{"title":"具有不完全CSI和相位误差的空间相关ris辅助MIMO系统的中断约束传输优化","authors":"Meng Gao;Yang Wang;Huafu Li;Junqi Guo","doi":"10.1109/TGCN.2024.3432111","DOIUrl":null,"url":null,"abstract":"It is practically challenging to achieve perfect channel state information (CSI) and ideal reconfigurable intelligent surface (RIS) hardware for the transmission design of RIS-assisted multiple-input multiple-output (MIMO) systems. To address this issue, incorporating phase errors, spatial correlation, and imperfect CSI into a unified outage-constrained beamforming optimization framework can be extended from i.i.d. Rician model to correlated Rician model. Subsequently, the outage constrained power minimizing problem is first transformed into a convex problem through Bernstein-type inequality method. Then, precoder and reflection beamforming are iteratively optimized under the alternate optimization (AO) framework. Especially, the scheme adopts semidefinite relaxation (SDR) technology and element iteration method to optimize the passive beamforming and achieve better performance than Gaussian randomization scheme. The simulation results demonstrate the effectiveness of the proposed scheme in two models. Compared to i.i.d. model, which is more sensitive to CSI errors, correlated model can provide more robust QoS guarantees for large CSI uncertainty sets. Phase errors undermine transmission power under the two models, especially in the i.i.d. model. Further, deploying more RIS elements can effectively improve the transmission power. Ultimately, the proposed approach has the potential to improve transmission robustness in practical scenarios.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"658-669"},"PeriodicalIF":5.3000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Outage Constrained Transmit Optimization for Spatially Correlated RIS-Aided MIMO Systems With Imperfect CSI and Phase Errors\",\"authors\":\"Meng Gao;Yang Wang;Huafu Li;Junqi Guo\",\"doi\":\"10.1109/TGCN.2024.3432111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is practically challenging to achieve perfect channel state information (CSI) and ideal reconfigurable intelligent surface (RIS) hardware for the transmission design of RIS-assisted multiple-input multiple-output (MIMO) systems. To address this issue, incorporating phase errors, spatial correlation, and imperfect CSI into a unified outage-constrained beamforming optimization framework can be extended from i.i.d. Rician model to correlated Rician model. Subsequently, the outage constrained power minimizing problem is first transformed into a convex problem through Bernstein-type inequality method. Then, precoder and reflection beamforming are iteratively optimized under the alternate optimization (AO) framework. Especially, the scheme adopts semidefinite relaxation (SDR) technology and element iteration method to optimize the passive beamforming and achieve better performance than Gaussian randomization scheme. The simulation results demonstrate the effectiveness of the proposed scheme in two models. Compared to i.i.d. model, which is more sensitive to CSI errors, correlated model can provide more robust QoS guarantees for large CSI uncertainty sets. Phase errors undermine transmission power under the two models, especially in the i.i.d. model. Further, deploying more RIS elements can effectively improve the transmission power. Ultimately, the proposed approach has the potential to improve transmission robustness in practical scenarios.\",\"PeriodicalId\":13052,\"journal\":{\"name\":\"IEEE Transactions on Green Communications and Networking\",\"volume\":\"9 2\",\"pages\":\"658-669\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Green Communications and Networking\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10611741/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Green Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10611741/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Outage Constrained Transmit Optimization for Spatially Correlated RIS-Aided MIMO Systems With Imperfect CSI and Phase Errors
It is practically challenging to achieve perfect channel state information (CSI) and ideal reconfigurable intelligent surface (RIS) hardware for the transmission design of RIS-assisted multiple-input multiple-output (MIMO) systems. To address this issue, incorporating phase errors, spatial correlation, and imperfect CSI into a unified outage-constrained beamforming optimization framework can be extended from i.i.d. Rician model to correlated Rician model. Subsequently, the outage constrained power minimizing problem is first transformed into a convex problem through Bernstein-type inequality method. Then, precoder and reflection beamforming are iteratively optimized under the alternate optimization (AO) framework. Especially, the scheme adopts semidefinite relaxation (SDR) technology and element iteration method to optimize the passive beamforming and achieve better performance than Gaussian randomization scheme. The simulation results demonstrate the effectiveness of the proposed scheme in two models. Compared to i.i.d. model, which is more sensitive to CSI errors, correlated model can provide more robust QoS guarantees for large CSI uncertainty sets. Phase errors undermine transmission power under the two models, especially in the i.i.d. model. Further, deploying more RIS elements can effectively improve the transmission power. Ultimately, the proposed approach has the potential to improve transmission robustness in practical scenarios.