Spectrum management for proactive video caching in information-centric cognitive radio networks

Pengbo Si*, Hao Yue, Yanhua Zhang, Yuguang Fang

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

39 Citations (Scopus)

Abstract

To deal with the rapid growth of mobile data traffic and the user interest shift from peer-to-peer communications to content dissemination-based services, such as video streaming, information-centric networking has emerged as a promising architecture and has been increasingly used for wireless and mobile networks. In this paper, we focus on video dissemination in information-centric cognitive radio networks (IC-CRNs) and investigate the use of harvested bands for proactively caching video contents at the locations close to the interested users to improve the performance of video distribution. With consideration of the dynamic and unobservable nature of some parameters, we formulate the allocation of harvested bands as a Markov decision process with hidden and dynamic parameters and transform it into a partially observable Markov decision process and a multi-armed bandit formulation. Based on them, we develop a new spectrum management mechanism, which maximizes the benefit of proactive video caching as well as the efficiency of spectrum utilization in the IC-CRNs. Extensive simulation results demonstrate the significant performance improvement of the proposed scheme for video streaming.
Original languageEnglish
Article number7485888
Pages (from-to)2247-2259
JournalIEEE Journal on Selected Areas in Communications
Volume34
Issue number8
DOIs
Publication statusPublished - 1 Aug 2016
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • cognitive radio
  • information-centric network
  • spectrum management
  • Video streaming

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