Ultrawideband IEEE802.15.4a Cognitive Localization Methods for the 5G Environment

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.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of Essex

Year dc:date.issued

2017

Author dc:creator

• Adebomehin, Akeem A

• T Technology (General)
• TK Electrical engineering. Electronics Nuclear engineering

Language dc:language

en