Opportunistic Relay Selection in Multicast Relay Networks using Compressive Sensing

Handle URI:
http://hdl.handle.net/10754/348535
Title:
Opportunistic Relay Selection in Multicast Relay Networks using Compressive Sensing
Authors:
Elkhalil, Khalil ( 0000-0001-7656-3246 ) ; Eltayeb, Mohammed E; Shibli, Hussain; Bahrami, Hamid Reza; Al-Naffouri, Tareq Y.
Abstract:
Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. However, for relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. In this paper, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback. Following that, the CSI of the selected relays is estimated using linear minimum mean square error estimation. To minimize the effect of noise on the fed back CSI, we introduce a back-off strategy that optimally backs-off on the noisy estimated CSI. For a fixed group size, we provide closed form expressions for the scaling law of the maximum equivalent SNR for both Decode and Forward (DF) and Amplify and Forward (AF) cases. Numerical results show that the proposed algorithm drastically reduces the feedback air-time and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback channels.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Electrical Engineering Program
Publisher:
IEEE
Journal:
IEEE Globecom
Conference/Event name:
IEEE Globecom
Issue Date:
Dec-2014
DOI:
10.1109/GLOCOM.2014.7037286
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7037286
Appears in Collections:
Conference Papers; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorElkhalil, Khalilen
dc.contributor.authorEltayeb, Mohammed Een
dc.contributor.authorShibli, Hussainen
dc.contributor.authorBahrami, Hamid Rezaen
dc.contributor.authorAl-Naffouri, Tareq Y.en
dc.date.accessioned2015-04-06T08:10:01Zen
dc.date.available2015-04-06T08:10:01Zen
dc.date.issued2014-12en
dc.identifier.doi10.1109/GLOCOM.2014.7037286en
dc.identifier.urihttp://hdl.handle.net/10754/348535en
dc.description.abstractRelay selection is a simple technique that achieves spatial diversity in cooperative relay networks. However, for relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. In this paper, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback. Following that, the CSI of the selected relays is estimated using linear minimum mean square error estimation. To minimize the effect of noise on the fed back CSI, we introduce a back-off strategy that optimally backs-off on the noisy estimated CSI. For a fixed group size, we provide closed form expressions for the scaling law of the maximum equivalent SNR for both Decode and Forward (DF) and Amplify and Forward (AF) cases. Numerical results show that the proposed algorithm drastically reduces the feedback air-time and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback channels.en
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7037286en
dc.rights(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectRelay selectionen
dc.subjectMulticasten
dc.subjectFeedbacken
dc.subjectDecode and Forwarden
dc.subjectAmplify and Forwarden
dc.subjectCompressive Sensingen
dc.titleOpportunistic Relay Selection in Multicast Relay Networks using Compressive Sensingen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journalIEEE Globecomen
dc.conference.dateDecember 2014en
dc.conference.nameIEEE Globecomen
dc.conference.locationAustin Texasen
dc.eprint.versionPost-printen
dc.contributor.institutionDepartment of Electrical and Computer Engineering, The University of Akron, Ohio, USA.en
dc.contributor.institutionElectrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.en
kaust.authorElkhalil, Khalilen
kaust.authorShibli, Hussain J.en
kaust.authorAl-Naffouri, Tareq Y.en
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