Handoff using Machine Learning Techniques


Authors : P. Sai Krishna; K. Sai Harsha Vardhan Reddy; K. Srikar; DR. Rama Swamy; Dr. Gobinda Prasad Acharya

Volume/Issue : Volume 7 - 2022, Issue 3 - March

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3iWoLMo

DOI : https://doi.org/10.5281/zenodo.6406715

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.

Keywords : Handoff, roaming, cellular networks, Logistic Regression, Decision trees, Random Forests.

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