{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T02:11:29Z","timestamp":1773886289983,"version":"3.50.1"},"reference-count":44,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005307","name":"Direction G\u00e9n\u00e9rale de la Recherche Scientifique et du D\u00e9veloppement Technologique","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005307","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002717","name":"Minist\u00e8re de l'Enseignement Sup\u00e9rieur et de la Recherche Scientifique","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002717","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007335","name":"Ministry of Higher Education and Scientific Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007335","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Physical Communication"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1016\/j.phycom.2025.102952","type":"journal-article","created":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T23:27:51Z","timestamp":1765063671000},"page":"102952","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Efficient convolutional LDPC decoding for Nakagami-m fading channels in 5G-NR"],"prefix":"10.1016","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5022-8797","authenticated-orcid":false,"given":"Nour El Houda","family":"Zareb","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2990-2214","authenticated-orcid":false,"given":"Mohamed","family":"Azni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9847-9547","authenticated-orcid":false,"given":"Meriem","family":"Gagaoua","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0898-3382","authenticated-orcid":false,"given":"Reda","family":"Kasmi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.phycom.2025.102952_sbref0001","series-title":"Technical Report","article-title":"IMT vision - Framework and overall objectives of the future development of IMT for 2020 and beyond","author":"ITU-R","year":"2015"},{"issue":"1","key":"10.1016\/j.phycom.2025.102952_bib0002","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TIT.1962.1057683","article-title":"Low-density parity-check codes","volume":"8","author":"Gallager","year":"1962","journal-title":"IRE Trans. Inf. Theory"},{"key":"10.1016\/j.phycom.2025.102952_bib0003","series-title":"Proc. Annu. Conf. Inf. Sci. Syst. (CISS)","first-page":"1","article-title":"On deep learning-based channel decoding","author":"Gruber","year":"2017"},{"key":"10.1016\/j.phycom.2025.102952_bib0004","series-title":"Machine Learning and Wireless Communications","first-page":"77","article-title":"Channel coding via machine learning","author":"Kim","year":"2022"},{"issue":"1","key":"10.1016\/j.phycom.2025.102952_bib0005","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1109\/JSTSP.2017.2788405","article-title":"Deep learning methods for improved decoding of linear codes","volume":"12","author":"Nachmani","year":"2018","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"10.1016\/j.phycom.2025.102952_bib0006","series-title":"2022 IEEE Globecom Workshops (GC Wkshps)","first-page":"486","article-title":"Graph neural networks for channel decoding","author":"Cammerer","year":"2022"},{"key":"10.1016\/j.phycom.2025.102952_bib0007","doi-asserted-by":"crossref","DOI":"10.1109\/ACCESS.2024.3420106","article-title":"CNN-Based approach for enhancing 5G LDPC code decoding performance","author":"Tera","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.phycom.2025.102952_bib0008","series-title":"2021 IEEE International Conference on Networking, Sensing and Control (ICNSC)","first-page":"1","article-title":"Normalized neural network for belief propagation LDPC decoding","volume":"1","author":"Tang","year":"2021"},{"issue":"1","key":"10.1016\/j.phycom.2025.102952_bib0009","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/JSTSP.2018.2794062","article-title":"An iterative BP-CNN architecture for channel decoding","volume":"12","author":"Liang","year":"2018","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"10.1016\/j.phycom.2025.102952_bib0010","series-title":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","first-page":"1","article-title":"A model-driven deep learning method for normalized min-sum LDPC decoding","author":"Wang","year":"2020"},{"key":"10.1016\/j.phycom.2025.102952_bib0011","series-title":"2023 IEEE International Conference on Communications (ICC)","first-page":"6645","article-title":"Interpreting neural min-Sum decoders","author":"Ankireddy","year":"2023"},{"issue":"7","key":"10.1016\/j.phycom.2025.102952_bib0012","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.1109\/LCOMM.2024.3404110","article-title":"Neural self-corrected min-sum decoder for NR LDPC codes","volume":"28","author":"Kim","year":"2024","journal-title":"IEEE Commun. Lett."