Cognitive radio spectrum prediction using dictionary learning

Seung Jun Kim, Georgios B Giannakis

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

24 Scopus citations

Abstract

Spatio-temporal spectrum prediction algorithms for cognitive radios (CRs) are developed using the framework of dictionary learning and compressive sensing. The interference power levels at each CR node locations are predicted using the measurements from a subset of CR nodes without a priori knowledge on the primary transmitters. Batch and online alternatives are presented, where the online algorithm features low complexity and memory requirements. Numerical tests verify the performance of the proposed novel methods.

Original languageEnglish (US)
Title of host publication2013 IEEE Global Communications Conference, GLOBECOM 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3206-3211
Number of pages6
ISBN (Print)9781479913534
DOIs
StatePublished - Jan 1 2013
Event2013 IEEE Global Communications Conference, GLOBECOM 2013 - Atlanta, GA, United States
Duration: Dec 9 2013Dec 13 2013

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference

Other

Other2013 IEEE Global Communications Conference, GLOBECOM 2013
Country/TerritoryUnited States
CityAtlanta, GA
Period12/9/1312/13/13

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