Name
Title | ||
|---|---|---|
Poisson Noise Channel with Dark Current: Numerical Computation of the Optimal Input Distribution |
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 $\mathsf{A}$ and in the presence of dark current $\lambda$. 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 $\mathsf{A}$ and $\lambda$. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ICC45855.2022.9838555 | IEEE International Conference on Communications (ICC) |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luca Barletta | 1 | 58 | 11.42 |
| Alex Dytso | 2 | 45 | 20.03 |