Open AccessTracking areas planning based on spectral clustering in small cell networks
Author(s) -
Lin Qiangqiang,
Tu Shanshan,
Waqas Muhammad,
Rehman Sadaqat ur,
Chang Chin Chen
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0306
Subject(s) - computer science , paging , handover , cluster analysis , overhead (engineering) , signalling , graph , spectral clustering , distributed computing , real time computing , computer network , data mining , artificial intelligence , theoretical computer science , mathematics , mathematical economics , operating system
In future small cell networks, tracking areas (TAs) that are defined for location management will be updated frequently to cope with the massive signalling overhead. In this study, a TA planning method based on spectral clustering is proposed to minimise the network signalling overhead. Firstly, handover and paging statistics are simulated to construct a series of graphs showing user mobility and traffic. Then, the TA planning problem is formulated as a classical graph partitioning problem. Finally, a new TA planning method based on spectral clustering is used to build the new TA plan. Simulation results show that the proposed method can effectively reduce the system location update rate and signalling overhead, and improve the system performance.