Minimax Optimal Stochastic Strategy (MOSS) for Neighbor Discovery and Selection in Millimeter Wave D2D Networks

Sherief Hashima, Kohei Hatano, Eiji Takimoto, Ehab Mahmoud Mohamed

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

1 Citation (Scopus)

Abstract

The millimeter-waves (mmWaves) features promote its soon employment in device to device (D2D) communications. In D2D, neighbor discovery and selection (NDS) problem is a critical one due to the tradeoff between exploring more devices for the best choice and the expected beamforming training (BT) overhead. In this paper, mmWave D2D neighbor discovery and selection (NDS) problem is modeled as a budget-constrained multiarmed bandit (MAB). Specifically, an energy constrained minimax optimal stochastic strategy (E-MOSS) algorithm is proposed, which reflects the real network scenario by counting the remaining battery levels of the neighboring devices. Simulation results prove the efficiency of the proposed E-MOSS algorithm over the traditional NDS arrangements regards network lifetime, convergence rate, energy performance, and average throughput. Index Terms - MOSS, mmWave, D2D, Multiarmed Bandit (MAB).

Original languageEnglish
Title of host publicationWPMC 2020 - 23rd International Symposium on Wireless Personal Multimedia Communications
Subtitle of host publicationBridging Wireless and Business Worlds
PublisherIEEE Computer Society
ISBN (Electronic)9781728182964
DOIs
Publication statusPublished - Oct 19 2020
Event23rd International Symposium on Wireless Personal Multimedia Communications, WPMC 2020 - Virtual, Okayama, Japan
Duration: Oct 19 2020Oct 26 2020

Publication series

NameInternational Symposium on Wireless Personal Multimedia Communications, WPMC
Volume2020-October
ISSN (Print)1347-6890

Conference

Conference23rd International Symposium on Wireless Personal Multimedia Communications, WPMC 2020
CountryJapan
CityVirtual, Okayama
Period10/19/2010/26/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Human-Computer Interaction

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