Narrowband interference parameterization for sparse Bayesian recovery

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

doi:10.1109/ICC.2015.7249036

Narrowband interference parameterization for sparse Bayesian recovery

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

King Fahd University of Petroleum & Minerals

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	2015 IEEE International Conference on Communications, ICC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4530-4535
Number of pages	6
ISBN (Electronic)	9781467364324
DOIs	https://doi.org/10.1109/ICC.2015.7249036
State	Published - 9 Sep 2015

Publication series

Name	IEEE International Conference on Communications
Volume	2015-September
ISSN (Print)	1550-3607

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Bayesian sparse recovery
Narrowband interference
SC-FDMA
compressed sensing
stochastic geometry

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering

Access to Document

10.1109/ICC.2015.7249036

Cite this

Ali, A., Elsawy, H., Al-Naffouri, T. Y., & Alouini, M. S. (2015). Narrowband interference parameterization for sparse Bayesian recovery. In 2015 IEEE International Conference on Communications, ICC 2015 (pp. 4530-4535). Article 7249036 (IEEE International Conference on Communications; Vol. 2015-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2015.7249036

@inproceedings{45b19647f1044fae85b00ceadb277108,

title = "Narrowband interference parameterization for sparse Bayesian recovery",

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.",

keywords = "Bayesian sparse recovery, Narrowband interference, SC-FDMA, compressed sensing, stochastic geometry",

author = "Anum Ali and Hesham Elsawy and Al-Naffouri, {Tareq Y.} and Alouini, {Mohamed Slim}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.",

year = "2015",

month = sep,

day = "9",

doi = "10.1109/ICC.2015.7249036",

language = "English",

series = "IEEE International Conference on Communications",

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Ali, A, Elsawy, H, Al-Naffouri, TY & Alouini, MS 2015, Narrowband interference parameterization for sparse Bayesian recovery. in 2015 IEEE International Conference on Communications, ICC 2015., 7249036, IEEE International Conference on Communications, vol. 2015-September, Institute of Electrical and Electronics Engineers Inc., pp. 4530-4535. https://doi.org/10.1109/ICC.2015.7249036

Narrowband interference parameterization for sparse Bayesian recovery. / Ali, Anum; Elsawy, Hesham; Al-Naffouri, Tareq Y. et al.
2015 IEEE International Conference on Communications, ICC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 4530-4535 7249036 (IEEE International Conference on Communications; Vol. 2015-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Narrowband interference parameterization for sparse Bayesian recovery

AU - Ali, Anum

AU - Elsawy, Hesham

AU - Al-Naffouri, Tareq Y.

AU - Alouini, Mohamed Slim

PY - 2015/9/9

Y1 - 2015/9/9

N2 - 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.

AB - 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.

KW - Bayesian sparse recovery

KW - Narrowband interference

KW - SC-FDMA

KW - compressed sensing

KW - stochastic geometry

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T3 - IEEE International Conference on Communications

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EP - 4535

BT - 2015 IEEE International Conference on Communications, ICC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Narrowband interference parameterization for sparse Bayesian recovery

Abstract

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Keywords

ASJC Scopus subject areas

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Cite this