Accurate received power prediction is important to wireless network planning and
optimization, and appropriate channel modeling approach is highly demanded. The existing …

This paper proposes a method to predict received power in urban area deterministically,
which can learn a prediction model from small amount of measurement data by a simulation …

In this paper, a new method for radio wave propagation prediction based on BP neural
network and simplified path loss model is proposed. The method is based on a large amount …

In this article, artificial neural networks are applied to data measured on a wireless indoor
mobile communications scenario for 768 MHz transmission. Three multilayer perceptron …

In this paper, we propose a measurement-based spectrum database using model classifier.
In the radio propagation, path loss is the fundamental factor to recognize the coverage area …

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 …

This paper aims to evaluate the average uplink transmit power of users' equipment in
commercial 4G and 5G networks. In the case of the 4G network, the analysis was done …

This paper describes a deep neural network (DNN) based method for forecasting short-term
hospital electricity usage. In Experiment One, a 4-layer DNN stack auto-encoder (SAE) …

Throughout the wireless communication network planning process, efficient signal reception
power estimation is of great significance for accurate 5 G network deployment. The wireless …

When deploying communication systems, an accurate wireless propagation model is
important to ensure the quality of service covering the region. Due to the complex radio …