English

Poisson Noise Channel with Dark Current: Numerical Computation of the Optimal Input Distribution

Information Theory 2021-11-23 v1 math.IT

Abstract

This paper considers a discrete time-Poisson noise channel which is used to model pulse-amplitude modulated optical communication with a direct-detection receiver. The goal of this paper is to obtain insights into the capacity and the structure of the capacity-achieving distribution for the channel under the amplitude constraint A\mathsf{A} and in the presence of dark current λ\lambda. Using recent theoretical progress on the structure of the capacity-achieving distribution, this paper develops a numerical algorithm, based on the gradient ascent and Blahut-Arimoto algorithms, for computing the capacity and the capacity-achieving distribution. The algorithm is used to perform extensive numerical simulations for various regimes of A\mathsf{A} and λ\lambda.

Keywords

Cite

@article{arxiv.2111.11371,
  title  = {Poisson Noise Channel with Dark Current: Numerical Computation of the Optimal Input Distribution},
  author = {Luca Barletta and Alex Dytso},
  journal= {arXiv preprint arXiv:2111.11371},
  year   = {2021}
}

Comments

Submitted to IEEE ICC 2022. This is a companion paper of: A. Dytso, L. Barletta and S. Shamai Shitz, "Properties of the Support of the Capacity-Achieving Distribution of the Amplitude-Constrained Poisson Noise Channel," in IEEE Transactions on Information Theory, vol. 67, no. 11, pp. 7050-7066, Nov. 2021