Analysing an Analytical Solution Model for Simultaneous Mobility

Chowdhury, Md. Ibrahim; Iqbal, Mohammad; Sultana, Naznin; Rahman, Faisal

doi:10.5121/ijwmn.2013.5609

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…The UE-traces scenario is dependent on the chosen mobility model, including the amount and speed of each UE's movement. There is an extensive amount of research on mobility models using analytical and simulation approaches [27,33,34]. However, the study of UEs mobility behaviors is out of the scope of this dissertation, and hence the methods applied for generating the UE-traces scenario used for the performance evaluation, and aggregating the data from it, are explained in Appendix B.…”

Section: Performance Evaluation Of the Proposed Tal Schemesmentioning

confidence: 99%

Planning and Optimization of Tracking Areas for Long TermEvolution Networks

Razavi¹

2014

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Along with the evolution of network technologies, user's expectations on performance and mobile services are rising rapidly. To fulfill customer demands, the operators are facing a great amount of network signaling overhead in terms of Location Management (LM), which tracks and pages User Equipments (UEs) in the network. Hence, sustaining a reliable and cost-efficient LM system for future mobile broadband networks has become one of the major challenges in mobile telecommunications. Tracking Area (TA) in Long Term Evolution (LTE), is a logical grouping of cells that manages and represents the locations of UEs. This dissertation deals with planning and optimization of TAs.TA design must be revised over time in order to adapt to changes and trends in UE location and mobility patterns. Re-optimization of a once optimized design subject to different cost budgets is one of the problems considered in this dissertation. By re-optimization, the design is successively improved by reassigning some cells to TAs other than their original ones. An algorithm based on repeated local search is developed in order to solve the resulting problem.The next topic of research is the trade-off between the performance in terms of the total signaling overhead of the network and the reconfiguration cost. This trade-off is modeled as a bi-objective optimization problem to which the solutions are characterized by Paretooptimality. Solving the problem delivers a host of potential tradeoffs, among which the selection can be based on the preferences of a decision-maker. An integer programming model and a genetic algorithm heuristic are developed for solving the problem in large-scale networks.In comparison to previous generations of cellular networks, LTE systems allow for a more flexible configuration of TA design by means of Tracking Area List (TAL). How to utilize this flexibility in applying TAL to large-scale networks is still an open problem. In this dissertation, three approaches for allocating and assigning TALs are presented, and their performances are compared with each other, as well as with the conventional TA scheme. Moreover, a linear programming model is developed to minimize the total signaling overhead of the network based on overlapping TALs.In this dissertation, the problem of mitigating signaling congestion is thoroughly studied both for the specific train scenario and also for the general network topology. For each signaling congestion scenario, a related linear programming model based on minimizing the maximum signaling due to tracking area update or paging is developed. As a major advantage of the modified overlapping TAL scheme iii for signaling congestion avoidance, information of individual UE mobility is not required.Automatic reconfiguration of LM is an important element in LTE. The network continuously collects UE statistics, and the management system adapts the network configuration to changes in UE distribution and demand. In this dissertation an evaluation of dynamic configuration of TA design, including ...

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Section: Performance Evaluation Of the Proposed Tal Schemesmentioning

confidence: 99%

Planning and Optimization of Tracking Areas for Long TermEvolution Networks

Razavi¹

2014

View full text Add to dashboard Cite

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Analysing an Analytical Solution Model for Simultaneous Mobility

Abstract: ABSTRACT

Cited by 1 publication

References 12 publications

Planning and Optimization of Tracking Areas for Long TermEvolution Networks

Planning and Optimization of Tracking Areas for Long TermEvolution Networks

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