RSMA-Enabled Aerial RIS-Aided MU-MIMO System for Improved Spectral-Efficient URLLC

This study explores a new resource allocation framework for a multi-user multiple-input and multiple-output (MU-MIMO) downlink system utilizing aerial reconfigurable intelligent surfaces (ARIS) in a rate-splitting multiple access (RSMA) scheme under ultra-reliable low-latency communication (URLLC)....

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Published inIEEE transactions on vehicular technology Vol. 74; no. 2; pp. 3110 - 3127
Main Authors Katwe, Mayur V., Deshpande, Rasika, Singh, Keshav, Ku, Meng-Lin, Clerckx, Bruno
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
active and passive beamforming
Algorithms
Array signal processing
Beamforming
Design optimization
downlink (DL) communication
Energy efficiency
MIMO communication
Multiaccess communication
Multiple access
multiple-input–multiple-output system
Network latency
NOMA
Particle swarm optimization
Rate-splitting multiple access (RSMA)
reconfigurable intelligent surface (RIS)
Reconfigurable intelligent surfaces
Reliability
Reliability engineering
Resource allocation
Resource management
Spectral efficiency
sum-rate maximization
Ultra reliable low latency communication
ultra-reliable low-latency communication (URLLC)
Online AccessGet full text
ISSN0018-9545
1939-9359
DOI10.1109/TVT.2024.3483449

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Abstract This study explores a new resource allocation framework for a multi-user multiple-input and multiple-output (MU-MIMO) downlink system utilizing aerial reconfigurable intelligent surfaces (ARIS) in a rate-splitting multiple access (RSMA) scheme under ultra-reliable low-latency communication (URLLC). The objective is to maximize the overall spectral efficiency of users located in severely blocked dead zones, where there is no direct link between the base station (BS) and the users and, the ARIS acts as a relay to facilitate communication. To achieve this, we formulate a sum-rate maximization problem considering the joint design of active beamforming at the BS, passive beamforming at the ARIS, and determination of the ARIS height. The constraints include given packet size and packet error probability (PEP) requirements. Since the original problem is non-convex, we propose an alternating optimization framework to solve it. The framework involves solving sub-problems of beamforming design and ARIS location alternately. The beamforming design sub-problem is addressed using successive convex approximation, while the ARIS location sub-problem is solved using a particle-swarm optimization (PSO) algorithm. The proposed solution demonstrates fast convergence within a few iterations, as validated through numerical simulations. Additionally, a computational complexity analysis is performed. The results show that the proposed RSMA scheme for the ARIS-aided DL URLLC system surpasses conventional multiple access schemes in terms of rate performance. The findings highlight the potential of utilizing ARIS and RSMA to enhance the spectral efficiency and meet the requirements of URLLC applications.
AbstractList This study explores a new resource allocation framework for a multi-user multiple-input and multiple-output (MU-MIMO) downlink system utilizing aerial reconfigurable intelligent surfaces (ARIS) in a rate-splitting multiple access (RSMA) scheme under ultra-reliable low-latency communication (URLLC). The objective is to maximize the overall spectral efficiency of users located in severely blocked dead zones, where there is no direct link between the base station (BS) and the users and, the ARIS acts as a relay to facilitate communication. To achieve this, we formulate a sum-rate maximization problem considering the joint design of active beamforming at the BS, passive beamforming at the ARIS, and determination of the ARIS height. The constraints include given packet size and packet error probability (PEP) requirements. Since the original problem is non-convex, we propose an alternating optimization framework to solve it. The framework involves solving sub-problems of beamforming design and ARIS location alternately. The beamforming design sub-problem is addressed using successive convex approximation, while the ARIS location sub-problem is solved using a particle-swarm optimization (PSO) algorithm. The proposed solution demonstrates fast convergence within a few iterations, as validated through numerical simulations. Additionally, a computational complexity analysis is performed. The results show that the proposed RSMA scheme for the ARIS-aided DL URLLC system surpasses conventional multiple access schemes in terms of rate performance. The findings highlight the potential of utilizing ARIS and RSMA to enhance the spectral efficiency and meet the requirements of URLLC applications.
Author Singh, Keshav
Clerckx, Bruno
Katwe, Mayur V.
Deshpande, Rasika
Ku, Meng-Lin
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  surname: Katwe
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Snippet This study explores a new resource allocation framework for a multi-user multiple-input and multiple-output (MU-MIMO) downlink system utilizing aerial...
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SubjectTerms active and passive beamforming
Algorithms
Array signal processing
Beamforming
Design optimization
downlink (DL) communication
Energy efficiency
MIMO communication
Multiaccess communication
Multiple access
multiple-input–multiple-output system
Network latency
NOMA
Particle swarm optimization
Rate-splitting multiple access (RSMA)
reconfigurable intelligent surface (RIS)
Reconfigurable intelligent surfaces
Reliability
Reliability engineering
Resource allocation
Resource management
Spectral efficiency
sum-rate maximization
Ultra reliable low latency communication
ultra-reliable low-latency communication (URLLC)
Title RSMA-Enabled Aerial RIS-Aided MU-MIMO System for Improved Spectral-Efficient URLLC
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