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5G/6G End-to-end Network Slicing Framework for Vertical Industries

Eligibility: UK/EU/International graduates with the required entry requirements

Funding details: Bursary plus tuition fees

Duration: Full-Time, between 3 - 3.5 years

Application deadline: 31 May 2022

Interview date: Will be confirmed to shortlisted candidates

Start date: September 2022

For further details contact: Dr. Faouzi Bouali 


The Trailblazer PhD studentships have been devised and developed by leading early-career researchers at Coventry University.

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Project details

With the growing dependency of 5G networks on software, network slicing has emerged as a new paradigm to create a set of customised logical network instances on top of the same physical infrastructure. It will allow telecom operators to offer “slices” of their networks to several industries (e.g., automotive, industry 4.0 and eHealth), which will increase resource usage efficiency and generate valuable return-on-investment. Despite these benefits, the concept is still in its infancy with limited applications to small portions of the network.

In this context, this PhD project aims at constructing a 5G/6G end-to-end (E2E) slicing framework, where “network slices” spanning all relevant domains (e.g., user devices, base stations and network infrastructure) are created and tailored to meet the heterogeneous needs of target industries. All the practical aspects (e.g., orchestration, isolation, scalability, and security) associated with the design, deployment, and operation of these slices will be studied, and the required mechanisms will be developed. To demonstrate the benefits of the proposed framework in a real-world environment, a future-proof experimental 5G/6G slicing testbed, based on commodity hardware (e.g., software-defined radios (SDRs) and x86 computers) and open-source solutions, will be built and applied to significant use cases in the automotive industry.


The successful candidate will receive comprehensive research training including technical, personal and professional skills. All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.

Entry Requirements

  • A bachelor’s (honours) degree in a relevant discipline/subject area with a minimum classification of 2:1 and a minimum mark of 60% in the project element (or equivalent), or an equivalent award from an overseas institution.
  • The potential to engage in innovative research and to complete the PhD within 3.5 years.
  • Adequate proficiency in English must be demonstrated by applicants whose first language is not English.  The general requirement is a minimum overall IELTS Academic score of 7.0 with a minimum of 6.5 in each of the four sections, or the TOEFL iBT test with a minimum overall score of 95 with a minimum of 21 in each of the four sections.

For further details please view our research entry criteria

Additional Requirements

  • MSc degree in a relevant major in Electrical Engineering or Computer Science e.g., wireless communications or computer networks.
  • Familiarity with the architecture and protocol stack of 3GPP-based 4G/5G networks and the associated radio-access, transport and core network protocols.
  • Excellent programming and prototyping skills using e.g., Python, C/C++, Linux networking, community-based open-source software tools (e.g., Kubernetes, Docker, Git and Jenkins). Prior experience in conducting 4G/5G experimental research based on software defined radios will be a clear advantage.
  • Familiarity with software-defined networking (SDN), network function virtualisation (NFV), network slicing and the associated management and orchestration (MANO) solutions (e.g., OSM). Prior hands-on experience in these technologies will be an added plus.
  • Familiarity with virtualisation, traditional cloud computing and emerging cloud-native concepts (e.g., micro-services and containers). Prior hands-on experience in these will be a plus.
  • Knowledge of artificial intelligence/machine learning (AI/ML) techniques and tools. Prior experience applying/using these will be a plus.

How to Apply

To find out more about the project, please contact Dr. Faouzi Bouali

All applications require full supporting documentation, a covering letter plus an up-to 2000-word supporting statement is required showing how the applicant’s expertise and interests are relevant to the project.

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