Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.715724
Title: Heterogeneous networking for beyond 3G system in a high-speed train environment : investigation of handover procedures in a high-speed train environment and adoption of a pattern classification neural-networks approach for handover management
Author: Ong, Felicia Li Chin
Awarding Body: University of Bradford
Current Institution: University of Bradford
Date of Award: 2016
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Abstract:
Based on the targets outlined by the EU Horizon 2020 (H2020) framework, it is expected that heterogeneous networking will play a crucial role in delivering seamless end-to-end ubiquitous Internet access for users. In due course, the current GSM-Railway (GSM-R) will be deemed unsustainable, as the demand for packet-oriented services continues to increase. Therefore, the opportunity to identify a plausible replacement system conducted in this research study is timely and appropriate. In this research study, a hybrid satellite and terrestrial network for enabling ubiquitous Internet access in a high-speed train environment is investigated. The study focuses on the mobility management aspect of the system, primarily related to the handover management. A proposed handover strategy, employing the RACE II MONET and ITU-T Q.65 design methodology, will be addressed. This includes identifying the functional model (FM) which is then mapped to the functional architecture (FUA), based on the Q.1711 IMT-2000 FM. In addition, the signalling protocols, information flows and message format based on the adopted design methodology will also be specified. The approach is then simulated in OPNET and the findings are then presented and discussed. The opportunity of exploring the prospect of employing neural networks (NN) for handover is also undertaken. This study focuses specifically on the use of pattern classification neural networks to aid in the handover process, which is then simulated in MATLAB. The simulation outcomes demonstrated the effectiveness and appropriateness of the NN algorithm and the competence of the algorithm in facilitating the handover process.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.715724  DOI: Not available
Keywords: Mobility management ; Neural networking ; Heterogeneous network ; Handover decision ; Wireless fidelity (WiFi) system ; Satellite system ; Backpropagation network ; Pattern classification
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