01382nas a2200121   4500008004100000245005200041210005200093520093500145100002101080700002701101700001801128856011401146       2021                        eng d00aClustering Based User Allocation in 5G Networks0 aClustering Based User Allocation in 5G Networks3 aMachine 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.1 aBouras, Christos1 aKalogeropoulos, Rafail1 aSina, Ioannis  uhttp://telematics.upatras.gr/telematics/publications/clustering-based-user-allocation-5g-networks?language=en