CORDIS
EU research results

CORDIS

English EN

Data Aware Wireless Networks for Internet of Everything

Project information

Grant agreement ID: 778305

Status

Ongoing project

  • Start date

    1 December 2017

  • End date

    30 November 2021

Funded under:

H2020-EU.1.3.3.

  • Overall budget:

    € 1 107 000

  • EU contribution

    € 850 500

Coordinated by:

THE UNIVERSITY OF WARWICK

United Kingdom

Objective

Whilst traffic demand is increasing exponentially, network operators’ revenue remains flat. There is an urgent for data driven 4G/5G networks.

In this project, we exploit heterogeneous big data analytics to optimize both the deployment and operations of wireless networks. We design protocols that enable future Data Aware Wireless Networks (DAWN) for enabling a new age of Internet of Everything (IoE). The proposal has been developed to address the following open issues in data driven flexible systems:
• How to characterize user mobility and wireless data traffic patterns
• How to infer user Quality-of-Experience (QoE) from combining data sets
• How to use data analytics to assist cell planning
• How to use data driven techniques to optimise the network using Self-Organising-Network (SON) algorithms
• How to optimally cache data to accelerate and optimise data storage and transmission.

The research objectives of the DAWN4IoE project are as follows:
• Develop appropriate spatial-temporal structured filters to combine different data sets and infer both human location/mobility and digital data demand patterns.
• Develop appropriate machine-learning techniques for unstructured natural language processing (NLP) to understand consumer experience for different service categories.
• Design algorithms to integrate the new data analytics techniques with current state-of-the-art deployment techniques to assist HetNet planning, performance prediction, and deployment
• Design mechanisms to integrate structured and unstructured data analytics to drive SON algorithms for radio resource management and smart antenna elements.
• Design algorithms to optimally cache data leveraging on mobile edge computing (MEC).

Achieving the above objectives will provide crucial inputs for 5G/B5G data-driven flexible wireless network design and both increase network capacity by 50% and decrease operation costs by 20-30% (compared with non-data driven networks).
Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

Coordinator

THE UNIVERSITY OF WARWICK

Address

Kirby Corner Road - University House
Cv4 8uw Coventry

United Kingdom

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 270 000

Participants (4)

RANPLAN WIRELESS NETWORK DESIGN LTD

United Kingdom

EU Contribution

€ 202 500

CONSIGLIO NAZIONALE DELLE RICERCHE

Italy

EU Contribution

€ 108 000

WINGS ICT SOLUTIONS INFORMATION & COMMUNICATION TECHNOLOGIES IKE

Greece

EU Contribution

€ 135 000

THE UNIVERSITY OF SHEFFIELD

United Kingdom

EU Contribution

€ 135 000

Partners (4)

Zhejiang University

China

EAST CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY

China

The University of Iowa

United States

Baicells Technologies Co., Ltd

China

Project information

Grant agreement ID: 778305

Status

Ongoing project

  • Start date

    1 December 2017

  • End date

    30 November 2021

Funded under:

H2020-EU.1.3.3.

  • Overall budget:

    € 1 107 000

  • EU contribution

    € 850 500

Coordinated by:

THE UNIVERSITY OF WARWICK

United Kingdom