{"id":{"repo_id":"essex","oai_identifier":"oai:repository.essex.ac.uk:20006"},"canonical_url":"https://search.dev.ndltd.org/etd/essex/oai:repository.essex.ac.uk:20006","repository":{"repo_id":"essex","name":"University of Essex","base_url":"https://repository.essex.ac.uk/cgi/oai2"},"display":{"title":"Ultrawideband IEEE802.15.4a Cognitive Localization Methods for the 5G Environment","abstract":"This thesis focuses on utilization of ultra-wideband (UWB) technology for cognitive localization in the fifth generation (5G) wireless environment that envisages seamless global connection of ubiquitous devices. This suggests the need for cognitive high-definition location-aware networks and devices devoid of the drawbacks of current positioning systems. The thesis therefore models a cognitive UWB IEEE802.15.4a LOS sufficient technique (ULOSTECH); with a framework for optimal UWB localization channel that utilizes combined cluster decay rate and mistiming probability method that achieves over 90% realizations. Moreover, the ULOSTECH NLOS mitigation method achieves about 0.257 improvement ratio on the accuracy of cellular network localization methods. An impulse radio (IR)-UWB device-to-device (D2D) WWAN is further proposed with channel time partitioned into discrete micro-channel slots (DMCS) along with a cluster formation scheme that achieves above 350Mbps network throughput in comparison with 100Mbps cellular and 250Mbps wi-fi standards respectively. Additionally, the cluster cooperation method achieves multi-user access rate of over 485% above cellular network standards. Also proposed is the ULOSTECH D2D-propagation-based combined localization and communication scheme (UD-CLOCS) for ultra-dense networks. This utilizes cooperative D2D data hoping localization technique that achieves a mean distance error of 0.54 – 3.32 shorter than trilateration and multi-dimensional scaling (MDS) methods respectively. Finally, the thesis proposes an overall IR-UWB network layout for the 5G setting. This comprises an all-IP D2D UWB network overlay of concurrent multi-layered super-core architecture (5G-COMUSA). This is significant as the proposed solutions could serve to decongest the licensed spectrums in the 5G environment.","abstract_html":"This thesis focuses on utilization of ultra-wideband (UWB) technology for cognitive localization in the fifth generation (5G) wireless environment that envisages seamless global connection of ubiquitous devices. This suggests the need for cognitive high-definition location-aware networks and devices devoid of the drawbacks of current positioning systems. The thesis therefore models a cognitive UWB IEEE802.15.4a LOS sufficient technique (ULOSTECH); with a framework for optimal UWB localization channel that utilizes combined cluster decay rate and mistiming probability method that achieves over 90% realizations. Moreover, the ULOSTECH NLOS mitigation method achieves about 0.257 improvement ratio on the accuracy of cellular network localization methods. An impulse radio (IR)-UWB device-to-device (D2D) WWAN is further proposed with channel time partitioned into discrete micro-channel slots (DMCS) along with a cluster formation scheme that achieves above 350Mbps network throughput in comparison with 100Mbps cellular and 250Mbps wi-fi standards respectively. Additionally, the cluster cooperation method achieves multi-user access rate of over 485% above cellular network standards. Also proposed is the ULOSTECH D2D-propagation-based combined localization and communication scheme (UD-CLOCS) for ultra-dense networks. This utilizes cooperative D2D data hoping localization technique that achieves a mean distance error of 0.54 – 3.32 shorter than trilateration and multi-dimensional scaling (MDS) methods respectively. Finally, the thesis proposes an overall IR-UWB network layout for the 5G setting. This comprises an all-IP D2D UWB network overlay of concurrent multi-layered super-core architecture (5G-COMUSA). This is significant as the proposed solutions could serve to decongest the licensed spectrums in the 5G environment.","abstract_has_math":false,"creators":["Adebomehin, Akeem A"],"institution":"University of Essex","degree_name":"phd","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-07","date_published":"2017-07","updated_at":"2026-07-24T02:18:14Z","subjects":["T Technology (General)","TK Electrical engineering. 