},{"issue":"23","key":"10.1016\/j.phycom.2025.102952_bib0013","doi-asserted-by":"crossref","DOI":"10.3390\/app132312657","article-title":"Shared graph neural network for channel decoding","volume":"13","author":"Wu","year":"2023","journal-title":"Appl. Sci."},{"key":"10.1016\/j.phycom.2025.102952_bib0014","doi-asserted-by":"crossref","DOI":"10.1109\/ACCESS.2024.3472466","article-title":"Deep learning approach for efficient 5G LDPC decoding in IoT","author":"Tera","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.phycom.2025.102952_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.phycom.2023.102255","article-title":"BEP Evaluation of 5G LDPC codes in a pre-amplified optical PPM receiver","volume":"62","author":"Yiannopoulos","year":"2024","journal-title":"Phys. Commun."},{"key":"10.1016\/j.phycom.2025.102952_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.phycom.2024.102567","article-title":"LDPC-Coded OAM shift-keying FSO communication system with dual-pattern CNN demodulator","volume":"68","author":"Li","year":"2025","journal-title":"Phys. Commun."},{"key":"10.1016\/j.phycom.2025.102952_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.phycom.2021.101538","article-title":"Novel memory efficient LDPC decoders for beyond 5G","volume":"51","author":"Li","year":"2022","journal-title":"Phys. Commun."},{"key":"10.1016\/j.phycom.2025.102952_bib0018","doi-asserted-by":"crossref","first-page":"50179","DOI":"10.1109\/ACCESS.2018.2869374","article-title":"Decoding optimization for 5G LDPC codes by machine learning","volume":"6","author":"Wu","year":"2018","journal-title":"IEEE Access"},{"key":"10.1016\/j.phycom.2025.102952_bib0019","series-title":"2018 10Th International Conference on Wireless Communications and Signal Processing (WCSP)","first-page":"1","article-title":"A unified deep learning based polar-LDPC decoder for 5G communication systems","author":"Wang","year":"2018"},{"key":"10.1016\/j.phycom.2025.102952_bib0020","series-title":"ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"4845","article-title":"Neural layered min-sum decoding for protograph LDPC codes","author":"Zhang","year":"2021"},{"issue":"7","key":"10.1016\/j.phycom.2025.102952_bib0021","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1109\/JSAC.2021.3078488","article-title":"Learning to decode protograph LDPC codes","volume":"39","author":"Dai","year":"2021","journal-title":"IEEE J. Sel. Areas Commun."},{"issue":"11","key":"10.1016\/j.phycom.2025.102952_bib0022","doi-asserted-by":"crossref","first-page":"3590","DOI":"10.1109\/LCOMM.2021.3113610","article-title":"Neural layered decoding of 5G LDPC codes","volume":"25","author":"Shah","year":"2021","journal-title":"IEEE Commun. Lett."},{"key":"10.1016\/j.phycom.2025.102952_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.compeleceng.2025.110406","article-title":"LDPC Code design with 5G based on hybrid lyre puffer fish optimization","volume":"124","author":"Shah","year":"2025","journal-title":"Comput. Electr. Eng."},{"key":"10.1016\/j.phycom.2025.102952_bib0024","series-title":"ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"3782","article-title":"Decoding 5G-NR communications VIA deep learning","author":"Henarejos","year":"2020"},{"issue":"1","key":"10.1016\/j.phycom.2025.102952_bib0025","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/TCCN.2022.3212438","article-title":"Normalized min-sum neural network for LDPC decoding","volume":"9","author":"Wang","year":"2022","journal-title":"IEEE Trans. Cognit. Commun. Networking"},{"key":"10.1016\/j.phycom.2025.102952_bib0026","series-title":"2023 International Wireless Communications and Mobile Computing (IWCMC)","first-page":"224","article-title":"A deep learning based multi-edge-type decoding algorithm for 5G NR LDPC codes","author":"Du","year":"2023"},{"key":"10.1016\/j.phycom.2025.102952_bib0027","series-title":"2023Del InsThinspace IEEE 98Th Vehicular Technology Conference (VTC2023-Fall)","first-page":"1","article-title":"Neural adjusted min-sum decoding for LDPC codes","author":"Yu","year":"2023"},{"issue":"5","key":"10.1016\/j.phycom.2025.102952_bib0028","doi-asserted-by":"crossref","first-page":"7374","DOI":"10.1109\/TVT.2023.3344127","article-title":"Rate compatible LDPC neural decoding network: a multi-task learning approach","volume":"73","author":"Cheng","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"10.1016\/j.phycom.2025.102952_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.compeleceng.2020.106636","article-title":"Optimization design of polar-LDPC concatenated scheme based on deep learning","volume":"84","author":"Wang","year":"2020","journal-title":"Comput. Elect. Eng."