Our objective
traffic management and safety

Proposal

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.

Objectives

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).

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