| dc.contributor.author | Shen, W | en_US |
| dc.contributor.author | Qin, Z | en_US |
| dc.contributor.author | Nallanathan, A | en_US |
| dc.date.accessioned | 2024-07-16T08:32:23Z | |
| dc.date.issued | 2023 | en_US |
| dc.identifier.issn | 0090-6778 | en_US |
| dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/98164 | |
| dc.format.extent | 1491 - 1503 | en_US |
| dc.relation.ispartof | IEEE TRANSACTIONS ON COMMUNICATIONS | en_US |
| dc.rights | This item is distributed under the terms of the Creative Commons Attribution 4.0 Unported License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | |
| dc.subject | Channel estimation | en_US |
| dc.subject | deep learning | en_US |
| dc.subject | OFDM | en_US |
| dc.subject | multi-user | en_US |
| dc.subject | reconfigurable intelligent surface | en_US |
| dc.title | Deep Learning for Super-Resolution Channel Estimation in Reconfigurable Intelligent Surface Aided Systems | en_US |
| dc.type | Article | |
| dc.rights.holder | © 2023 The Author(s). Published by IEEE | |
| dc.identifier.doi | 10.1109/TCOMM.2023.3239621 | en_US |
| pubs.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:001053380300019&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
| pubs.issue | 3 | en_US |
| pubs.notes | Not known | en_US |
| pubs.publication-status | Published | en_US |
| pubs.volume | 71 | en_US |
| rioxxterms.funder | Default funder | en_US |
| rioxxterms.identifier.project | Default project | en_US |
| rioxxterms.funder.project | b215eee3-195d-4c4f-a85d-169a4331c138 | en_US |
