Data driven optimisation of small cell depolyment. Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: Chen, Bozhong; Zhang, Zitian; Chu, Xiaoli; Zhang, Jie
• Is Part Of: Electronics letters. Volume 56:Issue 1(2020)
• Page Start: 48
• Page End: 50
• Publication Date: 2020-01-01
• Subjects: telecommunication traffic -- social networking (online) -- Poisson distribution -- pattern clustering -- cellular radio -- mobility management (mobile radio) -- quality of service -- normal distribution -- telecommunication computing; base station -- social network data -- mobile traffic hot‐spots -- noise algorithm -- clustered hot‐spots -- macro base stations -- SBS deployment -- mobile communication network -- random SBS deployment -- data driven optimisation -- cell depolyment -- carrier data -- online social networks -- density‐based spatial clustering -- quality of service -- normal distribution -- Poisson distribution; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2019.2976
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : Increasingly popular online social networks contribute to the massive growth in mobile traffic. The authors find that social network data, which is easier to obtain than carrier data, can be used to optimise the deployment of small base station (SBS). In this Letter, the authors propose a framework based on analysing social network data to identify and cluster mobile traffic hot‐spots by using the density‐based spatial clustering of applications with noise algorithm. By comparing the clustered hot‐spots with the existing macro base stations' locations, they identify where additional SBSs need to be deployed and show that such deployment can effectively improve the quality of service. The proposed simulation results show that the SBSs deployment around hot‐spot has relatively better user received signal power on mobile communication network than random SBS deployment following the normal distribution or the Poisson distribution.