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8th Training School

8th IC1004 Training School 
"From hetnets to cloud radio access networks"

April 21-23, 2015
University of Luxembourg
Local organizer: Symeon Chatzinotas
Technical organizers: Lucio Ferreira (INOV-INESC) and Silvia Ruiz (UPC)

Cloud computing technology has emerged as a promising solution for providing high energy efficiency together with gigabit data rates across software defined wireless communication networks, in which the virtualization of communication hardware and software elements place stress on communication networks and protocols.

Future Networks architectures are evolving to become to ever more flexible, developing towards the Cloud RAN concept, based on technologies such as distributed antenna systems, and evolving beyond it towards what can be called “ultra-flexible RANs”. C-RAN means a centralized processing, collaborative radio, real-time cloud computing and clean RAN systems. C-RAN brings to RAN the advantages of the cloud: resource-sharing, elasticity, on demand and pay-as-you-go.

Cloud RAN concept is expanded to include also EPC (Evolved Packet Core) functionalities, in what could be called Network Virtualisation, which refers to the capability of partitioning and/or pooling underlying physical resources or logical elements in a network, usually associated with the concepts of software-defined networking (SDN) and cloud services.

There are significant technical issues that still need to be addressed for successful rollout and operation of C-RAN and Virtual Networks. This training school brings together academic and industrial researchers to explain from the basis to the technical challenges and recent results related with C-RAN.

Introduction and challenges of today’s RAN
Green and Cooperative HetNetsSON in HetNets
Architecture of C-RAN
BTS splitting in BBU and RRH
Technical challenges of C-RAN
Operator view of C-RAN
Optical Transport Networks
Optical Fronthaul between BBUs and RRHs
Virtual Networks
Virtualisation in RAN, Cor&Transport
Recent Advances and Testbeds
Cooperative Transmission/Reception and Dynamic Radio Resource Allocation
SDR and Joint Signal Processing

Ph.D. students, researchers, and practicing engineers.

To be updated soon


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