BCH codes; channel decoding; DL; GNN; BCH code; Channel decoding; Correction methodology; Deep learning; Errors correction; Graph neural networks; Graph structured data; Learning techniques; Performance tradeoff; Physical layers; Safety, Risk, Reliability and Quality; Control and Optimization; Artificial Intelligence; Computer Networks and Communications; Computer Science Applications; Signal Processing; Information Systems and Management; Renewable Energy, Sustainability and the Environment
Résumé :
[en] This paper delves into the transformative impact of Deep Learning (DL) techniques on decoding tasks at the physical layer onboard regenerative software-defined satellites, reshaping traditional error correction methodologies. Specifically, we focus on the integration of Graph Neural Networks (GNNs) for channel decoding, which offers a fresh perspective by adeptly handling graph-structured data and effectively modelling intricate interference and channel dependencies. The study systematically explores the potential performance tradeoffs that arise from modifying the graph structure. Furthermore, we extend our investigation by implementing the message-passing algorithm with GNN, employing a topk pooling method following pick, prune, and link optimization strategies. This strategic approach aims to mitigate computational complexity and minimize latency, by 30 to 35 % which is particularly advantageous for decoding BCH codes. This advancement promises to enhance the efficiency of communication systems sianificantly
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM - Signal Processing & Communications
Disciplines :
Sciences informatiques
Auteur, co-auteur :
VARADARAJULU, Swetha ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Baeza, Victor Monzon; University of Luxembourg, Interdisciplinary Centre for Security Reliability and Trust (SnT), Luxembourg
QUEROL, Jorge ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
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