Joint Wavelet-Based Spectrum Sensing and FBMC Modulation for Cognitive mmWave Small Cell Networks
dc.contributor.author | Erküçük, Serhat | |
dc.contributor.author | Anpalagan, Alagan | |
dc.contributor.author | Raahemifar, Kaamran | |
dc.contributor.author | Erküçük, Serhat | |
dc.contributor.author | Habib, Salman | |
dc.date.accessioned | 2019-06-27T08:01:40Z | |
dc.date.available | 2019-06-27T08:01:40Z | |
dc.date.issued | 2016 | |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
dc.description.abstract | Millimetre-wave (mmWave) 5G communications is an emerging technology to enhance the capacity of existing systems by thousand-fold improvement. Heterogeneous networks employing densely distributed small cells can optimise the available coverage and throughput of 5G systems. Efficiently utilising the spectrum bands by small cells is one of the approaches that will considerably increase the available data rate and capacity of the heterogeneous networks. This challenging task can be achieved by spectrum sensing capability of cognitive radios and new modulation techniques for data transmission. In this study a wavelet-based filter bank is proposed for spectrum sensing and modulation in 5G heterogeneous networks. The proposed technique can mitigate the spectral leakage and interference by adapting the subcarriers according to cognitive information provided by wavelet packet based spectrum sensing (WPSS) and lowering sidelobes using wavelet-based filter bank multicarrier modulation. The performance improvement of WPSS compared with Fourier-based spectrum sensing is verified in terms of power spectral density comparison and probabilities of detection and false alarm. Meanwhile the bit error rate performance demonstrates the superiority of the proposed wavelet-based system compared with its Fourier-based counterpart over the 60 GHz mmWave channel. | en_US] |
dc.identifier.citation | 18 | |
dc.identifier.doi | 10.1049/iet-com.2016.0128 | en_US |
dc.identifier.endpage | 1809 | |
dc.identifier.issn | 1751-8628 | en_US |
dc.identifier.issn | 1751-8636 | en_US |
dc.identifier.issn | 1751-8628 | |
dc.identifier.issn | 1751-8636 | |
dc.identifier.issue | 14 | |
dc.identifier.scopus | 2-s2.0-84988419993 | en_US |
dc.identifier.scopusquality | Q2 | |
dc.identifier.startpage | 1803 | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.12469/439 | |
dc.identifier.uri | https://doi.org/10.1049/iet-com.2016.0128 | |
dc.identifier.volume | 10 | en_US |
dc.identifier.wos | WOS:000384183500015 | en_US |
dc.identifier.wosquality | N/A | |
dc.institutionauthor | Erküçük, Serhat | en_US |
dc.language.iso | en | en_US |
dc.publisher | Inst Engineering Technology-IET | en_US |
dc.relation.journal | IET Communications | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | 5G Mobile Communication | en_US |
dc.subject | Radio Spectrum Management | en_US |
dc.subject | Cognitive Radio | en_US |
dc.subject | Channel Bank Filters | en_US |
dc.subject | Wavelet Transforms | en_US |
dc.subject | Modulation | en_US |
dc.subject | Millimetre-Wave 5G Communications | en_US |
dc.subject | mmWave 5G Communications | en_US |
dc.subject | Densely Distributed Small Cells | en_US |
dc.subject | Spectrum Bands | en_US |
dc.subject | Spectrum Sensing Capability | en_US |
dc.subject | Cognitive Radios | en_US |
dc.subject | Data Transmission | en_US |
dc.subject | 5G Heterogeneous Networks | en_US |
dc.subject | Spectral Leakage | en_US |
dc.subject | Wavelet Packet Based Spectrum Sensing | en_US |
dc.subject | WPSS | en_US |
dc.subject | Wavelet-Based Filter Bank Multicarrier Modulation | en_US |
dc.subject | mmWave Channel | en_US |
dc.subject | Frequency 60 GHz | en_US |
dc.title | Joint Wavelet-Based Spectrum Sensing and FBMC Modulation for Cognitive mmWave Small Cell Networks | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 440e977b-46c6-40d4-b970-99b1e357c998 | |
relation.isAuthorOfPublication.latestForDiscovery | 440e977b-46c6-40d4-b970-99b1e357c998 |