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cs.IT2026
Performance Analysis and Optimal Design of ORB-Type GRAND Algorithms
Li Wan, Wenyi Zhang
Guessing Random Additive Noise Decoding (GRAND) performs decoding by sequentially guessing channel error patterns (EPs). Ordered Reliability Bits GRAND (ORBGRAND) is a notable inst…
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…