With IoT deployment accelerating in multiple sectors this is becoming a significant field for mobile operators, generating demand for effective ways of managing and monetizing all the additional users, devices and data traffic. Machine learning is being recruited across the protocol stack and in different scenarios to help operators and providers of services embrace this proliferating and often unwieldy field incorporating diverse devices, use cases and traffic profiles. Machine learning is featuring even at the MAC (media access control) layer to help optimize allocation of resources across the RAN and backhaul according to the use case and varying levels of traffic, helping to identify devices and predict demand over the immediate term. It is also figuring for security by helping…