Communication Dans Un Congrès Année : 2025

On Universal Decoding over Discrete Additive Channels by Noise Guessing

Résumé

We study universal decoding over unknown discrete additive channels. Aiming at low-complexity decoders, we study variants of noise-guessing decoders that use estimators for the probability of a noise sequence when the actual channel law is unknown. A deterministic version produces noise sequences in a fixed order, and a new randomised version draws them at random, until finding one that, subtracted from the received sequence, results in a valid codeword. In all cases, we give sufficient conditions on the family of parametric channels for the decoding strategies to be random-coding universal, and derive upper bounds for their complexity. We give examples of common families of channels in which these conditions are satisfied, and a numerical example illustrates the proposed method's performance.

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Dates et versions

hal-05180830 , version 1 (23-07-2025)

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Henrique K. Miyamoto, Sheng Yang. On Universal Decoding over Discrete Additive Channels by Noise Guessing. 2025 IEEE Information Theory Workshop (ITW 2025), Sep 2025, Sydney, Australia. pp.1-6, ⟨10.1109/ITW62417.2025.11240417⟩. ⟨hal-05180830⟩
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