Opportunistic scheduling revisited using restless bandits: Indexability and index policy

Kehao Wang, Jihong Yu, Lin Chen, Moe Win

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

Abstract

We investigate the opportunistic scheduling problem where a server opportunistically serves multiple classes of users under time varying multi-state Markovian channels. The aim of the server is to find an optimal policy minimizing the average waiting cost of users. Mathematically, the problem can be cast to a restless bandit one, and a pivot to solve restless bandit by index policy is to establish indexability. We mathematically propose a set of sufficient conditions on channel state transition matrix, and consequently, the index policy is feasible. Our work consists of a small step toward solving the opportunistic scheduling problem in its generic form involving multi-state Markovian channels and multi-class users.

Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
Volume2018-January
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
Duration: 4 Dec 20178 Dec 2017

Keywords

  • Indexability
  • Performance evaluation
  • Restless bandit
  • Stochastic scheduling

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