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The thesis therefore models a cognitive UWB IEEE802.15.4a LOS sufficient technique (ULOSTECH); with a framework for optimal UWB localization channel that utilizes combined cluster decay rate and mistiming probability method that achieves over 90% realizations. Moreover, the ULOSTECH NLOS mitigation method achieves about 0.257 improvement ratio on the accuracy of cellular network localization methods. An impulse radio (IR)-UWB device-to-device (D2D) WWAN is further proposed with channel time partitioned into discrete micro-channel slots (DMCS) along with a cluster formation scheme that achieves above 350Mbps network throughput in comparison with 100Mbps cellular and 250Mbps wi-fi standards respectively. Additionally, the cluster cooperation method achieves multi-user access rate of over 485% above cellular network standards. Also proposed is the ULOSTECH D2D-propagation-based combined localization and communication scheme (UD-CLOCS) for ultra-dense networks. This utilizes cooperative D2D data hoping localization technique that achieves a mean distance error of 0.54 – 3.32 shorter than trilateration and multi-dimensional scaling (MDS) methods respectively. Finally, the thesis proposes an overall IR-UWB network layout for the 5G setting. This comprises an all-IP D2D UWB network overlay of concurrent multi-layered super-core architecture (5G-COMUSA). This is significant as the proposed solutions could serve to decongest the licensed spectrums in the 5G environment."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Ultrawideband IEEE802.15.4a Cognitive Localization Methods for the 5G Environment"]}]}],"canonical_facts":{"dc:creator":["Adebomehin, Akeem A"],"dc:date":["2017-07-01"],"dc:date.issued":["2017-07"],"dc:description.abstract":["This thesis focuses on utilization of ultra-wideband (UWB) technology for cognitive localization in the fifth generation (5G) wireless environment that envisages seamless global connection of ubiquitous devices. This suggests the need for cognitive high-definition location-aware networks and devices devoid of the drawbacks of current positioning systems. The thesis therefore models a cognitive UWB IEEE802.15.4a LOS sufficient technique (ULOSTECH); with a framework for optimal UWB localization channel that utilizes combined cluster decay rate and mistiming probability method that achieves over 90% realizations. Moreover, the ULOSTECH NLOS mitigation method achieves about 0.257 improvement ratio on the accuracy of cellular network localization methods. An impulse radio (IR)-UWB device-to-device (D2D) WWAN is further proposed with channel time partitioned into discrete micro-channel slots (DMCS) along with a cluster formation scheme that achieves above 350Mbps network throughput in comparison with 100Mbps cellular and 250Mbps wi-fi standards respectively. Additionally, the cluster cooperation method achieves multi-user access rate of over 485% above cellular network standards. Also proposed is the ULOSTECH D2D-propagation-based combined localization and communication scheme (UD-CLOCS) for ultra-dense networks. This utilizes cooperative D2D data hoping localization technique that achieves a mean distance error of 0.54 – 3.32 shorter than trilateration and multi-dimensional scaling (MDS) methods respectively. Finally, the thesis proposes an overall IR-UWB network layout for the 5G setting. This comprises an all-IP D2D UWB network overlay of concurrent multi-layered super-core architecture (5G-COMUSA). This is significant as the proposed solutions could serve to decongest the licensed spectrums in the 5G environment."],"dc:format":["text"],"dc:identifier.uri":["https://repository.essex.ac.uk/20006/1/FINAL%20THESIS%20COMPLETE%20SUBMISSION%20COPY%20-%2001JULY2017.pdf"],"dc:language":["en"],"dc:publisher.department":["School of Computer Science and and Electronic Engineering"],"dc:publisher.institution":["University of Essex"],"dc:relation.isreferencedby":["https://repository.essex.ac.uk/20006/"],"dc:subject":["T Technology (General)","TK Electrical engineering. 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