Chengzhi Ma, Jintao Wang, Xi Yang, Guanghua Yang, Wei Zhang, Shaodan Ma
{"title":"RDARS Empowered Massive MIMO System: Two-Timescale Transceiver Design with Imperfect CSI","authors":"Chengzhi Ma, Jintao Wang, Xi Yang, Guanghua Yang, Wei Zhang, Shaodan Ma","doi":"arxiv-2312.08753","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate a novel reconfigurable distributed antennas and\nreflecting surface (RDARS) aided multi-user massive MIMO system with imperfect\nCSI and propose a practical two-timescale (TTS) transceiver design to reduce\nthe communication overhead and computational complexity of the system. In the\nRDARS-aided system, not only distribution gain but also reflection gain can be\nobtained by a flexible combination of the distributed antennas and reflecting\nsurface, which differentiates the system from the others and also makes the TTS\ndesign challenging. To enable the optimal TTS transceiver design, the\nachievable rate of the system is first derived in closed-form. Then the TTS\ndesign aiming at the weighted sum rate maximization is considered. To solve the\nchallenging non-convex optimization problem with high-order design variables,\ni.e., the transmit powers and the phase shifts at the RDARS, a block coordinate\ndescent based method is proposed to find the optimal solutions in semi-closed\nforms iteratively. Specifically, two efficient algorithms are proposed with\nprovable convergence for the optimal phase shift design, i.e., Riemannian\nGradient Ascent based algorithm by exploiting the unit-modulus constraints, and\nTwo-Tier Majorization-Minimization based algorithm with closed-form optimal\nsolutions in each iteration. Simulation results validate the effectiveness of\nthe proposed algorithm and demonstrate the superiority of deploying RDARS in\nmassive MIMO systems to provide substantial rate improvement with a\nsignificantly reduced total number of active antennas/RF chains and lower\ntransmit power when compared to the DAS and RIS-aided systems.","PeriodicalId":501433,"journal":{"name":"arXiv - CS - Information Theory","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Information Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2312.08753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we investigate a novel reconfigurable distributed antennas and
reflecting surface (RDARS) aided multi-user massive MIMO system with imperfect
CSI and propose a practical two-timescale (TTS) transceiver design to reduce
the communication overhead and computational complexity of the system. In the
RDARS-aided system, not only distribution gain but also reflection gain can be
obtained by a flexible combination of the distributed antennas and reflecting
surface, which differentiates the system from the others and also makes the TTS
design challenging. To enable the optimal TTS transceiver design, the
achievable rate of the system is first derived in closed-form. Then the TTS
design aiming at the weighted sum rate maximization is considered. To solve the
challenging non-convex optimization problem with high-order design variables,
i.e., the transmit powers and the phase shifts at the RDARS, a block coordinate
descent based method is proposed to find the optimal solutions in semi-closed
forms iteratively. Specifically, two efficient algorithms are proposed with
provable convergence for the optimal phase shift design, i.e., Riemannian
Gradient Ascent based algorithm by exploiting the unit-modulus constraints, and
Two-Tier Majorization-Minimization based algorithm with closed-form optimal
solutions in each iteration. Simulation results validate the effectiveness of
the proposed algorithm and demonstrate the superiority of deploying RDARS in
massive MIMO systems to provide substantial rate improvement with a
significantly reduced total number of active antennas/RF chains and lower
transmit power when compared to the DAS and RIS-aided systems.