Using Data to Drive Networking
We are interested in exploiting data science and machine learning to drive network optimization from design to deployment to operations. Our long-term goal is to develop new algorithms to tackle complex high-dimensional optimization problems in wireless networks. The €1.1m project spans 4 years and involves universities and SMEs from Europe, USA, and China. You can read on to find out more about these projects below.
TRAFFIC & MOBILITY MODELS
In an effort to gain a better understanding of the world around us, we have recently begun to use structured data analytics tailored to urban geography as a new technique to investigate human data demand and mobility patterns. We are currently looking to expand this work by collaborating with other labs who have data and use models to drive proactive optimization.
MINING CONSUMER EXPERIENCE
Consumer experience and satisfaction drive profit margins and the wider digital economy. We have developed Natural Language Processing tools specifically to target wireless consumer satisfaction. A major advantage of social media analysis is to reduce customer feedback lag and directly use the data to inform infrastructure design and deployment.
NETWORK SELF ORGANISATION
As we increase network complexity, we must allow networks to self-organize and optimize. Using data from traffic demand and consumer experience, we can personalize network services. In turn, this can further inform and improved data collection.
MOBILE EDGE CACHING & COMPUTING
Develop mechanisms and exploit node storage capabilities for proactive caching of content closer to the end-users, improve content delivery, and reduce congestion in the backhaul. Develop proactive caching algorithms for D2D communications and support user-end MEC.
University of Warwick
Coordinator & Principle Investigator
Associate Professor and Turing Fellow at the University of Warwick. Expertise: Signal Processing, Network Science, Machine Learning.
Co-Coordinator & Chief Scientific Officer
Prof. Jie Zhang is an internationally recognized leader in small cell network planning and operations. He founded Ranplan, now a Nasdaq listed company.
WINGS is an SME that focuses on the development of software for various vertical sectors through advanced wireless, cloud/IoT, big data and security technologies.
University of Sheffield
Reader. Experienced, trustworthy, fun. Mobility models, handovers, radio resource management. Loves hugging small cells.
His research interests are in the fields of mobile networking and the characterization of user mobility in wireless access and spontaneous networks.
Yue Wu is a lecturer at ECUST specializing in optimization and cloud-RAN.
Zubair Shafiq is an Assistant Professor of Computer Science at the University of Iowa.
Associate Professor at Zhejiang University.
5G MULTISCALE MOBILITY: A LOOK AT CURRENT AND UPCOMING MODELS IN THE NEXT TECHNOLOGY ERA
IEEE Vehicular Technology Magazine
DATA-DRIVEN DEPLOYMENT AND COOPERATIVE SELF-ORGANIZATION IN ULTRA-DENSE SMALL CELL NETWORKS
DEEP LEARNING FOR INTERFERENCE CANCELLATION IN NON-ORTHOGONAL SIGNAL BASED OPTICAL COMMUNICATION SYSTEMS
Progress In Electromagnetics Research Symposium
ENHANCED 5G COGNITIVE RADIO NETWORKS BASED ON SPECTRUM SHARING AND SPECTRUM AGGREGATION
IEEE Transactions on Communications