Autor segons l'article: Mohamed, Ehab Mahmoud; Hashima, Sherief; Hatano, Kohei; Takimoto, Eiji; Abdel-Nasser, Mohamed
Departament: Enginyeria Electrònica, Elèctrica i Automàtica
Autor/s de la URV: Abdelnasser Mohamed Mahmoud, Mohamed
Paraules clau: 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
Resum: 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.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: mohamed.abdelnasser@urv.cat
Identificador de l'autor: 0000-0002-1074-2441
Data d'alta del registre: 2024-10-12
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Ieee Access. 11 15816-15830
Referència de l'ítem segons les normes 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
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2023
Tipus de publicació: Journal Publications
Repositori URV