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QoE-estimation-4G-Networks

Overview

This project aims to estimate the user satisfaction in 4G networks, relative to the usage of YouTube Service. This project takes as input Crowdsourcing Data (i.e., data measured directly at user's terminals) and will output the corresponding user satisfaction class.

Dataset

You can find some data samples available in two .csv files.

Features

In the following you can find a list of the features used to estimate user satisfaction:

  • Max_RSRQ
  • Cumulative_YoutubeSess_LTE_DL_Volume
  • Service_Availability_Ratio_LTE
  • Max_SNR
  • Cumulative_YoutubeSess_LTE_DL_Time
  • Youtube_Time_Percentage_LTE
  • Cumulative_Lim_Service_Time_LTE
  • Total_Service_Time_LTE
  • Cumulative_Full_Service_Time_LTE
  • Preferred_Network_Type
  • Cumulative_No_Service_Time_LTE
  • Avg_Youtube_Time_LTE
  • Avg_Youtube_Volume_LTE

Algorithms

The following algorithms have been used in this project:

  • Bayesian optimization
  • Grid search
  • XGBoost
  • Random Forest
  • Decision Tree

Releases

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Packages

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