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Galaxy Codes: Advancing Achievability for Deterministic Identification via Gaussian Channels

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arxiv 2501.12548 v1 pith:CMRWPXFF submitted 2025-01-22 cs.IT math.IT

Holger Boche , Christian Deppe , Safieh Mahmoodi , Golamreza Omidi This is my paper
classification cs.ITmath.IT
keywords deterministicidentificationcapacitycodesachievabilitychannelsefficientgalaxy
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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 deterministic identification in Gaussian channels with power constraints grows superexponentially, unlike Shannon's transmission capacity. This allows for a significantly higher number of messages to be transmitted using this event-driven method. So far, only upper and lower bounds for deterministic identification capacity have been established. Our work introduces a novel construction: galaxy codes for deterministic identification. Using these codes, we demonstrate an improvement in the achievability bound of 1/4 to 3/8, representing a previously unknown advance that opens new possibilities for efficient communication.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Deterministic identification for Bernoulli channels and related channels with continuous input

    cs.IT 2026-05 conditional novelty 7.0 of 10

    Deterministic identification capacity Ċ_DI(W) equals exactly 1/2 for Bernoulli channels and channels reducible to them via continuous output distribution curves.

  2. Optimal Codes for Deterministic Identification over Gaussian Channels: Closing the Capacity Gap

    cs.IT 2026-04 unverdicted novelty 7.0 of 10

    The linearithmic deterministic identification capacity of Gaussian channels is 1/2, achieved by an optimized code that matches the upper bound and closes gaps in rate-reliability tradeoffs for all error regimes.

  3. Identification for ISI Gaussian Channels

    cs.IT 2026-03 unverdicted novelty 7.0 of 10

    Identification capacity of ISI Gaussian channels permits super-exponential message growth ~2^(n log n R) even when ISI taps scale as n^κ for κ in [0, 1/2).

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