IMPROVING THE PERFORMANCE OF CELLULAR SYSTEM USING OPTIMAL SMALL CELLS DEPLOYMENT TECHNIQUE

Deciding on the most suitable location for cell deployment continues to pose significant challenges for network administrators. Despite the operation of numerous cell sites, customers often experience poor quality of service. A major contributing factor is the inadequate consideration of critical parameters such as population density, terrain characteristics, and interference patterns during the deployment process. This study developed a new cell deployment model using network information collected from areas with diverse terrain characteristics. The data was analyzed and used to train a linear regression model for predicting network performance metrics. The prediction outputs served as the foundation for a smart, decision-based framework for cell deployment. This framework was implemented as a desktop application capable of real-time network testing and cell deployment. The model was developed using MATLAB’s regression learner application and integrated with JavaScript programming for seamless functionality