Distributed learning algorithms for spectrum sharing in spatial random access networks

Kobi Cohen, Angelia Nedic, R. Srikant

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

Abstract

We consider distributed optimization over orthogonal collision channels in spatial multi-channel ALOHA networks. Users are spatially distributed and each user is in the interference range of a few other users. Each user is allowed to transmit over a subset of the shared channels with a certain attempt probability. We study both the non-cooperative and cooperative settings. In the former, the goal of each user is to maximize its own rate irrespective of the utilities of other users. In the latter, the goal is to achieve proportionally fair rates among users. We develop simple distributed learning algorithms to solve these problems. The efficiencies of the proposed algorithms are demonstrated via both theoretical analysis and simulation results.

Original languageEnglish (US)
Title of host publication2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages513-520
Number of pages8
ISBN (Electronic)9783901882746
DOIs
StatePublished - Jul 6 2015
Event2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015 - Mumbai, India
Duration: May 25 2015May 29 2015

Publication series

Name2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015

Other

Other2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
Country/TerritoryIndia
CityMumbai
Period5/25/155/29/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Optimization
  • Modeling and Simulation

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