4 papers
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…
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)…
Reducing ORBGRAND Latency via Partial Gaussian Elimination
Li Wan, Wenyi Zhang
Guessing Random Additive Noise Decoding (GRAND) is a universal framework for decoding all block codes by testing candidate error patterns (EPs). Ordered Reliability Bits GRAND (ORB…
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…