},{"key":"10.1016\/j.phycom.2025.102952_bib0030","series-title":"2021 29Th Telecommunications Forum (TELFOR)","first-page":"1","article-title":"Performance of 5G new radio low-Density parity-Check codes in nakagami-m fading channel","author":"Vasi\u0107","year":"2021"},{"issue":"5","key":"10.1016\/j.phycom.2025.102952_bib0031","article-title":"Performance evaluation of 5G new radio low-density parity check codes over different scenarios of lognormal fading channel","volume":"72","author":"Ali","year":"2024","journal-title":"Bull. Polish Acad. Sci. Tech. Sci."},{"key":"10.1016\/j.phycom.2025.102952_bib0032","series-title":"2017Del InsThinspace IEEE International Symposium on Information Theory (ISIT)","first-page":"1361","article-title":"Neural offset min-sum decoding","author":"Lugosch","year":"2017"},{"key":"10.1016\/j.phycom.2025.102952_bib0033","series-title":"2019Del InsThinspace IEEE International Symposium on Information Theory (ISIT)","first-page":"2444","article-title":"Deep learning-aided trainable projected gradient decoding for LDPC codes","author":"Wadayama","year":"2019"},{"issue":"2","key":"10.1016\/j.phycom.2025.102952_bib0034","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1109\/JSAIT.2021.3073834","article-title":"Belief propagation decoding of short graph-based channel codes via reinforcement learning","volume":"2","author":"Habib","year":"2021","journal-title":"IEEE J. Sel. Areas Infor. Theory"},{"key":"10.1016\/j.phycom.2025.102952_bib0035","series-title":"2021 XVII International Symposium\u201d Problems of Redundancy in Information and Control Systems\u201d(REDUNDANCY)","first-page":"155","article-title":"Deep neural network based decoding of short 5G LDPC codes","author":"Andreev","year":"2021"},{"key":"10.1016\/j.phycom.2025.102952_bib0036","series-title":"2021 IEEE 94Th Vehicular Technology Conference (VTC2021-Fall)","first-page":"1","article-title":"Machine learning scaled belief propagation for short codes","author":"Hummert","year":"2021"},{"issue":"3","key":"10.1016\/j.phycom.2025.102952_bib0037","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1109\/LCOMM.2021.3137222","article-title":"Stopping-set assisted reinforced belief propagation for decoding short LDPC codes","volume":"26","author":"Zamzami","year":"2021","journal-title":"IEEE Commun. Lett."},{"key":"10.1016\/j.phycom.2025.102952_bib0038","series-title":"2021Del InsThinspace IEEE 6Th International Conference on Computer and Communication Systems (ICCCS)","first-page":"558","article-title":"A low complexity model-driven deep learning ldpc decoding algorithm","author":"Qingle","year":"2021"},{"issue":"9","key":"10.1016\/j.phycom.2025.102952_bib0039","doi-asserted-by":"crossref","first-page":"2015","DOI":"10.1109\/LWC.2022.3192518","article-title":"Improved layered normalized min-sum algorithm for 5G NR LDPC","volume":"11","author":"Jayawickrama","year":"2022","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"10.1016\/j.phycom.2025.102952_bib0040","unstructured":"M. Hernandez, F. Pinero, 5G LDPC Linear Transformer for Channel Decoding, arXiv preprint arXiv: 2501.14102(2025)."},{"key":"10.1016\/j.phycom.2025.102952_bib0041","unstructured":"D. Chang, Q. Peng, G. Wang, G. Yan, High Throughput QC-LDPC Decoder With Optimized Schedule Policy in Layered Decoding, arXiv preprint arXiv: 2505.19027(2025)."},{"key":"10.1016\/j.phycom.2025.102952_bib0042","unstructured":"Ad-Hoc Chair (Nokia), Chairman\u2019s Notes of Agenda Item 7.1.4: Channel Coding, 2017, (3GPP TSG RAN WG1 Meeting AH 2, Document R1-1711982). Available online: https:\/\/portal.3gpp.org."},{"key":"10.1016\/j.phycom.2025.102952_bib0043","unstructured":"3rd Generation Partnership Project (3GPP), TS 38.212 - NR; Multiplexing and Channel Coding, 2024, (https:\/\/portal.3gpp.org\/desktopmodules\/Specifications\/SpecificationDetails.aspx?specificationId=3191). 3GPP Technical Specification, version 17.6.0, Release 17."},{"key":"10.1016\/j.phycom.2025.102952_bib0044","series-title":"Modern Coding Theory","author":"Richardson","year":"2008"}],"container-title":["Physical Communication"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1874490725003556?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1874490725003556?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T21:09:14Z","timestamp":1773868154000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1874490725003556"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":44,"alternative-id":["S1874490725003556"],"URL":"https:\/\/doi.org\/10.1016\/j.phycom.2025.102952","relation":{},"ISSN":["1874-4907"],"issn-type":[{"value":"1874-4907","type":"print"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Efficient convolutional LDPC decoding for Nakagami-m fading channels in 5G-NR","name":"articletitle","label":"Article Title"},{"value":"Physical Communication","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.phycom.2025.102952","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"102952"}}