Optimal Channel Selection in Hybrid RF/VLC Networks: A Multi-Armed Bandit Approach

Mostafa M. Fouda, Sherief Hashima, Sadman Sakib, Zubair Md Fadlullah, Kohei Hatano, Xuemin Shen

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

We investigate optimal band/channel selection in hybrid radio frequency and visible light communication (RF/VLC) networks. Particularly, we first develop a robust hybrid RF/VLC based system model for the optimal band/channel selection. We then formulate it as an online stochastic budget-constrained multi-armed bandit (MAB) problem. Two online learning algorithms based on different optimal policies are proposed to choose the appropriate band, i.e., energy-aware band selection with upper confidence bound (EABS-UCB) and energy-aware band selection with Thompson sampling (EABS-TS). The cost/budget is the battery consumption of the transmitting device according to the selected band. Through extensive simulations, it is confirmed that the proposed EABS-TS emerges as the superior technique compared with the random, brute-force, and EABS-UCB band selection schemes, in terms of energy efficiency, average throughput, and convergence performance.

Original languageEnglish
Pages (from-to)6853-6858
Number of pages6
JournalIEEE Transactions on Vehicular Technology
Volume71
Issue number6
DOIs
Publication statusPublished - Jun 1 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Optimal Channel Selection in Hybrid RF/VLC Networks: A Multi-Armed Bandit Approach'. Together they form a unique fingerprint.

Cite this