Author, as appears in the article.: Mohamed, Ehab Mahmoud; Hashima, Sherief; Hatano, Kohei; Takimoto, Eiji; Abdel-Nasser, Mohamed
Department: Enginyeria Electrònica, Elèctrica i Automàtica
URV's Author/s: Abdelnasser Mohamed Mahmoud, Mohamed
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
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.
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
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: mohamed.abdelnasser@urv.cat
Author identifier: 0000-0002-1074-2441
Record's date: 2024-10-12
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://ieeexplore.ieee.org/document/10044086
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Ieee Access. 11 15816-15830
APA: Mohamed, Ehab Mahmoud; Hashima, Sherief; Hatano, Kohei; Takimoto, Eiji; Abdel-Nasser, Mohamed (2023). Load Balancing Multi-Player MAB Approaches for RIS-Aided mmWave User Association. Ieee Access, 11(), 15816-15830. DOI: 10.1109/access.2023.3244781
Article's DOI: 10.1109/access.2023.3244781
Entity: Universitat Rovira i Virgili
Journal publication year: 2023
Publication Type: Journal Publications
Repositori URV