A Posteriori Guessing Random Additive Noise for Lossless Source Coding With Side Information

We propose a maximum a posteriori (MAP)-approaching decoder, namely a posteriori 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 usef...

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Vydáno v:IEEE communications letters Ročník 29; číslo 10; s. 2361 - 2365
Hlavní autoři: Camino Trevino, Javier, Benammar, Meryem, Roque, Damien
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.10.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Additive noise
Decoding
Lossless compression
maximum a posteriori
maximum likelihood
Maximum likelihood decoding
Parity check codes
Polar codes
Receivers
side information
Sorting
Source coding
syndrome compression
Training
Transmitters
Vectors
ISSN:1089-7798, 1558-2558
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Shrnutí:We propose a maximum a posteriori (MAP)-approaching decoder, namely a posteriori 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.
Bibliografie:ObjectType-Article-1
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ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2025.3595492