Feature‐oriented channel estimation in reconfigurable intelligent surface‐assisted wireless communication systems. Issue 19 (6th November 2020)

• Record Type: Journal Article
• Authors: Lin, Junliang; Wang, Gongpu; Fan, Rongfei; Zou, Yulong; Tsiftsis, Theodoros A.; Tellambura, Chintha
• Is Part Of: IET communications. Volume 14:Issue 19(2020)
• Page Start: 3458
• Page End: 3463
• Publication Date: 2020-11-06
• Subjects: least squares approximations -- channel estimation -- minimisation -- iterative methods -- radiocommunication -- wireless channels; assistant channel -- constrained residual sum of squares minimisation problem -- dual ascent‐based estimation scheme -- estimation accuracy -- reconfigurable intelligent surface‐assisted wireless communication systems -- RIS -- feature‐oriented channel channel estimation problem -- efficient Lagrange multiplier -- iterative solution -- Cramér–Rao lower bounds -- performance benchmark -- conventional least‐square method -- low signal‐to‐noise ratio regime; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2020.0372
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this6study, the channel estimation problem is investigated for a wireless communication system assisted by a reconfigurable intelligent surface (RIS). The RIS thus creates an assistant channel, which has the features of positivity and dominance. Owing to these features, the channel estimation problem is formulated as a constrained residual sum of squares minimisation problem, which differs radically from the traditional channel estimation issue. An efficient Lagrange multiplier and dual ascent‐based estimation scheme is then designed to obtain an iterative solution for the estimator. Moreover, the Cramér–Rao lower bounds are deduced as a performance benchmark. Simulation results show that the authors' designed scheme improves the estimation accuracy up to 33%, compared with the conventional least‐square method in the low signal‐to‐noise ratio regime.