RIS-Aided Multiple-Input Multiple-Output Broadcast Channel Capacity

Scalable algorithms are conceived for obtaining the sum-rate capacity of the reconfigurable intelligent surface (RIS)-aided multiuser (MU) multiple-input multiple-output (MIMO) broadcast channel (BC), where a multi-antenna base station (BS) transmits signals to multi-antenna users with the help of a...

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Vydané v:IEEE transactions on communications Ročník 72; číslo 1; s. 1
Hlavní autori: Tuan, H. D., Nasir, A. A., Dutkiewicz, E., Poor, H. V., Hanzo, L.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.01.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Antennas
Beamforming
Channel capacity
Computational modeling
Information theory
Linear programming
MIMO communication
Minimax techniques
mixed discrete continuous optimization
Optimization
Optimized production technology
Reconfigurable intelligent surface (RIS )-aided communication
scalable algorithms
Sensors
sum capacity
ISSN:0090-6778, 1558-0857
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Shrnutí:Scalable algorithms are conceived for obtaining the sum-rate capacity of the reconfigurable intelligent surface (RIS)-aided multiuser (MU) multiple-input multiple-output (MIMO) broadcast channel (BC), where a multi-antenna base station (BS) transmits signals to multi-antenna users with the help of an RIS equipped with a massive number of finite-resolution programmable reflecting elements (PREs). As a byproduct, scalable path-following algorithms emerge for determining the sum-rate capacity of the conventional MIMO BCs, closing a long-standing open problem of information theory. The paper also develops scalable algorithms for maximizing the minimum rate (max-min rate optimization) of the users achieved by the joint design of RIS's PRE and transmit beamforming for such an RIS-aided BC. The simulations provided confirm the high performance achieved by the algorithms developed, despite their low computational complexity.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2023.3321909