{"title":"Statistical CSI-based dual-hop hybrid RIS-assisted wireless communication","authors":"Shuang Liang, Guangliang Ren","doi":"10.1016/j.dsp.2025.105398","DOIUrl":null,"url":null,"abstract":"<div><div>Statistical channel state information (S-CSI) based ergodic achievable rate maximization is investigated for dual-hop hybrid reconfigurable intelligent surfaces (D-HRIS) assisted single-user wireless communication systems. A communication model, in which the transmitted signal is reflected through passive RIS (pRIS) to the active RIS (aRIS) and then reflected to the receiver via aRIS, is regarded as D-HRIS-assisted communication. The ergodic achievable rate is analyzed and its approximate expression is derived for this system. Based on the S-CSI, a low-complexity iterative updating scheme is proposed to design the precoding of the base station (BS) and the reflecting matrices of hybrid RISs (HRIS) to maximize the ergodic achievable rate. Specifically, the ergodic achievable rates of the proposal are 1.32 and 1.16 times larger than those of the dual-hop pRIS-aided scheme when the number of elements at the second-hop RIS is 20 and 100, respectively. When the Rician-K factor is larger than 0 dB, the ergodic achievable rate of the proposal is close to that of the instantaneous channel state information (I-CSI) based D-HRIS-assisted communication. And the performance of the system can still be guaranteed when RIS employs discrete phase shifters.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105398"},"PeriodicalIF":2.9000,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1051200425004208","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Statistical channel state information (S-CSI) based ergodic achievable rate maximization is investigated for dual-hop hybrid reconfigurable intelligent surfaces (D-HRIS) assisted single-user wireless communication systems. A communication model, in which the transmitted signal is reflected through passive RIS (pRIS) to the active RIS (aRIS) and then reflected to the receiver via aRIS, is regarded as D-HRIS-assisted communication. The ergodic achievable rate is analyzed and its approximate expression is derived for this system. Based on the S-CSI, a low-complexity iterative updating scheme is proposed to design the precoding of the base station (BS) and the reflecting matrices of hybrid RISs (HRIS) to maximize the ergodic achievable rate. Specifically, the ergodic achievable rates of the proposal are 1.32 and 1.16 times larger than those of the dual-hop pRIS-aided scheme when the number of elements at the second-hop RIS is 20 and 100, respectively. When the Rician-K factor is larger than 0 dB, the ergodic achievable rate of the proposal is close to that of the instantaneous channel state information (I-CSI) based D-HRIS-assisted communication. And the performance of the system can still be guaranteed when RIS employs discrete phase shifters.
期刊介绍:
Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal.
The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as:
• big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,