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  Communication and computation cooperation (3C) for 5G and beyond networks (Advert Reference: RDF18/CIS/WANG)


   Faculty of Engineering and Environment

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  Dr K Wang  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Nowadays, more and more resource-hungry applications such as virtual reality services are coming into play in our mobile devices. However, due to the limited resources in terms of computing capacity etc, mobile devices are struggling in keeping up with the development of those computing-intensive applications. Furthermore, the growing popularity and increasing traffic of mobile devices poses an increasingly high burden on the existing communication networks, which becomes a big challenge for 5G networks. To address the above-mentioned problems, we believe that communication must collaborate closely with communication, as the famous information theorist Professor T. Cover once said, ‘communication is computation limited and computation is communication limited’. Thanks to the fast development of the cloud computing and virtualization techniques, more and more communication and service related functions may be realized and assisted by computation in cloud, as exemplified by the recent progress in cloud radio access networks (C-RAN), Mobile Edge Computing (MEC), Network Function Virtualization (NFV) and Network Slicing, etc. We envision that with the transition from conventional hardware-based infrastructure to a software-based environment, computing resource may be allocated more dynamically, conveniently and flexibly to the communications and other resource-intensive applications.

The aim of this project is first to look into the relations between communication and computation, and then research on how to allocate proper communication and computation resource to networks and users’ applications for 5G and beyond communications. Also, applications of 3C in Internet of Vehicles (IoV), Internet of Things (IoT), Unmanned Aerial Vehicle (UAV) may also be considered. New protocols, schemes or optimal resource allocation algorithms are expected to be developed and designed. The candidate is expected to have strong background in the following one or more areas or other related areas, such as wireless communications, computer networks, cloud computing, optimization theory. Strong background in mathematics and programming skills such as Maltlab, C/C++/Java is highly desired. Previous research experience, such as having publications is greatly appreciated.

Eligibility and How to Apply:
Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

For further details of how to apply, entry requirements and the application form, see:
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF18/…) will not be considered.

Deadline for applications: 28 January 2018

Start Date: 1 October 2018

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality and is a member of the Euraxess network, which delivers information and support to professional researchers.

Funding Notes

The studentship includes a full stipend, paid for three years at RCUK rates (for 2017/18, this is £14,553 pa) and fees.

References

Kezhi Wang, Kun Yang, Hsiao Hua Chen, Lianming Zhang, Computation Diversity in Emerging Networking Paradigms, IEEE Wireless Communications Magazine. 2017.

L Zhang, Kezhi Wang, Xuan Du, Kun Yang, Optimal task allocation in near-far computing enhanced C-RAN for wireless big data processing, IEEE Wireless Communications Magazine. 2017.

Haibo Mei, Kezhi Wang, Kun Yang, Multi-layer Cloud-RAN with Cooperative Resource Allocations for Low-latency Computing and Communication Services, IEEE Access, 2017

Kezhi Wang, Kun Yang, Cunhua Pan, Jiangzhou Wang, Joint Offloading Framework to Support Communication and Computation Cooperation, arXiv:1705.10384, 2017

Tong Li, C. Magurawalage, Kezhi Wang, et al, On efficient offloading control in cloud radio access network with mobile edge computing, IEEE ICDCS, 2017.

Kezhi Wang, Kun Yang, Resource Allocation Between Service Computing and Communication Computing for Mobile Operator, IEEE ICC, 2017.

Kezhi Wang, Kun Yang, Chathura Sarathchandra Magurawalage, “Joint Energy Minimization and Resource Allocation in C-RAN with Mobile Cloud”, IEEE Transactions on Cloud Computing, 2016.

Kezhi Wang, Kun Yang, Xinhou Wang, Chathura Sarathchandra Magurawalage, Cost-Effective Resource Allocation in C-RAN with Mobile Cloud", IEEE ICC, 2016.

Xinhou Wang, Kezhi Wang, Song Wu, Sheng Di, Kun Yang, Hai Jin. Dynamic Resource Scheduling in Cloud Radio Access Network with Mobile Cloud Computing, IEEE/ACM IWQoS, 2016.

Where will I study?