Improved Bounds on the Number of Support Points of the Capacity-Achieving Input for Amplitude Constrained Poisson Channels

Luca Barletta, Alex Dytso, Shlomo Shamai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This work considers a discrete-time Poisson noise channel with an input amplitude constraint A and a dark current parameter λ. It is known that the capacity-achieving distribution for this channel is discrete with finitely many points. Recently, for λ = 0, a lower bound of order √A and an upper bound of order Alog2(A) have been demonstrated on the cardinality of the support of the optimal input distribution. In this work, we improve these results in several ways. First, we provide upper and lower bounds that hold for non-zero dark current. Second, we produce a sharper upper bound with a far simpler technique. In particular, for λ = 0, we sharpen the upper bound from the order of Alog2(A) to the order of A. Finally, some other additional information about the location of the support is provided.

Original languageEnglish
Title of host publication2024 IEEE International Symposium on Information Theory, ISIT 2024 - Proceedings
Pages3630-3635
Number of pages6
ISBN (Electronic)9798350382846
DOIs
StatePublished - 2024
Event2024 IEEE International Symposium on Information Theory, ISIT 2024 - Athens, Greece
Duration: 7 Jul 202412 Jul 2024

Publication series

NameIEEE International Symposium on Information Theory - Proceedings

Conference

Conference2024 IEEE International Symposium on Information Theory, ISIT 2024
Country/TerritoryGreece
CityAthens
Period7/07/2412/07/24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

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