Identification over Poisson ISI Channels: Feedback and Molecular Applications

Fuente: arXiv
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Main Authors: Zhao, Yaning, Colomer, Pau, Boche, Holger, Deppe, Christian
Format: Preprint
Published: 2025
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author Zhao, Yaning
Colomer, Pau
Boche, Holger
Deppe, Christian
author_facet Zhao, Yaning
Colomer, Pau
Boche, Holger
Deppe, Christian
contents Molecular communication (MC) enables information transfer via molecules, making it ideal for biomedical applications where traditional methods fall short. In many such scenarios, identifying specific events is more critical than decoding full messages, motivating the use of deterministic identification (DI). This paper investigates DI over discrete-time Poisson channels (DTPCs) with inter-symbol interference (ISI), a realistic setting due to channel memory effects. We improve the known upper bound on DI capacity under power constraints from $\frac{3}{2} + κ$ to $\frac{1 + κ}{2}$. Additionally, we present the first results on deterministic identification with feedback (DIF) in this context, providing a constructive lower bound. These findings enhance the theoretical understanding of MC and support more efficient, feedback-driven biomedical systems.
format Preprint
id arxiv_https___arxiv_org_abs_2504_20550
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Identification over Poisson ISI Channels: Feedback and Molecular Applications
Zhao, Yaning
Colomer, Pau
Boche, Holger
Deppe, Christian
Information Theory
Molecular communication (MC) enables information transfer via molecules, making it ideal for biomedical applications where traditional methods fall short. In many such scenarios, identifying specific events is more critical than decoding full messages, motivating the use of deterministic identification (DI). This paper investigates DI over discrete-time Poisson channels (DTPCs) with inter-symbol interference (ISI), a realistic setting due to channel memory effects. We improve the known upper bound on DI capacity under power constraints from $\frac{3}{2} + κ$ to $\frac{1 + κ}{2}$. Additionally, we present the first results on deterministic identification with feedback (DIF) in this context, providing a constructive lower bound. These findings enhance the theoretical understanding of MC and support more efficient, feedback-driven biomedical systems.
title Identification over Poisson ISI Channels: Feedback and Molecular Applications
topic Information Theory
url https://arxiv.org/abs/2504.20550