Title
Active Reconfigurable Intelligent Surface-Aided Wireless Communications
Abstract
Reconfigurable Intelligent Surface (RIS) is a promising solution to reconfigure the wireless environment in a controllable way. To compensate for the double-fading attenuation in the RIS-aided link, a large number of passive reflecting elements (REs) are conventionally deployed at the RIS, resulting in large surface size and considerable circuit power consumption. In this paper, we propose a new type of RIS, called active RIS, where each RE is assisted by active loads (negative resistance), that reflect and amplify the incident signal instead of only reflecting it with the adjustable phase shift as in the case of a passive RIS. Therefore, for a given power budget at the RIS, a strengthened RIS-aided link can be achieved by increasing the number of active REs as well as amplifying the incident signal. We consider the use of an active RIS to a single input multiple output (SIMO) system. However, it would unintentionally amplify the RIS-correlated noise, and thus the proposed system has to balance the conflict between the received signal power maximization and the RIS-correlated noise minimization at the receiver. To achieve this goal, it has to optimize the reflecting coefficient matrix at the RIS and the receive beamforming at the receiver. An alternating optimization algorithm is proposed to solve the problem. Specifically, the receive beamforming is obtained with a closed-form solution based on linear minimum-mean-square-error (MMSE) criterion, while the reflecting coefficient matrix is obtained by solving a series of sequential convex approximation (SCA) problems. Simulation results show that the proposed active RIS-aided system could achieve better performance over the conventional passive RIS-aided system with the same power budget.
Year
DOI
Venue
2021
10.1109/TWC.2021.3064024
IEEE Transactions on Wireless Communications
Keywords
DocType
Volume
Reconfigurable intelligent surface (RIS),active load,negative resistance,optimization
Journal
20
Issue
ISSN
Citations 
8
1536-1276
16
PageRank 
References 
Authors
0.57
0
4
Name
Order
Citations
PageRank
Ruizhe Long1392.37
Liang Ying-Chang210007593.03
Yiyang Pei360728.70
Erik G. Larsson410189605.81