Open AccessData driven optimisation of small cell depolyment
Author(s) -
Chen Bozhong,
Zhang Zitian,
Chu Xiaoli,
Zhang Jie
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2019.2976
Subject(s) - software deployment , computer science , base station , cluster analysis , computer network , mobile social network , cellular network , hot spot (computer programming) , mobile telephony , mobile broadband , mobile computing , real time computing , mobile radio , telecommunications , wireless , artificial intelligence , operating system
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.