Error correction techniques traditionally focus on the co-design of restricted code-structures
in tandem with code-specific decoders that are computationally efficient when decoding long …

While many communications media, such as wireless and certain classes of wireline
channels, typically lead to bursty errors, most decoders are designed assuming memoryless …

The first release of 5G technology is being rolled out worldwide. In parallel, 3GPP is
constantly adding new features to upcoming releases covering well-known use cases. This …

Guessing Random Additive Noise Decoding (GRAND) is a universal decoding algorithm
that has been recently proposed as a practical way to perform maximum likelihood …

A universal decoding scheme is conceived for quantum stabilizer codes (QSCs) by
appropriately adapting the 'guessing random additive noise decoding'(GRAND) philosophy …

The design and implementation of error correcting codes has long been informed by two
fundamental results: Shannon's 1948 capacity theorem, which established that long codes …

Guessing random additive noise decoding (GRAND) is a universal maximum-likelihood
decoder that recovers codewords by guessing rank-ordered putative noise sequences and …

Maximum-likelihood (ML) decoding can be used to obtain the optimal performance of error
correction codes. However, the size of the search space and consequently the decoding …

Guessing Random Additive Noise Decoding (GRAND) is a family of hard-and soft-detection
error correction decoding algorithms that provide accurate decoding of any moderate …

For spectral efficiency, higher order modulation symbols confer information on more than
one bit. As soft detection forward error correction decoders assume the availability of …