Narrowband interference parameterization for sparse Bayesian recovery

Handle URI:
http://hdl.handle.net/10754/621281
Title:
Narrowband interference parameterization for sparse Bayesian recovery
Authors:
Ali, Anum; Elsawy, Hesham ( 0000-0003-4201-6126 ) ; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
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.
KAUST Department:
King Abdullah University of Science and Technology (KAUST), Makkah Province, Thuwal, Saudi Arabia
Citation:
Ali A, Elsawy H, Al-Naffouri TY, Alouini M-S (2015) Narrowband interference parameterization for sparse Bayesian recovery. 2015 IEEE International Conference on Communications (ICC). Available: http://dx.doi.org/10.1109/ICC.2015.7249036.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 IEEE International Conference on Communications (ICC)
Conference/Event name:
IEEE International Conference on Communications, ICC 2015
Issue Date:
11-Sep-2015
DOI:
10.1109/ICC.2015.7249036
Type:
Conference Paper
Appears in Collections:
Conference Papers

Full metadata record

DC FieldValue Language
dc.contributor.authorAli, Anumen
dc.contributor.authorElsawy, Heshamen
dc.contributor.authorAl-Naffouri, Tareq Y.en
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2016-11-03T06:56:45Z-
dc.date.available2016-11-03T06:56:45Z-
dc.date.issued2015-09-11en
dc.identifier.citationAli A, Elsawy H, Al-Naffouri TY, Alouini M-S (2015) Narrowband interference parameterization for sparse Bayesian recovery. 2015 IEEE International Conference on Communications (ICC). Available: http://dx.doi.org/10.1109/ICC.2015.7249036.en
dc.identifier.doi10.1109/ICC.2015.7249036en
dc.identifier.urihttp://hdl.handle.net/10754/621281-
dc.description.abstractThis 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.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectBayesian sparse recoveryen
dc.subjectcompressed sensingen
dc.subjectNarrowband interferenceen
dc.subjectSC-FDMAen
dc.subjectstochastic geometryen
dc.titleNarrowband interference parameterization for sparse Bayesian recoveryen
dc.typeConference Paperen
dc.contributor.departmentKing Abdullah University of Science and Technology (KAUST), Makkah Province, Thuwal, Saudi Arabiaen
dc.identifier.journal2015 IEEE International Conference on Communications (ICC)en
dc.conference.date8 June 2015 through 12 June 2015en
dc.conference.nameIEEE International Conference on Communications, ICC 2015en
dc.contributor.institutionKing Fahd University of Petroleum and Minerals (KFUPM), Eastern Province, Dhahran, Saudi Arabiaen
kaust.authorAli, Anumen
kaust.authorElsawy, Heshamen
kaust.authorAl-Naffouri, Tareq Y.en
kaust.authorAlouini, Mohamed-Slimen
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