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

Tuan, HD; Nasir, AA; Dutkiewicz, E; Poor, HV; Hanzo, L

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

Tuan, HD Nasir, AA Dutkiewicz, E

Poor, HV Hanzo, L

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Transactions on Communications, 2024, 72, (1), pp. 117-132
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Tuan, HD
dc.contributor.author	Nasir, AA
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286
dc.contributor.author	Poor, HV
dc.contributor.author	Hanzo, L
dc.date.accessioned	2024-04-16T02:17:22Z
dc.date.available	2024-04-16T02:17:22Z
dc.date.issued	2024-01-01
dc.identifier.citation	IEEE Transactions on Communications, 2024, 72, (1), pp. 117-132
dc.identifier.issn	0090-6778
dc.identifier.issn	1558-0857
dc.identifier.uri	http://hdl.handle.net/10453/177951
dc.description.abstract	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.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation	http://purl.org/au-research/grants/arc/DP190102501
dc.relation.ispartof	IEEE Transactions on Communications
dc.relation.isbasedon	10.1109/TCOMM.2023.3321909
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0804 Data Format, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	4006 Communications engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.subject.classification	4606 Distributed computing and systems software
dc.title	RIS-Aided Multiple-Input Multiple-Output Broadcast Channel Capacity
dc.type	Journal Article
utslib.citation.volume	72
utslib.for	0804 Data Format
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-04-16T02:17:20Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	72
utslib.citation.issue	1

Abstract:

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.

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http://hdl.handle.net/10453/177951