Title
REM: Revisiting a cognitive tool for virtualized 5G networks
Abstract
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.
Year
DOI
Venue
2016
10.1109/ICT.2016.7500411
2016 23rd International Conference on Telecommunications (ICT)
Keywords
Field
DocType
limited data communications,REM,high-level architecture,radio environment maps,spectrum management,NFV principles,network functions virtualization,SDN,software-defined network,mobile networks,telecommunications industry,mobile data traffic,virtualized 5G networks,cognitive tool
Mobile computing,Wireless network,Spectrum management,Telecommunications,Computer security,Computer science,Public land mobile network,Computer network,Radio access network,Mobile broadband,Cognitive network,Cognitive radio
Conference
Citations 
PageRank 
References 
1
0.39
14
Authors
3
Name
Order
Citations
PageRank
Adrian Kliks1487.09
Leonardo Goratti233437.38
Tao Chen342931.76