Network upgrades in mass-scale mobile network environments can be very cumbersome and typically involve a network operator creating a unique upgrade plan to execute, which can be costly and time consuming. In order to improve the efficiency and reduce the cost of mobile network upgrades and also provide improved service assurance with the least risk of service disruptions, a machine learning (ML) based mathematical model is proposed herein to provide upgrade clustering that can be utilized to facilitate mobile network upgrades.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.