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dc.contributor.authorSoltani, Morteza
dc.contributor.authorRezki, Zouheir
dc.date.accessioned2021-04-15T09:05:18Z
dc.date.available2021-04-15T09:05:18Z
dc.date.issued2021-01-11
dc.identifier.urihttp://hdl.handle.net/10754/668792
dc.description.abstractThis paper addresses the degraded discrete-time Poisson wiretap channel (DT--PWC) in an optical wireless communication system based on intensity modulation and direct detection. Subject to nonnegativity, peak- and average-intensity as well as bandwidth constraints, we study the secrecy-capacity-achieving input distribution of this wiretap channel and prove it to be unique and discrete with a finite number of mass points; one of them located at the origin. Furthermore, we establish that every point on the boundary of the rate-equivocation region of this wiretap channel is also obtained by a unique and discrete input distribution with finitely many mass points. In general, the number of mass points of the optimal distributions is greater than two. This is in contrast with the degraded continuous-time PWC when the signaling bandwidth is not restricted and where the secrecy capacity and the entire boundary of the rate-equivocation region are achieved by binary distributions. Furthermore, we extend our analysis to the case where only an average-intensity constraint is active. For this case, we find that the secrecy capacity and the entire boundary of the rate-equivocation region are attained by discrete distributions with countably \textit{infinite} number of mass points, but with finitely many mass points in any bounded interval.
dc.description.sponsorshipThis work has been supported by the King Abdullah University of Science and Technology (KAUST).
dc.publisherarXiv
dc.relation.urlhttps://arxiv.org/pdf/2101.03650.pdf
dc.rightsArchived with thanks to arXiv
dc.titleThe Degraded Discrete-Time Poisson Wiretap Channel
dc.typePreprint
dc.eprint.versionPre-print
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Idaho, Moscow, Idaho, USA.
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of California Santa Cruz, CA, USA.
dc.identifier.arxivid2101.03650
kaust.grant.numberOSR-2016-CRG5-2958-01.
refterms.dateFOA2021-04-15T09:06:15Z
kaust.acknowledged.supportUnitCRG


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