Sparsity aware dynamic distributed compressive spectrum sensing and scheduling

Nicolo Michelusi, Urbashi Mitra

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

Abstract

A cross-layer framework for resource constrained dynamic distributed spectrum sensing and scheduling is presented. A network of secondary users (SUs) opportunistically communicate over portions of the spectrum estimated to be unused by other systems. A central controller (CC) schedules the traffic of the SUs, based on distributed compressed measurements collected by the SUs. Sensing and access are jointly controlled to maximize the SU throughput, with constraints on PU throughput degradation and SU cost. Sparsity in the network dynamics is exploited: leveraging a prior spectrum occupancy estimate, the CC needs to estimate only a residual uncertainty vector via sparse recovery techniques. The trade-off between achieving accurate spectrum estimates, high throughput, and low state information overhead, is optimized via dynamic programming.

Original languageEnglish (US)
Title of host publicationConference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1109-1113
Number of pages5
ISBN (Electronic)9781467385763
DOIs
StatePublished - Feb 26 2016
Externally publishedYes
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 8 2015Nov 11 2015

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2016-February
ISSN (Print)1058-6393

Other

Other49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/8/1511/11/15

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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