Tracking Area List Management Method Based on Overlapping Community Detection in Small Cell Networks

Abstract

The invention provides a tracking area list management method based on overlapping community detection in a small cell network. The method is mainly aimed at user location management in the small cell network, optimizes the signaling overhead of the network system, and provides a method for determining the TAL. For a given small cell network model after TA planning, the overall idea of ​​the method proposed by the present invention is to first count the tracking area location update and paging data of users in a specific time period and in a specific area; then the TAL management method It is modeled as a graph segmentation problem and a linear programming model is given; finally, an overlapping community detection algorithm based on game theory is applied to give a TAL structure.

Description

technical field [0001] The invention relates to the technical field of location management in communication technology, and mainly relates to a tracking area list (TAL, Tracking Area List) management method based on overlapping community detection. Background technique [0002] In the future small cell network, there will be a large number of mobile terminals, which will greatly increase the capacity requirements of the network. In large hotspot areas, such as shopping malls and stadiums, there will be a large number of mobile devices, so the intensive deployment of small cell base stations is imminent, and the subsequent ultra-dense networking applications will emerge. The future small cell network will densely deploy small cells featuring self-organization, low cost, and low power. With the miniaturization of small cell size and higher user density and mobility. All of these will significantly increase the location update frequency of mobile users, resulting in higher si...

AI Technical Summary

Problems solved by technology

[0005] Most of the above TAL-based location management methods generate different TALs for different mobile users, and the computational efficiency of these methods will drop sharply in a massive small cell deployment environment.

And most of them are based on the assumption of a regular pattern of the same size, shape and distribution of cells. Although the structured cell topology simplifies the analysis and calculation, they are seriously separated from the actual characteristics in real life, especially in small cell networks. deployment environment

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