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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

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

Deterministic identification (DI) has emerged as a promising paradigm for large-scale and goal-oriented communication systems. Despite significant progress, a fundamental open problem has remained unresolved: a persistent gap between the…

Information Theory · Computer Science 2026-04-14 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

We analyze deterministic message identification via channels with non-discrete additive white noise and with a noiseless feedback link under both average power and peak power constraints. The identification task is part of Post Shannon…

Information Theory · Computer Science 2022-02-18 Moritz Wiese , Wafa Labidi , Christian Deppe , Holger Boche

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 region of the compound broadcast channel is determined under an average error criterion, where the sender has no channel state information. We give single-letter identification capacity formulas for discrete…

Information Theory · Computer Science 2021-12-03 Johannes Rosenberger , Uzi Pereg , Christian Deppe

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

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

Deterministic K-Identification (DKI) for the binary symmetric channel (BSC) is developed. A full characterization of the DKI capacity for such a channel, with and without the Hamming weight constraint, is established. As a key finding, we…

Information Theory · Computer Science 2023-05-09 Ons Dabbabi , Mohammad Javad Salariseddigh , Christian Deppe , Holger Boche

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

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

The problem of blind identification of channel codes at a receiver involves identifying a code chosen by a transmitter from a known code-family, by observing the transmitted codewords through the channel. Most existing approaches for…

Information Theory · Computer Science 2026-03-04 Pramod Singh , Prasad Krishnan , Arti Yardi

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

Numerous applications in the field of molecular communications (MC) such as healthcare systems are often event-driven. The conventional Shannon capacity may not be the appropriate metric for assessing performance in such cases. We propose…

Information Theory · Computer Science 2024-01-30 Wafa Labidi , Christian Deppe , Holger Boche

The capacity of a time-varying block-memoryless channel in which the transmitter and the receiver have access to (possibly different) noisy causal channel side information (CSI) is obtained. It is shown that the capacity formula obtained in…

Information Theory · Computer Science 2008-06-09 Hamid Farmanbar , Amir K. Khandani

This paper studies a layered erasure interference channel model, which is a simplification of the Gaussian interference channel with fading using the deterministic model approach. In particular, the capacity region of the layered erasure…

Information Theory · Computer Science 2009-09-08 Yan Zhu , Dongning Guo

We investigate deterministic identification over arbitrary memoryless channels under the constraint that the error probabilities of first and second kind are exponentially small in the block length $\mathbf{n}$, controlled by reliability…

Information Theory · Computer Science 2025-07-29 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter
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