This paper proposes a probabilistic interference constraint method with a radio environment
map (REM) for spatial spectrum sharing. The REM stores the spatial distribution of the …

Machine learning (ML) and artificial neural networks (ANNs) have been successfully applied
to simulating complex physics by learning physics models thanks to large data. Inspired by …

Radio maps are expected to be an essential tool for the resource optimization and
management of 5G automotive. In this paper, we consider the problem of radio map …

Coverage planning and optimization is one of the most crucial tasks for a radio network
operator. Efficient coverage optimization requires accurate coverage estimation. This …

Coverage extension and prediction has always been of great importance for mobile network
operators. For coverage extension, the empirical and analytical path loss models assist in …

Minimization of drive test (MDT) allows coverage estimation at a base station by leveraging
measurement reports gathered at the user equipment (UE) without the need for drive tests …

Coverage optimization is an important process for the operator, as it is a crucial prerequisite
toward offering a satisfactory quality of service to the end users. The first step of this process …

The accuracy of measurement-driven mobile coverage maps depends on the quality,
density and pattern of the signal strength observations. Thus, identifying an efficient …

In computer networking, having limited buffer size is one of the vital causes of splitting the
messages into smaller frames to be then transmitted over the network. Increasing the buffer …

During the last decade a lot of effort has been spent on cellular network optimization to
improve network capacity and end-user Quality of Service (QoS). Coverage analysis …