REM: Revisiting a cognitive tool for virtualized 5G networks

The evidence that mobile data traffic is enormously increasing is forcing the whole telecommunications industry to rethink most of the paradigms which have driven until now the design of mobile networks, traditionally very efficient for voice and limited data communications. It is foreseen that 5G technology will introduce disruptive changes with respect to how radio resources are managed and consumed. In past years cognitive radio made its way to enable more intelligent and autonomous wireless networks but it has encountered several practical problems which have slowed down the massive adoption of this technology. Recently, an apparent turnaround has risen from the adoption of Software-Defined Network (SDN) and Network Functions Virtualization (NFV) principles. In this work we shall restart from known cognitive radio concepts which have been innovative in terms spectrum management in past years, paying particular attention to the concept of Radio Environment Maps (REMs). The main contribution of this work is hence to propose a high-level architecture in which SDN and NFV are the enablers that will facilitate the adoption of REM as the tool for spectrum management, since 5G will exhibit unprecedented levels of flexibility in managing different types of resources.