A Posteriori Guessing Random Additive Noise for Lossless Source Coding With Side Information
We propose a maximum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> (MAP)-approaching decoder, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> guessing random additive noise decoding (AP-GRAND), which generalizes the existing maximum likelihood (ML)-approaching guessing random additive noise decoding (GRAND) to non-uniform sources. This decoder is notably useful for lossless source coding with side information (LSCSI) problems involving non-uniform binary sources. The proposed decoder is universal and can be applied to all channel codes. We illustrate the performance of AP-GRAND for short-blocklength Polar, BCH, and LDPC codes.
Authors
- Meryem Benammar (ORCID: https://orcid.org/0000-0002-4443-9256)
- Damien Roque (ORCID: https://orcid.org/0000-0003-4352-3971)
- Javier Camino Treviño (ORCID: https://orcid.org/0009-0003-7034-081X)
Institutions
- École Nationale de l’Aviation Civile (FR)
- Institut Superieur de l'Aeronautique et de l'Espace (ISAE-SUPAERO) (FR)
- Office National d'Études et de Recherches Aérospatiales (FR)
Publication Details
- Journal
- IEEE Communications Letters
- Published
- 2025-08-04
- DOI
- https://doi.org/10.1109/lcomm.2025.3595492
- Primary Topic
- Wireless Communication Security Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Région Occitanie Pyrénées-Méditerranée