{"title":"稳健节能的 RIS 辅助多天线 DF 中继合作 MIMO","authors":"Shunwai Zhang;Lulu Song;Rongfang Song","doi":"10.1109/TNSM.2024.3436942","DOIUrl":null,"url":null,"abstract":"We consider a robust energy-efficient reconfigurable intelligent surface (RIS)-aided multi-antenna decode-and-forward (DF) relay cooperative multiple-input multiple-output (MIMO). Although RIS and relay share some similarities in common, they have fundamental differences and can indeed complement each other. Due to the passive characteristic of RIS, it is much challenging to obtain the perfect channel state information (CSI) and the channel estimation error (CEE) is inevitable in practice. Taking into account the imperfect CSI, we formulate the robust energy efficiency (EE) optimization problems under the bounded CEE and statistical CEE models, where the precoding matrices at the source and relay, and the passive beamforming at the RIS in two slots are jointly designed. At first, the original problems under two CEE models are transformed into deterministic forms with the help of S-procedure and Bernstein-type Inequality, respectively. Subsequently, the reformulated problems are solved by the alternating optimization (AO)-based Dinkelbach algorithm in an iterative manner. Particularly, for the passive beamforming subproblem, the semi-definite relaxation (SDR) method and penalty concave-convex procedure (PCCP) method are utilized to deal with the rank-one constraint. Numerical simulations demonstrate that the EE performance of the considered scheme obviously outperforms the benchmarks. Simulation results also show the superiorities of the robust EE optimization compared with the non-robust optimization.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 5","pages":"5063-5075"},"PeriodicalIF":4.7000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust Energy-Efficient RIS-Aided Multi-Antenna DF Relay Cooperative MIMO\",\"authors\":\"Shunwai Zhang;Lulu Song;Rongfang Song\",\"doi\":\"10.1109/TNSM.2024.3436942\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider a robust energy-efficient reconfigurable intelligent surface (RIS)-aided multi-antenna decode-and-forward (DF) relay cooperative multiple-input multiple-output (MIMO). Although RIS and relay share some similarities in common, they have fundamental differences and can indeed complement each other. Due to the passive characteristic of RIS, it is much challenging to obtain the perfect channel state information (CSI) and the channel estimation error (CEE) is inevitable in practice. Taking into account the imperfect CSI, we formulate the robust energy efficiency (EE) optimization problems under the bounded CEE and statistical CEE models, where the precoding matrices at the source and relay, and the passive beamforming at the RIS in two slots are jointly designed. At first, the original problems under two CEE models are transformed into deterministic forms with the help of S-procedure and Bernstein-type Inequality, respectively. Subsequently, the reformulated problems are solved by the alternating optimization (AO)-based Dinkelbach algorithm in an iterative manner. Particularly, for the passive beamforming subproblem, the semi-definite relaxation (SDR) method and penalty concave-convex procedure (PCCP) method are utilized to deal with the rank-one constraint. Numerical simulations demonstrate that the EE performance of the considered scheme obviously outperforms the benchmarks. 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引用次数: 0
摘要
我们考虑的是一种稳健的高能效可重构智能表面(RIS)辅助多天线解码前向(DF)中继合作多输入多输出(MIMO)。尽管可重构智能表面和中继有一些共同之处,但它们也有本质区别,而且确实可以相互补充。由于 RIS 的被动特性,要获得完美的信道状态信息(CSI)非常困难,信道估计误差(CEE)在实际应用中不可避免。考虑到不完美的 CSI,我们提出了有界 CEE 模型和统计 CEE 模型下的鲁棒能效(EE)优化问题,其中源端和中继端的预编码矩阵以及两个时隙内 RIS 的无源波束成形是共同设计的。首先,借助 S 过程和伯恩斯坦式不等式,分别将两种 CEE 模型下的原始问题转化为确定性问题。随后,采用基于交替优化(AO)的丁克尔巴赫算法,以迭代的方式解决重新表述的问题。特别是在无源波束成形子问题中,采用了半有限松弛(SDR)方法和惩罚凹凸过程(PCCP)方法来处理秩一约束。数值模拟表明,所考虑方案的 EE 性能明显优于基准方案。仿真结果还显示了鲁棒 EE 优化与非鲁棒优化相比的优越性。
Robust Energy-Efficient RIS-Aided Multi-Antenna DF Relay Cooperative MIMO
We consider a robust energy-efficient reconfigurable intelligent surface (RIS)-aided multi-antenna decode-and-forward (DF) relay cooperative multiple-input multiple-output (MIMO). Although RIS and relay share some similarities in common, they have fundamental differences and can indeed complement each other. Due to the passive characteristic of RIS, it is much challenging to obtain the perfect channel state information (CSI) and the channel estimation error (CEE) is inevitable in practice. Taking into account the imperfect CSI, we formulate the robust energy efficiency (EE) optimization problems under the bounded CEE and statistical CEE models, where the precoding matrices at the source and relay, and the passive beamforming at the RIS in two slots are jointly designed. At first, the original problems under two CEE models are transformed into deterministic forms with the help of S-procedure and Bernstein-type Inequality, respectively. Subsequently, the reformulated problems are solved by the alternating optimization (AO)-based Dinkelbach algorithm in an iterative manner. Particularly, for the passive beamforming subproblem, the semi-definite relaxation (SDR) method and penalty concave-convex procedure (PCCP) method are utilized to deal with the rank-one constraint. Numerical simulations demonstrate that the EE performance of the considered scheme obviously outperforms the benchmarks. Simulation results also show the superiorities of the robust EE optimization compared with the non-robust optimization.
期刊介绍:
IEEE Transactions on Network and Service Management will publish (online only) peerreviewed archival quality papers that advance the state-of-the-art and practical applications of network and service management. Theoretical research contributions (presenting new concepts and techniques) and applied contributions (reporting on experiences and experiments with actual systems) will be encouraged. These transactions will focus on the key technical issues related to: Management Models, Architectures and Frameworks; Service Provisioning, Reliability and Quality Assurance; Management Functions; Enabling Technologies; Information and Communication Models; Policies; Applications and Case Studies; Emerging Technologies and Standards.