Joint link learning and cognitive radio sensing

Seung Jun Kim, Nitin Jain, Georgios B. Giannakis, Pedro A. Forero

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

14 Scopus citations

Abstract

Novel cooperative spectrum sensing algorithms for cognitive radios (CRs) are developed, which can blindly learn the channel gains between CRs and licensed primary users (PUs), while jointly detecting active PU transmitters at each time instant. A dictionary learning approach is taken to decompose the received signal energy samples per CR into linear combinations of channel gains and PU transmit-powers, up to scaling ambiguity. In addition to a batch baseline algorithm, an efficient online implementation that can track slow variation of channel gains is developed, as well as a distributed alternative, which requires only local message passing among neighbors in CR networks. Numerical tests verify the proposed design.

Original languageEnglish (US)
Title of host publicationConference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Pages1415-1419
Number of pages5
DOIs
StatePublished - Dec 1 2011
Event45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 - Pacific Grove, CA, United States
Duration: Nov 6 2011Nov 9 2011

Publication series

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

Other

Other45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
CountryUnited States
CityPacific Grove, CA
Period11/6/1111/9/11

Fingerprint Dive into the research topics of 'Joint link learning and cognitive radio sensing'. Together they form a unique fingerprint.

Cite this