Main supervisor profile and contact: Dr. Gilberto Berardinelli <gb@es.aau.dk> and Dr. Preben Mogensen <pm@es.aau.dk>

Institution: Aalborg University

Description of the job: Wireless networks installed in industrial premises are emerging as a promising solution for supporting wireless control of production modules and mobile robots. While 5G has been designed to support latencies down to 0.5-1 ms and five-nine reliability, there is the need of tailoring wireless communication to applications which may require even more stringent requirements, e.g. down <100 us latencies and nine-nines reliability. The support of such extreme Ultra-reliable low latency communication (URLLC) applications naturally leads to the usage of a large bandwidth and raises the need of an aggressive reuse of the radio spectrum. Moreover, besides same-system-type of interference, the reliability of wireless industrial applications can be undermined by the presence of malicious jammers. This project aims at devising novel mechanisms for supporting extreme URLLC requirements in a group of potentially dense industrial radio cells. Both centimeter-wave and millimeter-wave bands can be considered, as well as both cases of interference generated by neighbor networks and malicious jammers. In particular, proactive interference mitigation mechanisms will be studied, potentially leveraging modern machine learning paradigms such as reinforcement learning, transfer learning and Bayesian optimization with Gaussian processes. Such mechanisms can eventually rely on apriori knowledge of traffic patterns and deployment characteristics, context information (e.g., positioning, or information obtained via digital twinning), spatial filtering capabilities of massive antenna arrays. Performance analysis can be based on experimental data collected in real industrial premises.

Mission: Developing novel methods for support of extreme URLLC requirements in dense industrial deployments via intelligent interference management, potentially leveraging context information and modern machine learning solutions.

Main functions: The main tasks to be carried out by the PhD student are the following: 1) Literature review on 5G URLLC solutions in both Release 15 and 16, related regulatory framework and on implicit and explicit interference coordination mechanisms, also based on cognitive radio and machine learning approaches. 2) Identification of relevant industrial scenarios and use cases, as well as reference spectrum regions. 3) Identification of shortcoming of current 5G solutions in addressing the support of URLLC-like services for a large number of links in a dense deployment. 4) Design of centralized interference coordination techniques for cells operating over licensed spectrum owned by the same operator, exploiting modern data-driven approaches and context information 5) Design of distributed interference coordination techniques for cells operating over licensed spectra where multiple operators may coexist. 6) Design of implicit distributed interference coordination techniques for coexistence between private and potentially large public networks operating over the same spectrum. 7) Design of solutions for detecting and mitigating malicious jamming. 8) Performance analysis based on data collected in real industrial scenarios. 9) Developing a set of recommendations for 6G system design (as well as potential new spectrum sharing regulations) for industrial cells leveraging from the previous learning. 10) Achievement of the necessary pre-requisites for obtaining a PhD degree: PhD courses, scientific dissemination, etc. 11) Writing of scientific articles in reputed international journals and publications, and writing and defence of a PhD thesis.

Secondments: The selected candidate will take part in one secondment of 10 months in Nokia (Aalbord, Denmark) (supervised by Dr. Klaus Pedersen) and another secondment of 8 months each, hosted by Bosch in Germany (supervised by Dr. Andreas Muller).

Doctoral programme: The ESR will be enroled in the Aalborg University doctoral programme.

Requirements of the candidate

• Education level: Master on Electrical Engineering

• Degree/speciality: Telecommunications, Wireless communications

• Language skills: Excellent oral, reading and writing skills in English.

• Research experience: Good knowledge of physical layer, medium access control and radio resource management for wireless network, as well as modern 3GPP standards. Eventual scientific publications already submitted will be positively valued.

• Other skills: Good programming skills (e.g., Matlab, C++, Python)

Apply: Job application form and AAU vacancies website. Please remember to send your application to both websites.