Adaptive thresholding for distributed power spectrum sensing

Omar Mehanna, Nikolaos Sidiropoulos

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

4 Scopus citations

Abstract

Wideband spectrum sensing is an important prerequisite for cognitive radio access. A network sensing scenario comprising low-end sensors is considered, with each sensor reporting a single randomly filtered power measurement bit to the fusion center (FC), which estimates the ambient power spectrum from these bits. An adaptive thresholding algorithm is proposed to improve the quality and speed of power spectrum reconstruction. Upon receipt of each new bit, the FC picks the threshold for the next sensor so as to cut off a half-space from the feasible region along its Chebyshev center. Convergence of this algorithm to the true finite-length autocorrelation is shown, whose Fourier transform yields the power spectrum estimate. To avoid the 'downlink' threshold communication overhead, an alternative algorithm is proposed, where each sensor pseudo-randomly chooses its threshold from a suitable distribution, and the FC judiciously polls sensors to form its power spectrum estimate.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages4459-4463
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

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