信息：
  
  广东省海洋经济发展资助项目(粤自然资合[2023]24号);广东省科技计划项目(2023A0505050127，2022A0505020008，2022A0505050023);广东省基础与应用基础研究基金资助项目(2023A1515011980);江西省军民融合研究院“北斗+”项目子课题(2024JXRH0Y02)
- DOI：10.12052/gdutxb.240087
  中图分类号： TN929.5
- 纸质出版：2025
- 稿件说明：
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林颖, 崔苗, 张广驰. RIS辅助RSMA通感一体化系统的波束赋形设计[J]. 广东工业大学学报, 2025, 42(6): 95–103.

Lin Ying, Cui Miao, Zhang Guangchi. Beamforming Design in RIS-assisted RSMA Integrated Sensing and Communication System[J]. 2025, 42(6): 95-103.
林颖, 崔苗, 张广驰. RIS辅助RSMA通感一体化系统的波束赋形设计[J]. 广东工业大学学报, 2025, 42(6): 95–103. DOI： 10.12052/gdutxb.240087

Lin Ying, Cui Miao, Zhang Guangchi. Beamforming Design in RIS-assisted RSMA Integrated Sensing and Communication System[J]. 2025, 42(6): 95-103. DOI： 10.12052/gdutxb.240087.

摘要

通信感知一体化将成为6G的一大业务应用，但如何实现通信与感知的资源合理分配，提高系统的整体性能和降低系统间的干扰是需要解决的难题。可重构智能表面(Reconfigurable Intelligence Surface

RIS) 和速率分割多址(Rate-splitting Multiple Access

RSMA) 被认为是6G时代的两项关键技术，是解决上述难题的有效手段。本文考虑一个RIS辅助RSMA的通感一体化系统，提出一个同时同频的通感一体化架构，并研究在实现通信和感知的良好权衡下，降低系统干扰和提升系统性能的速率分割和主被动波束赋形设计，制定了一个在满足有效感知功率阈值的约束下最大化系统的最小用户速率的优化问题。针对该非凸问题提出了一种联合优化算法，首先基于加权最小均方误差算法构造速率−加权最小均方误差关系，再使用块坐标下降法解耦变量划分子问题，结合连续凸逼近法交替求解。仿真结果表明，本文提出的算法在相同的发射功率预算下所得到的最小用户速率相较于其他基准方案有明显的增益，用户通信的公平性得到显著改善。

Abstract

An integrated sensing and communication system is expected to be a major application in 6G

but challenges remain in achieving efficient resource allocation and reducing interference between systems. Reconfigurable Intelligent Surfaces (RIS) and Rate-splitting Multiple Access (RSMA) are considered key technologies of 6G

offering potential solutions to these challenges. In this research

an RIS-assisted RSMA integrated sensing and communication system is proposed

introducing a framework for simultaneous communication and sensing using the same frequency spectrum. It explores rate-splitting and joint active-passive beamforming designs to enhance system performance and reduce interference while balancing communication and sensing needs. An optimization problem is formulated to maximize the minimum user rate under the constraint of an effective sensing power threshold. A joint optimization algorithm is proposed to solve this non-convex problem

utilizing a weighted minimum mean square error (WMMSE) approach to construct a rate-WMMSE relationship and employing block coordinate descent and successive convex approximation methods for variable decoupling and iterative solving. Simulation results show that the proposed algorithm achieves a significantly higher minimum user rate compared with other benchmark schemes under the same transmission power budget. This leads to a marked improvement in the fairness of user communications.

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references

SERGHIOU D, KHALILY M, BROWN T W C, et al . Terahertz channel propagation phenomena, measurement techniques and modeling for 6G wireless communication applications: a survey, open challenges and future research directions[J ] . IEEE Communications Surveys Tutorials, 2022, 24(4): 1957-1996.

PIVOTO D G S, REZENDE T T, FACINA M S P, et al . A detailed relevance analysis of enabling technologies for 6G architectures[J ] . IEEE Access, 2023, 11: 89644-89684.

QI Q, CHEN X, KHALILI A, et al . Integrating sensing, computing, and communication in 6G wireless networks: design and optimization[J ] . IEEE Transactions on Communications, 2022, 70(9): 6212-6227.

