BANYAN - Big dAta aNalYtics in 5G data-driven radio Access Networks (DIT.AD003.084)
Project areaInternet del futuro (DIT.AD003)
Structure responsible for the research project
The BANYAN project is designed to address major open issues towards the realisation if datadriven
5G RAN, as follows: - modelling and forecasting macroscopic high-dimensional mobile
traffic patterns observed at RAN for individual services, at multiple scales in time and space; -
geo-locating and characterising in-building mobile traffic patterns observed at RAN; - designing
data-driven strategies for the allocation of 5G RAN resources; - designing data-driven policies
for the orchestration of 5G RAN resources to suit service requirements and dynamics via
network slices; - coordinating outdoor and indoor 5G, multi-RAT and heterogeneous networks
to meet user QoS requirements.
"The measurable research objectives for the BANYAN project are as follows:
o Develop algorithms based on multivariate analysis and deep learning (DL) to forecast macroscopic spatial-temporal mobile service demands caused by user traffic and mobility;
o Develop data analytics based geo-location algorithms to geo-locate and characterise in-building mobile traffic demands at a high level of detail (e.g., including the exact time, building and floor where traffic is generated); and
o Develop data analytics-driven mechanisms to proactively optimize the orchestration of virtualized 5G RAN resources, to coordinate outdoor and indoor networks and to coordinate multi-RAT indoor networks.
In addition to the above research objectives, the project has the following doctoral training objectives:
o Train a group of 5 outstanding early-stage researchers (ESRs) for both academia and industry.
o Establish a virtual European centre of excellence for data-driven 5G RAN research that will exist well beyond the end of this project, reducing the fragmentation and facilitating long-term transnational and inter-sectoral collaborations."
Start date of activity
Last update: 08/12/2023