Machine Learning algorithms to investigate mobile network coverage prediction accuracy in an urban environment

In our latest research, we applied several Machine Learning algorithms to investigate mobile network coverage prediction accuracy in an urban environment (Putrajaya, Malaysia).

We have collected extensive datasets (21,323 of them!) on 4G-related mobile network parameters based on drive tests using GNetTrack (Pro) around several locations in Putrajaya.

The datasets are open & available here: https://github.com/fazuwanfauzi/4G-LTE-RSRP-Prediction-Model

We hope the datasets encourage other wireless researchers to compare and apply their current research works based on the 4G mobile network urban environment, such as Putrajaya.

And this is the link to our latest paper in IEEE: Mobile Network Coverage Prediction Based on Supervised Machine Learning Algorithms | IEEE Journals & Magazine | IEEE Xplore

6 Likes