Mobility Robustness Optimization Using ANN for Call Drop Prediction
Divya Mishra, Suryakant Yadav · Journal of Emerging Technologies and Innovative Research · 2020
Call drop in a mobile network is a much-unexpected phenomenon that is facing by every mobile consumer in today’s era even society is going to adopt 5G and 6G. This issue has not been resolved till now. Many intellectuals and academicians are currently in practice to reduce call drop and they proposed many proposals but still call drop rate is 62% according to a telecom survey. This research paper is giving an approach to minimize call drop during the time of traveling. The proposed model will be helpful to predict call drop which is based on few common parameters that are catching by the nearest base station during handover. This research paper is focused on mobility robustness optimization using an artificial neural network for call drop prediction. Mobility robustness is an important feature of a self-optimizing network and it can be implemented by using deep learning artificial neural network which is well famous for automatic feature extraction, classification, and prediction.