A multi-device and multi-operator dataset from mobile network coverage on Android devices

The demand for mobile coverage with adequate signal quality has triggered criticism due to the maturity of the Internet's diffusion in today's society. However, with the deployment of 5G networks, even 5G NSA by 4G LTE, the complexity of the operating environment of mobile networks has increased. To evaluate the behavior of mobile networks in terms of signal quality and other important metrics for mobile telephony, we developed a dataset consisting of 33 radio parameters that can collect up to 736,974 records generated daily by smartphones and tablets. The dataset comprises samples collected in cities situated on the banks of the Amazon and Negro rivers. To create the dataset, an application was designed for the Android operating system using the Kotlin programming language, which can collect data in real time and generate a CSV file. After post-processing the collected data with data science techniques, the filtered dataset was stored in the Mendeley public repository. We divided the data into three regions: the metropolitan area of Manaus, the middle Solimões River, and the middle Amazonas River. To improve the performance of the experiments, the database was separated according to the cities and locations collected.