LIU A, HUANG Z, LI M, et al . A survey on fundamental limits of integrated sensing and communic ation[J ] . IEEE Communications Surveys Tutorials, 2022, 24(2): 994-1034.

DAI L, WANG B, WANG M, et al . Reconfigurable intelligent surface-based wireless communications: antenna design, prototyping, and experimental results[J ] . IEEE Access, 2020, 8: 45913-45923.

SHAFI M, JHA R K, JAIN S. 6G: technology evolution in future wireless networks[J]. IEEE Access, 2024, 12: 57548-57573.

WU J R, CUI M, ZHANG G C, et al . RIS-Assisted secure communication in non-orthogonal multiple access systems[J ] . Journal of Guangdong University of Technology, 2022, 39(3): 49-54.

LE W Y, CUI M, ZHANG G C. Throughput optimization for IRS-assisted cognitive SWIPT secondary user networks[J]. Journal of Guangdong University of Technology, 2024, 41(3): 119-130.

LUO H, LIU R, LI M, et al . Joint beamforming design for RIS-assisted integrated sensing and communication systems[J ] . IEEE Transactions on Vehicular Technology, 2022, 71(12): 13393-13397.

WANG X, FEI Z, HUANG J, et al . Joint waveform and discrete phase shift design for RIS-assisted integrated sensing and communication system under Cramer-Rao bound constraint[J ] . IEEE Transactions on Vehicular Technology, 2021, 71(1): 1004-1009.

LUO H, LIU R, LI M, et al . RIS-aided integrated sensing and communication: joint beamforming and reflection design[J ] . IEEE Transactions on Vehicular Technology, 2023, 72(7): 9626-9630.

MAO Y, DIZDAR O, CLERCKX B, et al . Rate-splitting multiple access: fundamentals, survey, and future research trends[J ] . IEEE Communications Surveys Tutorials, 2022, 24(4): 2073-2126.

CLERCKX B, MAO Y, JORSWIECK E A, et al . A primer on rate-splitting multiple access: tutorial, myths, and frequently asked questions[J ] . IEEE Journal on Selected Areas in Communications, 2023, 41(5): 1265-1308.

YIN L, MAO Y, DIZDAR O, et al . Rate-splitting multiple access for 6G—Part II: interplay with integrated sensing and communications[J ] . IEEE Communications Letters, 2022, 26(10): 2237-2241.

XU C, CLERCKX B, CHEN S, et al . Rate-splitting multiple access for multi-antenna joint radar and communications[J ] . IEEE Journal of Selected Topics in Signal Processing, 2021, 15(6): 1332-1347.

GAO P, LIAN L, YU J. Cooperative ISAC with direct localization and rate-splitting multiple access communication: a pareto optimization framework[J]. IEEE Journal on Selected Areas in Communications, 2023, 41(5): 1496-1515.

ZHANG R, XIONG K, LU Y, et al . Energy efficiency maximization in RIS-assisted SWIPT networks with RSMA: a PPO-based approach[J ] . IEEE Journal on Selected Areas in Communications, 2023, 41(5): 1413-1430.

PALA S, KATWE M, SINGH K, et al . Spectral-efficient RIS-aided RSMA URLLC: toward mobile broadband reliable low latency communication (mBRLLC) system[J ] . IEEE Transactions on Wireless Communications, 2023, 23(4): 3507-3524.

ZHANG G C, GU Z L, CUI M. Joint trajectory and resource allocation optimization for air-ground collaborative integrated sensing and communication systems[J]. Journal of Electronics and Information Technology, 2024, 46(6): 2382-2390.

MENG K, WU Q, MA S, et al . Throughput maximization for UAV-enabled integrated periodic sensing and communication[J ] . IEEE Transactions on Wireless Communications, 2022, 22(1): 671-687.

LI B, CHEN W, LI Z, et al . Robust weighted sum-rate maximization for t ransmissive RIS transmitter enabled RSMA networks[J ] . IEEE Communications Letters, 2023, 27(10): 2847-2851.

YANG Z, ZHANG Y. Beamforming optimization for RIS-aided SWIPT in cell-free MIMO networks[J]. China Communications, 2021, 18(9): 175-191.

PAN C, REN H, WANG K, et al . Multicell MIMO communications relying on intelligent reflecting surfaces[J ] . IEEE Transactions on Wireless Communications, 2020, 19(8): 5218-5233.

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