On dynamic signaling congestion mitigation by overlapping tracking area lists

Mitigating signaling congestion of tracing user equipments (UEs), adaptively to the changes in UE location and mobility patterns is a challenging issue in mobility management of Long Term Evolution (LTE) networks. Signaling congestion usually occurs due to many UEs behaving in a similar manner, e.g., massive and simultaneous UE mobility in a train movement scenario. LTE networks allow the use of tracking area lists (TALs), each being a list containing multiple tracking areas (TAs). The overlapping TAL scheme has been previously used for signaling congestion mitigation for snapshot scenarios. For maintaining the improved performance over non-list-oriented TA configuration over time, an automatic dynamic configuration framework, which is a key aspect in Self-Organizing Network (SON), has been applied in this paper. We develop a linear programming model for optimal TAL configuration. Repetitively solving the model for different time intervals gives an evaluation framework on the performance of SON location management. Comprehensive numerical results are presented in this study using a large-scale realistic network scenario. The experiments demonstrate the effectiveness of the SON dynamic framework in reducing the total signaling overhead of the network compared to the static TA. Moreover, the overlapping TAL scheme significantly improves the performance of the network in the tracking area update congested scenarios over the conventional TA configuration.