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cs.IT2025
ORBGRAND Is Exactly Capacity-achieving via Rank Companding
Zhuang Li, Wenyi Zhang
Within the family of guessing-based decoding algorithms, ordered reliability bits GRAND (ORBGRAND) has attracted considerable attention due to its efficient use of soft information…
cs.IT2025
A Parallelization Strategy for GRAND with Optimality Guarantee by Exploiting Error Pattern Tree Representation
Li Wan, Huarui Yin, Wenyi Zhang
Parallelism has become a central concern in modern decoding frameworks aiming to meet stringent throughput and latency requirements. Guessing Random Additive Noise Decoding (GRAND)…
cs.IT2025
Fine-tuning ORBGRAND with Very Few Channel Soft Values
Li Wan, Huarui Yin, Wenyi Zhang
Guessing random additive noise decoding (GRAND) is a universal decoding paradigm that decodes by repeatedly testing error patterns until identifying a codeword, where the ordering…