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Deterministic Identification Over Poisson Channels

Authors :
Salariseddigh, Mohammad J.
Pereg, Uzi
Boche, Holger
Deppe, Christian
Schober, Robert
Publication Year :
2021

Abstract

Deterministic identification (DI) for the discrete-time Poisson channel, subject to an average and a peak power constraint, is considered. It is established that the code size scales as $2^{(n\log n)R}$, where $n$ and $R$ are the block length and coding rate, respectively. The authors have recently shown a similar property for Gaussian channels [1]. Lower and upper bounds on the DI capacity of the Poisson channel are developed in this scale. Those imply that the DI capacity is infinite in the exponential scale, regardless of the dark current, i.e., the channel noise parameter.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2107.06061
Document Type :
Working Paper