Several orthodox approaches, such as empirical methods and deterministic methods, had
earlier been used for the prediction of path loss in wireless communication systems. These …

In optimization of wireless networks, path loss prediction is of great importance for adequate
planning and budgeting in wireless communications. For efficient and reliable …

The importance of wireless path loss prediction and interference minimization studies in
various environments cannot be over‐emphasized. In fact, numerous researchers have …

Path loss prediction models are vital for accurate signal propagation in wireless channels.
Empirical and deterministic models used in path loss predictions have not produced optimal …

Path loss prediction is of great significance for the performance optimization of wireless
networks. With the development and deployment of the fifth-generation (5G) mobile …

Artificial Neural Networks (ANNs) which are one of the main tools used in machine learning
have often been utilised in developing models for path loss modelling in recent times …

Path loss propagation models are critically needed for optimum planning and deployment of
wireless communication networks. However, the complexity exhibited by the propagated …

One of the most critical problems in a communication system is losing information between
the transmitter and the receiver. WiMAX (Worldwide Interoperability of Microwave Access) …

Machine learning models have been widely deployed to tackle the problem of radio
propagation. In addition to helping in the estimation of path loss, they can also be used to …

Propagation models are used extensively in signal prediction and interference analysis.
Peculiarity of these models gives rise to high prediction errors when deployed in a different …