Fine-tuning of Cost-231 Hata Path Loss Model for LTE Network: The Case of 4 Kilo Area

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The demand for increased mobile phone subscribers requires an efficient radio network planning that involves an accurate prediction of path loss. For Long Term Evolution (LTE) mobile network, empirical path loss models such as Cost-231 Hata model are used to predict the loss in a propagation environment. These models depend on frequency of operation, terrain profile of an environment, transmitter and receiver heights and distance from a base station. As the propagation environments continuously changes, these models need to be fine-tune continuously. In this thesis, LTE 1800 MHz mobile signals that are recorded experimentally, for four eNodeB in Addis Ababa 4Kilo area, are considered for path loss analysis. A drive test methodology was adopted for data collection and the measuring tools used for the test was a hand phone installed with Nemo Handy software. The received signal strength and path loss were recorded in the form of logs which can later be extracted with ACTIX software analyzer in to a suitable form of Excel sheet. The measured path loss is determined from the collected data. Cost-231 Hata model was optimized because it is the existing model in Ethio telecom. In order to improve the prediction accuracy, this model is statistically optimized using Least Square algorithm. The initial offset parameter and slope of the model curve in Cost-231 Hata model are considered and new model parameters are estimated. The optimized path loss predicting model is compared with the original Cost-231 Hata model and MATLAB R2016a Simulation software was used for this purpose. The performance of the optimized model is evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The optimized model gives a RMSE = 0.039 dB and MAPE = 0.037% as compared to Cost-231 Hata model with a RMSE = 0.49 dB and MAPE = 0.47%. The results show that the errors are least for the optimized Cost-231 Hata model, compared to the original Cost-231 Hata model. Hence, the optimized model is recommended for better deployment and gives an accurate path loss prediction in the urban area of 4Kilo.



Path Loss Model, Long Term Evolution, Least Square Tuning Algorithm, Cost-231 Hata model, RMSE, MAP