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Planning and Optimization of Tracking Areas for Long Term Evolution Networks
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology.
2014 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Along with the evolution of network technologies, user’s expectations on performance and mobile services are rising rapidly. To fulfill the 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 re-assigning some cells to TAs other than their original ones. For solving the resulting problem, an algorithm based on repeated local search is developed.

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 Pareto-optimality. Solving the problem delivers a host of potential trade-offs 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 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 the use of overlapping TAL for congestion mitigation, is performed and compared to the static configuration by using a case study.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. , 171 including Appendix A and B p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1588
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-105924DOI: 10.3384/diss.diva-105924ISBN: 978-91-7519-360-1 (print)OAI: oai:DiVA.org:liu-105924DiVA: diva2:712248
Public defence
2014-05-05, TP1, Täppan, Campus Norrköping, Linköpings universitet, Norrköping, 10:15 (English)
Opponent
Supervisors
Available from: 2014-04-14 Created: 2014-04-14 Last updated: 2014-04-15Bibliographically approved

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Modarres Razavi, Sara

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