Compressed channel sensing

Waheed U. Bajwa, Jarvis Haupt, Gil Raz, Robert Nowak

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

165 Scopus citations

Abstract

Reliable wireless communications often requires accurate knowledge of the underlying multipath channel. This typically involves probing of the channel with a known training waveform and linear processing of the input probe and channel output to estimate the impulse response. Many real-world channels of practical interest tend to exhibit impulse responses characterized by a relatively small number of nonzero channel coefficients. Conventional linear channel estimation strategies, such as the least squares, are ill-suited to fully exploiting the inherent low-dimensionality of these sparse channels. In contrast, this paper proposes sparse channel estimation methods based on convex/linear programming. Quantitative error bounds for the proposed schemes are derived by adapting recent advances from the theory of compressed sensing. The bounds come within a logarithmic factor of the performance of an ideal channel estimator and reveal significant advantages of the proposed methods over the conventional channel estimation schemes.

Original languageEnglish (US)
Title of host publicationCISS 2008, The 42nd Annual Conference on Information Sciences and Systems
Pages5-10
Number of pages6
DOIs
StatePublished - Sep 22 2008
EventCISS 2008, 42nd Annual Conference on Information Sciences and Systems - Princeton, NJ, United States
Duration: Mar 19 2008Mar 21 2008

Publication series

NameCISS 2008, The 42nd Annual Conference on Information Sciences and Systems

Other

OtherCISS 2008, 42nd Annual Conference on Information Sciences and Systems
Country/TerritoryUnited States
CityPrinceton, NJ
Period3/19/083/21/08

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