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Line spectrum estimation from broadband power detection bits
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2013 (English)In: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, 2013, 405-409 p.Conference paper (Refereed)
Abstract [en]

Line spectrum estimation from analog signal samples is a classic problem with numerous applications. However, sending analog or finely quantized signal sample streams to a fusion center is a burden in distributed sensing scenarios. Instead, it is appealing to estimate the frequency lines from a few randomly filtered broadband power measurement bits taken using a network of cheap sensors. This leads to a new problem: line spectrum estimation from inequalities. Three different techniques are proposed for this estimation task. In the first two, the autocorrelation function is first estimated nonparametrically, then a parametric method is used to estimate the sought frequencies. The third is a direct maximum likelihood (ML) parameter estimation approach that uses coordinate descent. Simulations show that the underlying frequencies can be accurately estimated using the proposed techniques, even from relatively few bits; and that the ML estimates obtained with the third technique can meet the Cramer-Rao lower bound (also derived here), when the number of sensors is sufficiently large.

Place, publisher, year, edition, pages
2013. 405-409 p.
Keyword [en]
cognitive radio, Distributed spectrum sensing, line spectrum estimation, spectral analysis, Autocorrelation functions, Coordinate descent, Cramer Rao lower bound, Distributed sensing, Line spectra, Parametric method, Spectrum sensing, Three different techniques, Cramer-Rao bounds, Estimation, Sensors, Signal processing, Wireless telecommunication systems, Spectrum analysis
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-140024DOI: 10.1109/SPAWC.2013.6612081ScopusID: 2-s2.0-84885813044ISBN: 9781467355773OAI: diva2:689770
2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2013, 16 June 2013 through 19 June 2013, Darmstadt

QC 20140121

Available from: 2014-01-21 Created: 2014-01-16 Last updated: 2014-01-21Bibliographically approved

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Tsakonas, Efthymios
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Signal ProcessingACCESS Linnaeus Centre
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