{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:49:27Z","timestamp":1774450167987,"version":"3.50.1"},"reference-count":37,"publisher":"Institution of Engineering and Technology (IET)","issue":"1","license":[{"start":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T00:00:00Z","timestamp":1766707200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["ietresearch.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["IET Communications"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Reconfigurable intelligent surface (RIS) holds potential for enhancing spectral efficiency (SE) and energy efficiency (EE). Nevertheless, the variations in these two metrics are not synchronous. Additionally, acquiring precise channel state information (CSI) presents substantial difficulties in actual implementations. In this work, an RIS\u2010aided multi\u2010user network with imperfect CSI is investigated. Correspondingly, we focus on balancing SE and EE through the collaborative design of the base station (BS)'s precoding matrix and the RIS's phase shifts, which consider the transmit power budget and the channel uncertainties constraints. The non\u2010convexity of the joint optimization problem motivates the use of two\u2010stage AO, which decouples the problem into tractable subproblems for BS beamforming and RIS phase\u2010shift design, ensuring convergence to a locally optimal solution. In the outer\u2010stage problem, the quadratic transformation (QT) method is applied to convert the fractional objective into a linear form. By introducing auxiliary variables, a closed\u2010form solution is obtained. In the inner\u2010stage problem, by employing successive convex approximation (SCA), introducing auxiliary variables, and utilizing S\u2010procedure, the SE with uncertain channels is transformed into a concave form and further converted into equivalent linear matrix inequalities (LMIs). Simulation results illustrate that the proposed design effectively attains a favorable tradeoff in both SE and EE, and demonstrate certain superiority compared to the\u00a0baseline.<\/jats:p>","DOI":"10.1049\/cmu2.70122","type":"journal-article","created":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T09:01:52Z","timestamp":1766739712000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Robust Spectral and Energy Efficiency Tradeoff for RIS\u2010Aided Multi\u2010User Communication"],"prefix":"10.1049","volume":"20","author":[{"given":"Xiandeng","family":"He","sequence":"first","affiliation":[{"name":"School of Telecommunications Engineering Xidian University Xi'an P. R. China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4980-0911","authenticated-orcid":false,"given":"Yilin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Telecommunications Engineering Xidian University Xi'an P. R. China"}]},{"given":"Shun","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Telecommunications Engineering Xidian University Xi'an P. R. China"}]}],"member":"265","published-online":{"date-parts":[[2025,12,26]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.001.1900287"},{"issue":"9","key":"e_1_2_10_3_1","doi-asserted-by":"crossref","first-page":"3794","DOI":"10.1109\/TCOMM.2017.2715170","article-title":"Spectral and Energy Efficiency of Multi\u2010pair Massive MIMO Relay Network with Hybrid Processing","volume":"65","author":"Xu W.","year":"2017","journal-title":"IEEE Transactions on Communications"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2021.3051897"},{"issue":"7","key":"e_1_2_10_5_1","doi-asserted-by":"crossref","first-page":"4300","DOI":"10.1109\/TCOMM.2023.3270907","article-title":"Energy Consumption Optimization in RIS\u2010Assisted Cooperative RSMA Cellular Networks","volume":"71","author":"Khisa S.","year":"2023","journal-title":"IEEE Transactions on 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Non\u2010Linear Energy Harvesting Model","volume":"70","author":"Zargari S.","year":"2021","journal-title":"IEEE Transactions on Vehicular Technology"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3098632"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3000835"},{"issue":"12","key":"e_1_2_10_18_1","doi-asserted-by":"crossref","first-page":"2263","DOI":"10.1109\/LWC.2023.3318212","article-title":"Deep Reinforcement Learning\u2010Based Downlink Beamforming and Phase Optimization for RIS\u2010Aided Communication System","volume":"12","author":"Li L.","year":"2023","journal-title":"IEEE Wireless Communications Letters"},{"issue":"4","key":"e_1_2_10_19_1","doi-asserted-by":"crossref","first-page":"5424","DOI":"10.1109\/TVT.2022.3224926","article-title":"Energy\u2010Efficient Design for a NOMA Assisted STAR\u2010RIS Network With Deep Reinforcement Learning","volume":"72","author":"Guo Y.","year":"2023","journal-title":"IEEE 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