Prediction of Received Signal Power in Mobile Communications Using Different Machine Learning Algorithms:A Comparative Study

In this paper, we apply and compare various machine learning techniques to predict the received signal strength (RSS) in cellular communications. We generate the training set using experimental measurements from an unmanned aerial vehicle (UAV). We make a prediction model for the RSS using five base learners. We create a new ensemble method that averages the results from these five base learners. The proposed model outperforms all the original base learners. The obtained numerical results are compared with the original data from the test dataset using representative performance indicators and exhibit good precision.