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TITLE:
Load Balancing Multi-Player MAB Approaches for RIS-Aided mmWave User Association - imarina:9293317

URV's Author/s:Abdelnasser Mohamed Mahmoud, Mohamed
Author, as appears in the article.:Mohamed, EM; Hashima, S; Hatano, K; Takimoto, E; Abdel-Nasser, M
Author's mail:mohamed.abdelnasser@urv.cat
Author identifier:0000-0002-1074-2441
Journal publication year:2023
Publication Type:Journal Publications
APA:Mohamed, EM; Hashima, S; Hatano, K; Takimoto, E; Abdel-Nasser, M (2023). Load Balancing Multi-Player MAB Approaches for RIS-Aided mmWave User Association. Ieee Access, 11(), 15816-15830. DOI: 10.1109/access.2023.3244781
Papper original source:Ieee Access. 11 15816-15830
Abstract:In this paper, multiple reconfigurable intelligent surface (RIS) boards are deployed to enhance millimeter wave (mmWave) communication in a harsh blockage environment, where mmWave line-of-sight (LoS) link is completely blocked. Herein, RIS-user association should be considered to maximize the users' achievable data rate while assuring load balance among the installed RIS panels. However, maximum received power (MRP) based RIS-user association will overload some of the RIS boards while keeping others unloaded, which causes RIS load to unbalance and decreases the users' achievable data rate. Instead, in this paper, an online learning methodology using centralized multi-player multi-armed bandit (MP-MAB) with arms' load balancing is proposed. In this formulation, mmWave users, RIS boards, and achievable users' rates act as the bandit game players, arms, and rewards. During the MAB game, the users learn how to avoid associating with the heavily loaded RIS boards, maximizing their achievable data rates, and balancing the RIS loads. Three centralized MP-MAB algorithms with arms' load balancing are proposed from the family of upper confidence bound (UCB) MAB algorithms. These algorithms are UCB1, Kullback-Leibler divergence UCB (KLUCB), and Minimax optimal stochastic strategy (MOSS) with arms' load balancing, i.e., UCB1-LB, KLUCB-LB, and MOSS-LB. Numerical analysis ensures the superior performance of the proposed algorithms over MRP-based RIS-user association and other benchmarks.
Article's DOI:10.1109/access.2023.3244781
Link to the original source:https://ieeexplore.ieee.org/document/10044086
Papper version:info:eu-repo/semantics/publishedVersion
licence for use:https://creativecommons.org/licenses/by/3.0/es/
Department:Enginyeria Electrònica, Elèctrica i Automàtica
Licence document URL:https://repositori.urv.cat/ca/proteccio-de-dades/
Thematic Areas:Telecommunications
Materials science (miscellaneous)
Materials science (all)
General materials science
General engineering
General computer science
Engineering, electrical & electronic
Engineering (miscellaneous)
Engineering (all)
Engenharias iv
Engenharias iii
Electrical and electronic engineering
Computer science, information systems
Computer science (miscellaneous)
Computer science (all)
Ciência da computação
Keywords:User association
Reconfigurable intelligent surface
Multi-armed bandit
Millimeter wave communication
Millimeter wave
Intelligent surfaces
wireless communication
user association
tuning
transmission
robust
reconfigurable intelligent surface
performance analysis
optimization
multi-armed bandit problem
multi-armed bandit
millimeter wave
load management
games
design
channel estimation
array signal processing
Entity:Universitat Rovira i Virgili
Record's date:2024-08-03
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