3 citations · 3 across the 6 of their papers we have counts for
7 papers
Neural-Model-Augmented Hybrid NMS-OSD Decoders for Near-ML in Short Block Codes
Guangwen Li, Xiao Yu
This paper presents a hybrid decoding architecture that serially couples a normalized min-sum (NMS) decoder with reinforced ordered statistics decoding (OSD) to achieve near-maximu…
Effective Application of Normalized Min-Sum Decoding for Short BCH Codes
Guangwen Li, Xiao Yu
This paper introduces an enhanced normalized min-sum decoder designed to address the performance and complexity challenges associated with developing parallelizable decoders for sh…
Iterative decoding of short BCH codes and its post-processing
Guangwen Li, Xiao Yu
Effective iterative decoding of short BCH codes faces two primary challenges: identifying an appropriate parity-check matrix and accelerating decoder convergence. To address these…
Boosting Ordered Statistics Decoding of Short LDPC Codes with Simple Neural Network Models
Guangwen Li, Xiao Yu
Ordered statistics decoding has been instrumental in addressing decoding failures that persist after normalized min-sum decoding in short low-density parity-check codes. Despite it…
The impact when neural min-sum variant meets ordered statistics decoding of LDPC codes
Guangwen Li, Xiao Yu
This paper introduces three key initiatives in the pursuit of a hybrid decoding framework characterized by superior decoding performance, high throughput, low complexity, and indep…
Deep learning based enhancement of ordered statistics decoding of short LDPC codes
Guangwen Li, Xiao Yu
In the search for highly efficient decoders for short LDPC codes approaching maximum likelihood performance, a relayed decoding strategy, specifically activating the ordered statis…
A recipe of training neural network-based LDPC decoders
Guangwen Li, Xiao Yu
It is known belief propagation decoding variants of LDPC codes can be unrolled easily as neural networks after assigning differed weights to message passing edges flexibly. In this…