Social Spider Algorithm-based Approach for Propagation Model Optimization. Application to Yaounde Town

The propagation models are used to forecast the influences of terrains and artificial environments on path loss. They are the basis of coverage planning. Good models ensure the precision of planning. With the deployment of 4G network worldwide, operators need to plan the coverage of their network efficiently, in order to minimize the cost and improve the quality of service. In this paper, the standard K factors model is taken into account to develop a method for tuning propagation models based on the social spider algorithm. The data is collected on the existing CDMA2000 1X-EVDO rev B network in the city of Yaoundé. The root mean squared error (RMSE) between actual measurements and radio data obtained from the prediction model developed is used to test and validate the technique. The values of the RMSE obtained by the new model and those obtained by the standard model of OKUMURA HATA in urban areas are also compared. Based on RMSE value from the optimized model and OKUMURA HATA, it can be concluded that the new model developed using the social spider algorithm performs better than the OKUMURA HATA model and is more accurate. The new model proposed on Social spider algorithm is more representative of the local environment. This new evolutionary algorithm prove its performance and can be used anywhere to optimize existing propagation models.