Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks

A. Gouissem, R. Hamila, N. Aldhahir, Sebti Foufou

Research output: Contribution to journalArticle

Abstract

Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection techniques are proposed in this paper to increase the expected signal to interference and noise ratio based on full or partial knowledge of the channel state information (CSI). We also show that Distributed selection techniques provide all the SUs equal chances to be selected without affecting the selection diversity gain. General as well as simplified outage probability expressions are derived and extensive simulations are conducted to evaluate the performance of the proposed techniques and support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free limit over practical ranges of NBI power levels.

Original languageEnglish (US)
Pages (from-to)97-115
Number of pages19
JournalComputer Communications
Volume123
DOIs
StatePublished - Jun 1 2018

Fingerprint

Cognitive radio
Channel state information
Outages
Orthogonal frequency division multiplexing
Recovery

Keywords

  • Cognitive network
  • Compressive sensing
  • Interference mitigation
  • Narrow-band interference
  • OFDM
  • Sparsity

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks. / Gouissem, A.; Hamila, R.; Aldhahir, N.; Foufou, Sebti.

In: Computer Communications, Vol. 123, 01.06.2018, p. 97-115.

Research output: Contribution to journalArticle

@article{35b381101e164e1ea8cabffdbf790fb5,
title = "Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks",
abstract = "Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection techniques are proposed in this paper to increase the expected signal to interference and noise ratio based on full or partial knowledge of the channel state information (CSI). We also show that Distributed selection techniques provide all the SUs equal chances to be selected without affecting the selection diversity gain. General as well as simplified outage probability expressions are derived and extensive simulations are conducted to evaluate the performance of the proposed techniques and support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free limit over practical ranges of NBI power levels.",
keywords = "Cognitive network, Compressive sensing, Interference mitigation, Narrow-band interference, OFDM, Sparsity",
author = "A. Gouissem and R. Hamila and N. Aldhahir and Sebti Foufou",
year = "2018",
month = "6",
day = "1",
doi = "10.1016/j.comcom.2018.02.020",
language = "English (US)",
volume = "123",
pages = "97--115",
journal = "Computer Communications",
issn = "0140-3664",
publisher = "Elsevier",

}

TY - JOUR

T1 - Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks

AU - Gouissem, A.

AU - Hamila, R.

AU - Aldhahir, N.

AU - Foufou, Sebti

PY - 2018/6/1

Y1 - 2018/6/1

N2 - Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection techniques are proposed in this paper to increase the expected signal to interference and noise ratio based on full or partial knowledge of the channel state information (CSI). We also show that Distributed selection techniques provide all the SUs equal chances to be selected without affecting the selection diversity gain. General as well as simplified outage probability expressions are derived and extensive simulations are conducted to evaluate the performance of the proposed techniques and support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free limit over practical ranges of NBI power levels.

AB - Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection techniques are proposed in this paper to increase the expected signal to interference and noise ratio based on full or partial knowledge of the channel state information (CSI). We also show that Distributed selection techniques provide all the SUs equal chances to be selected without affecting the selection diversity gain. General as well as simplified outage probability expressions are derived and extensive simulations are conducted to evaluate the performance of the proposed techniques and support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free limit over practical ranges of NBI power levels.

KW - Cognitive network

KW - Compressive sensing

KW - Interference mitigation

KW - Narrow-band interference

KW - OFDM

KW - Sparsity

UR - http://www.scopus.com/inward/record.url?scp=85045711940&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85045711940&partnerID=8YFLogxK

U2 - 10.1016/j.comcom.2018.02.020

DO - 10.1016/j.comcom.2018.02.020

M3 - Article

AN - SCOPUS:85045711940

VL - 123

SP - 97

EP - 115

JO - Computer Communications

JF - Computer Communications

SN - 0140-3664

ER -