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DC Field | Value | Language |
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dc.contributor.author | Ahmed, AK | - |
dc.contributor.author | Al-Raweshidy, HS | - |
dc.coverage.spatial | Genoa, Italy | - |
dc.date.accessioned | 2024-08-30T13:10:45Z | - |
dc.date.available | 2024-08-30T13:10:45Z | - |
dc.date.issued | 2023-07-10 | - |
dc.identifier | ORCiD: Aya Kh. Ahmed https://orcid.org/0000-0002-3902-1760 | - |
dc.identifier | ORCiD: Hamed S. Al-Raweshidy https://orcid.org/0000-0002-3702-8192 | - |
dc.identifier.citation | Ahmed, A.K. and Al-Raweshidy, H.S. (2023) 'Deep Learning Polar Convolutional Parallel Concatenated (DL-PCPC) Channel Decoding for 6G Communications', Proceedings of the 2023 IEEE International Conference on Computer, Information, and Telecommunication Systems, CITS 2023, Genoa, Italy, 10-12 July, pp. 1 - 5. doi: 10.1109/CITS58301.2023.10188712. | en_US |
dc.identifier.isbn | 979-8-3503-3609-2 (ebk) | - |
dc.identifier.issn | 979-8-3503-3610-8 (PoD) | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29627 | - |
dc.description.abstract | The new wireless generation 6G use of intelligent devices, sensors, and new applications like virtual reality and autonomous driving requires higher demands on the network with more users which needs higher data rate networks with minimum delay and less energy consumption. The current state for channel decoding does not meet the 6G requirements. In this paper, we design, evaluate, and proposes deep learning polar convolutional parallel concatenated (DL-PCPC) decoding, a new powerful decoding technique for 6G. The developed decoding technique dynamically reduces errors by 99.8%. It provides up to 80% better system efficiency than iterative decoding algorithms, with a 100% reduction in system delay. The novel proposes design works with a 6G communication frequency range of 300 and 400 GHz with terahertz data rates, providing correctly received data with a minimum amount of detected errors. | en_US |
dc.format.extent | 1 - 5 | - |
dc.format.medium | Print-Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.rights | Copyright © Crown 2023. Published by Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. See: https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelinesand-policies/post-publication-policies/ | - |
dc.rights.uri | https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelinesand-policies/post-publication-policies/ | - |
dc.subject | channel decoding | en_US |
dc.subject | concatenated codes | en_US |
dc.subject | data rate | en_US |
dc.subject | deep learning | en_US |
dc.subject | delay | en_US |
dc.subject | terahertz | en_US |
dc.subject | 6G | en_US |
dc.title | Deep Learning Polar Convolutional Parallel Concatenated (DL-PCPC) Channel Decoding for 6G Communications | en_US |
dc.type | Conference Paper | en_US |
dc.date.dateAccepted | 2023-06-15 | - |
dc.identifier.doi | https://doi.org/10.1109/CITS58301.2023.10188712 | - |
dc.relation.isPartOf | Proceedings of the 2023 IEEE International Conference on Computer, Information, and Telecommunication Systems, CITS 2023 | - |
pubs.finish-date | 2023-07-12 | - |
pubs.finish-date | 2023-07-12 | - |
pubs.publication-status | Published | - |
pubs.start-date | 2023-07-10 | - |
pubs.start-date | 2023-07-10 | - |
dc.rights.holder | Crown | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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FullText.pdf | Copyright © Crown 2023. Published by Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. See: https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelinesand-policies/post-publication-policies/ | 523.69 kB | Adobe PDF | View/Open |
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