QGRAND - Quantized Guessing Additive Noise Decoding
We disclose a soft-detection variant of Guessing Random Additive Noise Decoding (GRAND) called discretized soft-information for GRAND (DSGRAND) that can efficiently decode any moderate redundancy block-code in an algorithm that is suitable for highly parallelized implementation in hardware. DSGRAND provides near maximum likelihood decoding performance when provided with five or more bits of soft information per received bit, by discretizing the soft information into noise effect sequences and allocating those sequences into bins according to weight. The use of these bins provides a separate, simplified manner of sequencing noise guessing.
Researchers
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discretized soft-information for guessing random additive noise decoding
United States of America | Pending -
quantized guessing random additive noise decoding
European Patent Convention | Published application -
quantized guessing random additive noise decoding
Japan | Published application -
quantized guessing random additive noise decoding
Korea (south) | Published application
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