1. Deterministic Identification Over Poisson Channels
- Author
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Salariseddigh, Mohammad J., Pereg, Uzi, Boche, Holger, Deppe, Christian, and Schober, Robert
- Subjects
Computer Science - Information Theory - 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.
- Published
- 2021