This app takes some sample LTE measurement data inputs and predicts the resultant Throughput based on the selected environment condition.

The data was source from the Beyond Throughput: a 4G LTE Dataset with Channel and Context Metrics paper. Only the pedestrian dataset was used in this example.

Input such as CQI, SNR, RSRP can be used to estimate a resultant LTE Throughtput.

• The app allows selection of input and output variables via drop down menu.
• It also incldudes a slider to select a specific input value
• There are 4x ouput tabs which will update based on the variable selection
  • Scatterplot
  • Distribution
  • Model Summary
  • Data
• The first tab documentation is static and contains the instruction for usage

Detail of how to operate the app can be found under the documentation tab.

The uses a simple linear regression model based on the inputs to estimate the ouput. The intended use is for throughput prediction but it can also be used to estimate the RF environment conditions based on the throughput value inputted

The app itself is located here: https://tsunamimor.shinyapps.io/SampleShinyLtePrediction/