Reinforcement Learning Assisted Decoding
dc.contributor.advisor | Vasic, Bane | |
dc.contributor.author | Taghipour, Milad | |
dc.contributor.author | Pradhan, Asit Kumar | |
dc.contributor.author | Vasic, Bane | |
dc.date.accessioned | 2024-12-20T21:44:50Z | |
dc.date.available | 2024-12-20T21:44:50Z | |
dc.date.issued | 2024-10 | |
dc.identifier.citation | Taghipour, M., Pradhan, A. K., & Vasic, B. (2024). Reinforcement Learning Assisted Decoding. International Telemetering Conference Proceedings, 59. | |
dc.identifier.issn | 0884-5123 | |
dc.identifier.issn | 1546-2188 | |
dc.identifier.uri | http://hdl.handle.net/10150/675419 | |
dc.description.abstract | This paper explores the application of reinforcement learning techniques in the context of the performance improvement of bit-flipping based decoders. We begin with a concise overview of bit-flipping based decoders and reinforcement learning algorithms. We then outline the methodology involved in mapping these iterative decoders into Markov Decision Processes and propose a method to decrease the number of states to make the Q-learning algorithm feasible for low-rate and long-length codes. This enables us to obtain an optimal decision rule and improve the decoding performance through the utilization of reinforcement learning algorithms. Subsequently, we conduct an analysis of the reinforcement aided bit-flipping based decoder and investigate a number of potential optimal solutions achievable through reinforcement learning algorithm. We provide a comparative examination of efficiency and complexity trade-offs between data-driven algorithms and traditional methods across the Binary Symmetric Channel and Additive White Gaussian Noise Channel. | |
dc.description.sponsorship | International Foundation for Telemetering | |
dc.language.iso | en | |
dc.publisher | International Foundation for Telemetering | |
dc.relation.url | https://telemetry.org/ | |
dc.rights | Copyright © held by the author; distribution rights International Foundation for Telemetering. | |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
dc.title | Reinforcement Learning Assisted Decoding | |
dc.type | Proceedings | |
dc.type | text | |
dc.contributor.department | Department of Electrical and Computer Engineering, University of Arizona | |
dc.identifier.journal | International Telemetering Conference Proceedings | |
dc.description.collectioninformation | Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit https://telemetry.org/contact-us/ if you have questions about items in this collection. | |
dc.eprint.version | Final published version | |
dc.source.journaltitle | International Telemetering Conference Proceedings | |
dc.source.volume | 59 | |
refterms.dateFOA | 2024-12-20T21:44:50Z |