Intelligent, self-configurable device-to-device communications for heterogeneous integrated connected-car autonomy

GLOBAL RESEARCH INSTITUTES

  • Intelligent, self-configurable device-to-device communications for heterogeneous integrated connected-car autonomy

Intelligent, self-configurable device-to-device communications for heterogeneous integrated connected-car autonomy

Principal Supervisor: Dr. Youngwook Ko

Second Supervisor: Dr. Michail Matthaiou

+ Project Description

Internet of Things (IoT) market will reach $1.7 trillion by 2020, growing to 75 billion connected devices in 5 years. Within IoT, short-range device-to-device (D2D) communications promise to interconnect devices with a significant increase in data traffics (a 1000-fold increase by 2020).

Due to rapidly increasing demand on the connected-devices with machine learning, very intelligent D2D communications have become very popular in a wide range of IoT services (e.g., electric car, unmanned factory automation, healthcare monitoring, hazardous environments sensing, disaster resilience). Today D2D is however not necessarily the best solution in many situations, particularly in dense, distributed wireless sensing, where autonomous D2D approach would be better choice with no or less human intervention. In general, devices suffer from the limitation of hardware and computational capability. Also, due to the finite power, future devices are challenged to provide the reliability at low power in a small device form, being deployed mainly in confined spaces rather than open spaces. This cause significant interference problems. For example, it is envisioned that 1000 devices per person will be deployed by 2020.

This PhD programme will investigate new self-organising multiple access algorithms for heterogeneous connected-devices where a variety of machines within an electric vehicle coexist being interferer to other and interfere by other, simultaneously. This project aims to develop opportunities for integrating the pricing of local machine resource and the cognitive cooperation principles so that a full connected-car autonomy can be enabled, taking into account fidelity-flexibility trade-offs at a variety of machine type fading environments.

+ How to Apply

Applicants should apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/

+ Contact Details

Supervisor Name: Dr Youngwook Ko            
Address:

Queens University of Belfast
School of EEECS
Centre for Wireless Innovation (CWI)
NI Science Park
Queens Road,
Belfast,
BT3 9DT

Email:

y.ko@qub.ac.uk

Tel:

+44 (0)28 9097 1772