Future network deployment strategy based on user behavior analysis and stochastic geometry

In the future Ultra Dense Network (UDN), deploying new small cells within macro cells is a solution to improve the User Data Rate (UDR). How and where to deploy the small cells are the questions network operator is facing. The paper presents strategies based on stochastic geometry and user behavior analysis to solve the problems separately. A smartphone dataset that reflects real-time network conditions is analyzed, based on which a process is conducted and results are demonstrated to give advice for network suppliers.

[1]  Tiankui Zhang,et al.  Stochastic geometry based energy-efficient base station density optimization in cellular networks , 2015, 2015 IEEE Wireless Communications and Networking Conference (WCNC).

[2]  Hans-Peter Kriegel,et al.  LOF: identifying density-based local outliers , 2000, SIGMOD '00.

[3]  Jeffrey G. Andrews,et al.  A Tractable Approach to Coverage and Rate in Cellular Networks , 2010, IEEE Transactions on Communications.

[4]  Daniel Crespo,et al.  Domain-size distribution in a Poisson-Voronoi nucleation and growth transformation. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[6]  Xinyu Gu,et al.  User average data rate analysis in future dense small cells , 2015, 2015 IEEE 16th International Conference on Communication Technology (ICCT).

[7]  Ai-Min Yang,et al.  Framework of Clustering-Based Outlier Detection , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.

[8]  Yong Shi,et al.  Detecting Clusters and Outliers for Multi-dimensional Data , 2008, 2008 International Conference on Multimedia and Ubiquitous Engineering (mue 2008).

[9]  Qingzhong Li,et al.  SLOF: Identify Density-Based Local Outliers in Big Data , 2015, 2015 12th Web Information System and Application Conference (WISA).

[10]  Ji Zhang,et al.  Advancements of Outlier Detection: A Survey , 2013, EAI Endorsed Trans. Scalable Inf. Syst..