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dc.contributor.authorArfaoui, Mohamed Amine
dc.contributor.authorZaid, Hajar
dc.contributor.authorRezki, Zouheir
dc.contributor.authorGhrayeb, Ali
dc.contributor.authorChaaban, Anas
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2019-03-11T07:08:25Z
dc.date.available2019-03-11T07:08:25Z
dc.date.issued2018-12-25
dc.identifier.citationArfaoui MA, Zaid H, Rezki Z, Ghrayeb A, Chaaban A, et al. (2018) Artificial Noise Based Beamforming for the MISO VLC Wiretap Channel. IEEE Transactions on Communications: 1–1. Available: http://dx.doi.org/10.1109/TCOMM.2018.2889649.
dc.identifier.issn0090-6778
dc.identifier.issn1558-0857
dc.identifier.doi10.1109/TCOMM.2018.2889649
dc.identifier.urihttp://hdl.handle.net/10754/631490
dc.description.abstractThis paper investigates the secrecy performance of the multiple-input single-output (MISO) visible light communication (VLC) wiretap channel. The considered system model comprises three nodes: a transmitter (Alice) equipped with multiple fixtures of LEDs, a legitimate receiver (Bob) and an eavesdropper (Eve), each equipped with one photo-diode (PD). The VLC channel is modeled as a real-valued amplitude-constrained Gaussian channel. Eve is assumed to be randomly located in the same area as Bob. Due to this, artificial noise (AN)-based beamforming is adopted as a transmission strategy in order to degrade Eve’s signal-to-noise ratio (SNR). Assuming discrete input signaling, we derive an achievable secrecy rate in a closed-form expression as a function of the beamforming vectors and the input distribution. We investigate the average secrecy performance of the system using stochastic geometry to account for the location randomness of Eve. We also adopt the truncated discrete generalized normal (TDGN) as a discrete input distribution. We present several examples through which we confirm the accuracy of the analytical results via Monte Carlo simulations. The results also demonstrate that the TDGN distribution, albeit being not optimal, yields performance close to the secrecy capacity.
dc.description.sponsorshipThis work was supported by Qatar National Research Fund (a member of Qatar Foundation) under NPRP Grant NPRP8-052-2-029. The statements made herein are solely the responsibility of the authors.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8589021
dc.rights(c) 2018 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.
dc.subjectAchievable secrecy rate
dc.subjectArray signal processing
dc.subjectbeamforming
dc.subjectLight emitting diodes
dc.subjectMISO
dc.subjectMISO communication
dc.subjectOptical distortion
dc.subjectOptical receivers
dc.subjectRadio frequency
dc.subjectstochastic geometry
dc.subjectTDGN
dc.subjectVLC
dc.titleArtificial Noise Based Beamforming for the MISO VLC Wiretap Channel
dc.typeArticle
dc.contributor.departmentCommunication Theory Lab
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journalIEEE Transactions on Communications
dc.eprint.versionPost-print
dc.contributor.institutionConcordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC H3G 1M8, Canada.
dc.contributor.institutionElectronics Computer and Telecommunications (ECT) department, National School of Applied Sciences (NSAC), Oujda, Maroc.
dc.contributor.institutionElectrical and Computer Engineering Department, University of Idaho, Moscow, ID 83844 USA.
dc.contributor.institutionElectrical and Computer Engineering Department, Texas A&M University at Qatar.
dc.contributor.institutionSchool of Engineering, The University of British Columbia, Kelowna, BC V1V 1V7, Canada.
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2019-03-11T14:30:02Z
dc.date.published-online2018-12-25
dc.date.published-print2019-04


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