Radio Resource Management for Connected Vehicles

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Project Detail:

Connected vehicles are one of the most fast-growing sectors of the expanding Internet of Things. It is forecasted that connected intelligent vehicles will account 10% in Europe by 2020. Connected vehicles will have technical, societal and economic impact as they can alleviate traffic congestion, reduce environmental pollution, and dramatically improve road safety.

However, the sheer volume of data, the stringent latency and ultra-reliability requirements, lack of
infrastructure support, high mobility and the unpredictable weather conditions make reliable and fast vehicular communications a serious technical challenge in the next-generation mobile networks research. Existing vehicular communications mainly employ the legacy IEEE 802.11p standard or the more recent Long Term Evolution (LTE) standard, but these standards were optimised for static or low-mobility environments and cannot satisfy the latency and reliability requirements for future vehicular networks.

This PhD project aims to develop novel communications protocols and resource allocation algorithms to enable the high-rate and reliable connections to vehicles in a scalable and cost-effective way. This project will take advantage of recent progress in areas such as device-to-device communications, content caching, vehicle social networks, software-defined networks (SDN), network function virtualization (NFV), mobile edge computing, and big data analysis to design the required communications technology for intelligent vehicles.

Find out more: please see the website https://sites.google.com/site/eegzheng

Entry requirements:
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in electrical/electronic engineering, computer science, applied mathematics or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: wireless communications, signal processing.

How to apply:

All applications should be made online at http://www.lboro.ac.uk/study/apply/research/. Under programme name, select ‘Electronic and Electrical Engineering’

Please quote reference number: GZ0501172

Application details:
Reference number: GZ0501172
Preferred Start date (if any): 1 April or 1 July 2017

Supervisors:
Primary supervisor: Gan Zheng
Secondary supervisor: Sangarapillai Lambotharan

Contact details:
Name: Gan Zheng
Email address: [Email Address Removed]
Telephone number: +44(0)1509227035