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For memoryless channels with continuous input alphabets, deterministic identification (DI) typically exhibits a linearithmic ($n\log n$) message growth. However, the exact DI capacity has long remained open due to a persistent gap between…

Information Theory · Computer Science 2026-05-07 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter

Deterministic identification offers an efficient solution for scenarios where decoding entire messages is unnecessary. It is commonly used in alarm systems and control systems. A key advantage of this approach is that the capacity for…

Information Theory · Computer Science 2025-01-23 Holger Boche , Christian Deppe , Safieh Mahmoodi , Golamreza Omidi

The identification capacity is developed without randomization at neither the encoder nor the decoder. In particular, full characterization is established for the deterministic identification (DI) capacity for the Gaussian channel and for…

Information Theory · Computer Science 2021-10-11 Mohammad J. Salariseddigh , Uzi Pereg , Holger Boche , Christian Deppe

Deterministic identification (DI) is addressed for Gaussian channels with fast and slow fading, where channel side information is available at the decoder. In particular, it is established that the number of messages scales as…

Information Theory · Computer Science 2021-10-12 Mohammad J. Salariseddigh , Uzi Pereg , Holger Boche , Christian Deppe

We extend the recent analysis of the rate-reliability tradeoff in deterministic identification (DI) to general linear Gaussian channels, marking the first such analysis for channels with continuous output. Because DI provides a framework…

Information Theory · Computer Science 2026-02-13 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter

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…

Information Theory · Computer Science 2021-09-29 Mohammad J. Salariseddigh , Uzi Pereg , Holger Boche , Christian Deppe , Robert Schober

Following initial work by JaJa, Ahlswede and Cai, and inspired by a recent renewed surge in interest in deterministic identification (DI) via noisy channels, we consider the problem in its generality for memoryless channels with finite…

Information Theory · Computer Science 2025-03-28 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter

We establish lower and upper bounds for the identification capacity of discrete-time Gaussian channels subject to inter-symbol interference (ISI), a canonical model in wireless communication. Our analysis accounts for deterministic encoders…

Information Theory · Computer Science 2026-05-04 Mohammad Javad Salariseddigh , Christian Deppe

Many communication applications incorporate event-triggered behavior, where the conventional Shannon capacity may not effectively gauge performance. Consequently, we advocate for the concept of identification capacity as a more suitable…

Information Theory · Computer Science 2025-02-04 Ilya Vorobyev , Christian Deppe , Holger Boche

In our previous work, we presented the \emph{Hypothesis Testing Lemma}, a key tool that establishes sufficient conditions for the existence of good deterministic identification (DI) codes for memoryless channels with finite output, but…

Information Theory · Computer Science 2025-07-25 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter

Identification capacities of randomized and deterministic identification were proved to exceed channel capacity for Gaussian channels \emph{with} channel side information (CSI). In this work, we extend deterministic identification to the…

Information Theory · Computer Science 2022-08-12 Yuan Li , Xianbin Wang , Huazi Zhang , Jun Wang , Wen Tong , Guiying Yan , Zhiming Ma

Several applications of molecular communications (MC) feature an alarm-prompt behavior for which the prevalent Shannon capacity may not be the appropriate performance metric. The identification capacity as an alternative measure for such…

Information Theory · Computer Science 2022-12-07 Mohammad Javad Salariseddigh , Vahid Jamali , Uzi Pereg , Holger Boche , Christian Deppe , Robert Schober

Deterministic $K$-identification (DKI) is addressed for Gaussian channels with slow fading (GSF), where the transmitter is restricted to an average power constraint and channel side information is available at the decoder. We derive lower…

Information Theory · Computer Science 2022-12-09 Mohammad Javad Salariseddigh , Muris Spahovic , Christian Deppe

Deterministic identification over K-input multiple-access channels with average input cost constraints is considered. The capacity region for deterministic identification is determined for an average-error criterion, where arbitrarily large…

Information Theory · Computer Science 2023-06-21 Johannes Rosenberger , Abdalla Ibrahim , Christian Deppe , Roberto Ferrara

Recently, Etkin, Tse, and Wang found the capacity region of the two-user Gaussian interference channel to within one bit/s/Hz. A natural goal is to apply this approach to the Gaussian interference channel with an arbitrary number of users.…

Information Theory · Computer Science 2016-11-17 Guy Bresler , Abhay Parekh , David Tse

The problem of identifying the channel with the highest capacity among several discrete memoryless channels (DMCs) is considered. The problem is cast as a pure-exploration multi-armed bandit problem, which follows the practical use of…

Information Theory · Computer Science 2024-01-19 Maximilian Egger , Rawad Bitar , Antonia Wachter-Zeh , Deniz Gündüz , Nir Weinberger

The capacity of a deterministic multiple-input multiple-output (MIMO) channel under the peak and average power constraints is investigated. For the identity channel matrix, the approach of Shamai et al. is generalized to the higher…

Information Theory · Computer Science 2016-09-29 Borzoo Rassouli , Bruno Clerckx

This paper explores the two-user Gaussian interference channel through the lens of a natural deterministic channel model. The main result is that the deterministic channel uniformly approximates the Gaussian channel, the capacity regions…

Information Theory · Computer Science 2008-07-22 Guy Bresler , David Tse

Various applications of molecular communications (MC) are event-triggered, and, as a consequence, the prevalent Shannon capacity may not be the right measure for performance assessment. Thus, in this paper, we motivate and establish the…

Information Theory · Computer Science 2022-03-08 Mohammad Javad Salariseddigh , Uzi Pereg , Holger Boche , Christian Deppe , Vahid Jamali , Robert Schober

Computing capacity of Gaussian Interference Channel (GIC) is complex since knowledge of input distributions is needed to find the mutual information terms in closed forms, which should be optimized over input distributions and associated…

Information Theory · Computer Science 2020-12-09 Amir K. Khandani
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