In this paper we propose a highly efficient and very accurate method for estimating the
propagation pathloss from a point x to all points y on the 2D plane. Our method, termed …

In this paper we propose a highly efficient and very accurate deep learning method for
estimating the propagation pathloss from a point (transmitter location) to any point on a …

We describe a path loss characteristic prediction method we propose using a convolution
neural network (CNN). In high traffic environments such as the public squares in front of …

Deep learning (DL) has been recently leveraged for the inference of characteristics related
to wireless communication channels, such as path loss (PL). This paper presents how a …

Radio propagation modeling and path loss prediction have been the subject of many
machine learning-based estimation attempts. Our current work uses deep learning for the …

Several models using deep neural network (DNN) have been proposed to estimate the path
loss characteristics in the urban macrocell (UMa) environment, most of which use the height …

In modern wireless communication systems, radio propagation modeling has always been a
fundamental task in system design and performance optimization. These models are used in …

Not only has the volume of mobile traffic been increasing exponentially in recent years,
making various services available, such as IoT and connected cars moving at high speed …

Although various linear log-distance path loss models have been developed, advanced
models are requiring to more accurately and flexibly represent the path loss for complex …

Path loss prediction is essential for network planning in any wireless communication system.
For cellular networks, it is usually achieved through extensive received signal power …