Real Call Detail Records (CDR) are analyzed and classified based on Support Vector
Machine (SVM) algorithm. The daily classification results in three traffic classes. We use two …

Cellular communications are undergoing significant evolutions in order to accommodate the
load generated by increasingly pervasive smart mobile devices. Dynamic access network …

The information contained within Call Details records (CDRs) of mobile networks can be
used to study the operational efficacy of cellular networks and behavioural pattern of mobile …

The evolution of cellular technology development has led to explosive growth in cellular
network traffic. Accurate time‐series models to predict cellular mobile traffic have become …

5G communication will bring a surge traffic in cellular network. The traffic in cellular network
not only has strong variability by time, but also has strong spatio-temporal correlation, which …

With the rapid development of CDMA systems, mobile network based applications have
been undergone a tremendous growth in the past several years. The ability to accurately …

With the evolution of various new types of application services for mobile devices, cellular
operators have started providing multiple subscription plans to the mobile users. The plan …

Traffic learning and prediction is at the heart of the evaluation of the performance of
telecommunications networks and attracts a lot of attention in wired broadband networks …

Big data comprises a large volume of data (ie, structured and unstructured) stored on a daily
basis. Processing such volume of data is a complex task as well as the challenging one …

In this work we design and implement a Neural Network that can identify recurrent patterns
in various metrics which can be then used for cellular network traffic forecasting. Based on a …