Advanced MAB Schemes for WiGig-Aided Aerial Mounted RIS Wireless Networks

Sherief Hashima, Kohei Hatano, Ehab Mahmoud Mohamed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper uses an aerial mounted RIS (A-RIS) to assist WiGig base station (BS) in serving mobile equipments (MEs) located within hotspot zones. The aerial should cover numerous large-capacity hotspots in this context while anticipating its flying/hovering energy expenditures. Hence, two advanced multi armed bandit (MAB) approaches, i.e. perturbed history exploration (PHE) and mini-max optimal Thompson sampling (MOTS), are envisioned as applicable self-learning methodologies to deal with such a problem effectively. Simulation results ensure the excellent performance of the envisioned schemes over naive upper confidence bound (UCB) and Thompson sampling (TS) algorithms and traditional heuristic solutions.

Original languageEnglish
Title of host publication2023 IEEE 20th Consumer Communications and Networking Conference, CCNC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages469-472
Number of pages4
ISBN (Electronic)9781665497343
DOIs
Publication statusPublished - 2023
Event20th IEEE Consumer Communications and Networking Conference, CCNC 2023 - Las Vegas, United States
Duration: Jan 8 2023Jan 11 2023

Publication series

NameProceedings - IEEE Consumer Communications and Networking Conference, CCNC
Volume2023-January
ISSN (Print)2331-9860

Conference

Conference20th IEEE Consumer Communications and Networking Conference, CCNC 2023
Country/TerritoryUnited States
CityLas Vegas
Period1/8/231/11/23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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