Advances in low-power wireless communications and microelectronics make a great impact
on a transportation system and pervasive deployment of roadside units (RSUs) is promising …

This paper presents a machine learning-based framework for the predictive deployment of
unmanned aerial vehicles (UAVs) as flying base stations (BSs) to offload heavy traffic from …

In this paper we propose a stochastic model to predict user throughput in mobile networks.
In particular, the model accounts for uncertainty such as random phenomena (eg, fast …

To minimize battery drain due to background communication in cellular-connected devices
such as smartphones, the duration for which the cellular radio is kept active should be …

In smart cities, green cellular networks play a crucial role to support wireless access for
numerous devices anywhere and anytime with efficiency and sustainability. Because base …

Bridging the advantages of differential privacy in both centralized model (ie, high accuracy)
and local model (ie, minimum trust), the shuffle privacy model has potential applications in …

The performance of Mobile Broadband (MBB) services of Fourth Generation (4G) and Third
Generation (3G) mobile networks over urban morphology is studied in Malaysia based on …

Using heterogeneous data sources collected from one of the largest 3G cellular networks in
the US over three months, in this paper we investigate the usage patterns of mobile data …

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 …

Time division multiplexing passive optical network (TDM-PON) technologies are viewed as
an attractive solution for flexible and cost-efficient mobile front-haul for cloud radio access …