2021/03/05 by Baptiste Cavarec, Hasan Basri Çelebi, Cavarec, Baptiste +6
Computer Science · Engineering · Mathematics · #Error Correcting Code Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #Low-power high-performance VLSI design #Machine Learning (cs.LG) #Numerical Methods and Algorithms #cs.IT #cs.LG #math.IT
paper · pdf · doi:10.48550/arxiv.2103.03860
Presented at the 2020 Asilomar Conference on Signals, Systems, and Computers
arxiv created 2021/03/05 · openalex publication_date 2021/03/05 · arxiv updated 2021/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we study the tradeoffs between complexity and reliability for decoding large linear block codes. We show that using artificial neural networks to predict the required order of an ordered statistics based decoder helps in reducing the average complexity and hence the latency of the decoder. We numerically validate the approach through Monte Carlo simulations.