Optimization of vertical handover decision processes for fourth generation heterogeneous wireless networks
thesisposted on 15.01.2017 by Yan, Xiaohuan
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
This thesis presents a vertical handover decision (VHD) scheme for optimizing the efficiency of vertical handover processes in the Fourth Generation (4G) heterogeneous wireless networks. The scheme consists of three closely integrated modules: Handover necessity estimation, handover target selection, and handover triggering condition estimation. Handover necessity estimation module determines whether a handover is necessary to an available network. Handover target selection module chooses the ``best'' network among the available candidates based on a set of criteria. Finally, handover triggering condition estimation module determines the right moment to initiate a handover out of the currently connected network. 4G wireless networks are expected to support mechanisms for tight integration and cooperation of divergent access network technologies. In such networks of heterogeneous nature, roaming users will experience frequent handovers across network boundaries. Thus, to ensure seamless roaming and efficient resource usage over dissimilar networks, intelligent VHD algorithms need to be used extensively. The research project presented in this thesis report focuses on this problem and provides an optimized VHD scheme, which minimizes the handover failures, unnecessary handovers and connection breakdowns whilst maintaining users' satisfaction at high levels. In addition, the scheme also provides mechanisms for mobile applications to control the tradeoff between the usage of the preferred access network and number of handovers or connection breakdowns. Simulation based performance evaluations demonstrate that the scheme reduces the number of handover failures, unnecessary handovers and connection breakdowns by up to 80%, 70% and 70%, respectively. They also show an increase of up to 50% in the satisfaction level of users.