4G Signal RSSI Recommendation System for ISP Quality of Service Improvement

Abstract

4G Signal RSSI Recommendation System is one of the monitoring methods. The usage rate of local users improves the quality of traffic signals to cycle to receive increased traffic. This paper proposed a method for Prediction and the traffic of data rates used within the area at each location. The result of the proposed approach comparing the performance of models was: the RMSE Gradient Boost Tree, Decision Tree, and Random Forest were 0.291, 0.316 and 0.346, respectively. The correlation will be 0.976, 0.971, and 0.966 for Gradient Boost Tree, Decision Tree, and Random Forest, respectively, and the accuracy of Gradient Boost Tree, Decision Tree, and Random Forest were 97.8%, 97.4%, and 97%, respectively. The results of ensemble learning methods, the RMSE, correlation, and accuracy were: 0.312, 0.972, and 97.5%.