Narrowband interference parameterization for sparse Bayesian recovery

Anum Ali, Hesham Elsawy, Tareq Y. Al-Naffouri, Mohamed-Slim Alouini

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

2 Scopus citations

Abstract

This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Communications (ICC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages4530-4535
Number of pages6
ISBN (Print)9781467364324
DOIs
StatePublished - Sep 11 2015

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