| dc.contributor.author | Toma, A | en_US |
| dc.contributor.author | Nawaz, T | en_US |
| dc.contributor.author | Gao, Y | en_US |
| dc.contributor.author | Marcenaro, L | en_US |
| dc.contributor.author | Regazzoni, CS | en_US |
| dc.date.accessioned | 2019-07-16T09:46:00Z | |
| dc.date.available | 2019-02-20 | en_US |
| dc.date.issued | 2019-06-25 | en_US |
| dc.identifier.issn | 1751-8628 | en_US |
| dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/58517 | |
| dc.format.extent | 1336 - 1347 | en_US |
| dc.relation.ispartof | IET COMMUNICATIONS | en_US |
| dc.rights | This is a pre-copyedited, author-produced version of an article accepted for publication in IET COMMUNICATIONS following peer review. The version of record is available https://digital-library.theiet.org/content/journals/10.1049/iet-com.2018.5720 | |
| dc.subject | cognitive radio | en_US |
| dc.subject | software radio | en_US |
| dc.subject | radio spectrum management | en_US |
| dc.subject | signal detection | en_US |
| dc.subject | Bayes methods | en_US |
| dc.subject | neural nets | en_US |
| dc.subject | interference mitigation | en_US |
| dc.subject | wideband radios | en_US |
| dc.subject | spectrum correlation | en_US |
| dc.subject | dynamic spectrum access | en_US |
| dc.subject | spectrum sensing | en_US |
| dc.subject | wireless devices | en_US |
| dc.subject | radio spectrum | en_US |
| dc.subject | surrounding environment | en_US |
| dc.subject | main challenges | en_US |
| dc.subject | wireless communications | en_US |
| dc.subject | shared spectrum | en_US |
| dc.subject | artificial intelligence | en_US |
| dc.subject | cognitive radio framework | en_US |
| dc.subject | system-level | en_US |
| dc.subject | cyclic spectrum intelligence algorithm | en_US |
| dc.subject | differentiate users | en_US |
| dc.subject | different modulation schemes | en_US |
| dc.subject | artificial neural network | en_US |
| dc.subject | potential malicious users | en_US |
| dc.subject | experimental modulated signals | en_US |
| dc.subject | dynamic signals | en_US |
| dc.subject | spectrum measurements | en_US |
| dc.subject | in-house software defined radio testbed | en_US |
| dc.subject | cyclostationary features | en_US |
| dc.subject | detected signal | en_US |
| dc.subject | neural network classifier | en_US |
| dc.subject | complex | en_US |
| dc.subject | dynamic scenario | en_US |
| dc.subject | size 1 | en_US |
| dc.subject | 0 inch | en_US |
| dc.title | Interference mitigation in wideband radios using spectrum correlation and neural network | en_US |
| dc.type | Article | |
| dc.rights.holder | © 2019 The Institution of Engineering and Technology | |
| dc.identifier.doi | 10.1049/iet-com.2018.5720 | en_US |
| pubs.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000471758400002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
| pubs.issue | 10 | en_US |
| pubs.notes | Not known | en_US |
| pubs.publication-status | Published | en_US |
| pubs.volume | 13 | en_US |
| rioxxterms.funder | Default funder | en_US |
| rioxxterms.identifier.project | Default project | en_US |
| qmul.funder | GBSense: GHz Bandwidth Sensing from Smart Antennas to Sub-Nyquist Signal Processing::EPSRC | en_US |
