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相关论文: Cost-Efficient RIS-Aided Channel Estimation via Ra…

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To achieve the more significant passive beamforming gain in the double-intelligent reflecting surface (IRS) aided system over the conventional single-IRS counterpart, channel state information (CSI) is indispensable in practice but also…

信息论 · 计算机科学 2021-03-12 Beixiong Zheng , Changsheng You , Rui Zhang

The performance of transmission schemes is heavily influenced by the wireless channel, which is typically considered an uncontrollable factor. However, the introduction of reconfigurable intelligent surfaces (RISs) to wireless…

信息论 · 计算机科学 2023-05-05 Weicong Chen , Chao-Kai Wen , Xiao Li , Shi Jin

The deployment of multiple reconfigurable intelligent surfaces (RISs) enhances the propagation environment by improving channel quality, but it also complicates channel estimation. Following the conventional wireless communication system…

信息论 · 计算机科学 2024-11-22 Weicong Chen , Yu Han , Chao-Kai Wen , Xiao Li , Shi Jin

Due to the passive nature of Intelligent Reflecting Surface (IRS), channel estimation is a fundamental challenge in IRS-aided wireless networks. Particularly, as the number of IRS reflecting elements and/or that of IRS-served users…

信息论 · 计算机科学 2020-08-04 Xinrong Guan , Qingqing Wu , Rui Zhang

Intelligent reflecting surfaces (IRSs) are promising enablers for next-generation wireless communications due to their reconfigurability and high energy efficiency in improving poor propagation condition of channels, e.g., limited…

信息论 · 计算机科学 2022-01-03 Xin Zhang , Xianghao Yu , S. H. Song , Khaled B. Letaief

The increasing demand for high data rates and seamless connectivity in wireless systems has sparked significant interest in reconfigurable intelligent surfaces (RIS) and artificial intelligence-based wireless applications. RIS typically…

The channel estimation overhead of reconfigurable intelligent surface (RIS) assisted communication systems can be prohibitive. Prior works have demonstrated via simulations that grouping neighbouring RIS elements can help to reduce the…

信息论 · 计算机科学 2021-11-23 Neel Kanth Kundu , Zan Li , Junhui Rao , Shanpu Shen , Matthew R. McKay , Ross Murch

The accurate estimation of Channel State Information (CSI) is of crucial importance for the successful operation of Multiple-Input Multiple-Output (MIMO) communication systems, especially in a Multi-User (MU) time-varying environment and…

The fluid antenna concept represents shape-flexible and position-flexible antenna technologies designed to enhance wireless communication applications. In this paper, we apply this concept to reconfigurable intelligent surfaces (RISs),…

信号处理 · 电气工程与系统科学 2025-02-25 Abdelhamid Salem , Kai-Kit Wong , George Alexandropoulos , Chan-Byoung Chae , Ross Murch

Reconfigurable intelligent surface (RIS) is considered a prospective technology for beyond fifth-generation (5G) networks to improve the spectral and energy efficiency at a low cost. Prior works on the RIS mainly rely on perfect channel…

信号处理 · 电气工程与系统科学 2023-09-11 Sadaf Syed , Dominik Semmler , Donia Ben Amor , Michael Joham , Wolfgang Utschick

This paper presents a physics-based channel modeling and optimization framework for reconfigurable intelligent surface (RIS)-assisted downlink multi-user multiple-input single-output (MU-MISO) communication systems in site-specific…

信号处理 · 电气工程与系统科学 2026-03-24 Ziqi Liu , Wei Yu , Sean Victor Hum

In this paper, we consider channel estimation for intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) systems, where an IRS is deployed to assist the data transmission from the base station (BS) to a user. It is shown…

信号处理 · 电气工程与系统科学 2020-07-15 Peilan Wang , Jun Fang , Huiping Duan , Hongbin Li

Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology to enhance the performance of sixth-generation (6G) and beyond communication systems. The passive nature of RISs and their large number of reflecting elements…

A reconfigurable intelligent surface (RIS) reflects incoming signals in different ways depending on the phase-shift pattern assigned to its elements. The most promising use case is to aid the communication between a base station and a user…

信息论 · 计算机科学 2022-12-06 Emil Björnson , Parisa Ramezani

We develop an optimal version of a prior two-stage channel estimation protocol for RIS-assisted channels. The new design uses a modified DFT matrix (MDFT) for the training phases at the RIS and is shown to minimize the total channel…

信息论 · 计算机科学 2022-10-19 Chelsea L. Miller , Peter J. Smith , Pawel A. Dmochowski

Reconfigurable intelligent surface (RIS) is a newly-emerged technology that, with its unique features, is considered to be a game changer for future wireless networks. Channel estimation is one of the most critical challenges for the…

信号处理 · 电气工程与系统科学 2023-03-30 Mehdi Haghshenas , Parisa Ramezani , Emil Björnson

In this paper, we adopt a three-stage based uplink channel estimation protocol with reduced pilot overhead for an reconfigurable intelligent surface (RIS)-aided multi-user (MU) millimeter wave (mmWave) communication system, in which both…

信号处理 · 电气工程与系统科学 2023-04-18 Zhendong Peng , Gui Zhou , Cunhua Pan , Hong Ren , A. Lee Swindlehurst , Petar Popovski , Gang Wu

Reconfigurable intelligent surfaces (RIS)-assisted massive multiple-input multiple-output (mMIMO) is a promising technology for applications in next-generation networks. However, reflecting-only RIS provides limited coverage compared to a…

Reconfigurable intelligent surface (RIS) is a promising technology to enhance the spectral efficiency of wireless communication systems. By optimizing the RIS elements, the performance of the overall system can be improved. Yet, in contrast…

信息论 · 计算机科学 2023-10-13 Mohammad Soleymani , Ignacio Santamaria , Aydin Sezgin , Eduard Jorswieck

This paper studies wideband channel estimation for OFDM systems assisted by extremely large RIS (XL-RIS). Due to the large aperture of XL-RISs, the user equipment may operate in the near-field region, while the base station-XL-RIS link…

信号处理 · 电气工程与系统科学 2026-03-24 Lanqing Zhi , Hongwei Wang , Lingxiang Li , Zhi Chen