Handoff using Machine Learning Techniques
P. Sai Krishna, K. Sai Harsha Vardhan Reddy, K. Srikar, G. Prasad Acharya, DR. Rama Swamy · Zenodo (CERN European Organization for Nuclear Research) · 2022
This paper demonstrates about Implementation of Handoff Techniques through Machine Learning Algorithms in Tele communications. A handoff is the process of transferring an active call or data session from one cell in a cellular network to another, or from one channel within a cell to another. Cellular networks are made up of cells, each of which can provide telecommunications services to customers roaming through the network. Each cell has a limited region and number of subscribers it can serve. A handoff occurs when any of these two thresholds is reached. When a certain mobile tower's capacity is exceeded, an existing or new call from a phone must be transferred to another cell tower that covers the same geographical area as the existing cell tower. A well-executed handoff is essential for providing continuous service to a caller or data session user. Using Machine learning algorithms. The present methodology examines the accuracies generated by three popular decision-making algorithms namely Logistic Regression, Decision trees, Random Forests.