Line spectrum estimation from broadband power detection bits
2013 (English)In: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, 2013, 405-409 p.Conference paper (Refereed)
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.
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
IdentifiersURN: urn:nbn:se:kth:diva-140024DOI: 10.1109/SPAWC.2013.6612081ScopusID: 2-s2.0-84885813044ISBN: 9781467355773OAI: oai:DiVA.org:kth-140024DiVA: diva2:689770
2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2013, 16 June 2013 through 19 June 2013, Darmstadt
QC 201401212014-01-212014-01-162014-01-21Bibliographically approved