|Title||Clustering Based User Allocation in 5G Networks|
|Publication Type||Conference Paper|
|Year of Publication||2021|
|Authors||Bouras, C, Kalogeropoulos, R, Sina, I|
|Conference Name||The 2021 IEEE International Symposium on Networks, Computers and Communications (ISNCC 2021), October 31 – November 2, 2021, Dubai - UAE|
Machine Learning is an extremely efficient technique for solving complex problems without the use of traditional programming but rather enabling machines to learn from an input of data and train them to cope with various problems. The rapid growth in the number of active mobile devices, mobile applications and services dictate an efficient utilization of mobile and wireless networking infrastructure. Communication networks need to evolve and valorize Machine Learning methods in order to process large volumes of data without introducing excessive time delay in these computations. Upcoming 5G systems are expected to be the first network infrastructure to support exploding mobile traffic volumes and Machine Learning techniques can be used in order to help manage the rise in data volumes. We present a mechanism for resource allocation in mobile and wireless networks, that effectively utilizes Machine Learning techniques.
Clustering Based User Allocation in 5G Networks