Main supervisor profile and contact: Dr. Carles Navarro and <gb@es.aau.dk> and Dr. Gilberto Berardinelli <gb@es.aau.dk>

Institution: Aalborg University

Description of the job: The diversity of use cases in Industry 4.0 (I4.0) implies that industrial wireless networks will have to accommodate different—and often conflicting—requirements: high data rates and low latency are demanded by virtual/augmented reality applications as well as kitting and assembly operations, extremely high reliability and low latency may be required for the control of cyber-physical systems, while the ability to serve a massive amount of devices is required to gather industrial sensor data. This PhD study will research how to exploit emerging technologies, such as massive MIMO and reconfigurable intelligent surfaces (RISs) to accommodate such diverse and demanding performance requirements, including frequencies below 6 GHz (FR1) and in the mmWave bands (FR2). We aim to develop novel methods focusing on the physical communication layer, e.g., beam management with enhanced mobility and reliability, service-specific transmission point association, radio resource management and interference management and coordination. The study will also target the design or radio resource control mechanisms for multiplexing diverse services with distinct performance requirements relying on the use of machine learning frameworks.

Mission: To research the application of massive MIMO and RIS-based communication techniques to Industry 4.0 scenarios and use cases and to propose novel enhancements to existing standards to address the special requirements of Industry 4.0 applications.

Main functions: The main tasks carried out by the researcher include: 1) Study of state-of-the-art including: current 5G standards for industrial communications, channel characterization in industrial scenarios, massive MIMO techniques and system architectures. 2) Identification of use-cases of interest, and further delimitation of the study’s scope. 3) Development of the necessary system models for the study, including: channel models, traffic models, mobility models, network architecture and physical layer. 4) Implementation of the developed models in a computer simulation tool for generation of results. 5) Baseline performance study for the identified use-cases with current 5G standard. Identification of shortcomings and proposal of enhancements. 6) Study and design of techniques for AI-based Beam management enhancements for improved reliability and mobility in FR2, Clustering and transmission point association in distributed MIMO scenarios, Radio resource management and interference coordination in multi-service context, Channel estimation of RIS-based communications. 7) The developed techniques will seek to enhance the latency and reliability of the resulting system, as well as to provide the necessary flexibility to accommodate the demands of different types of industrial use-cases. 8) Achievement of the necessary pre-requisites for obtaining a PhD degree: PhD courses, scientific dissemination, etc. 9) Writing of scientific articles in reputed international journals and publications, 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 NEC (Heidelberg, Germany) (supervised by Dr. Vincenzo Sciancalepore).

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: Wireless communications, Information processing or similar

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

• Research experience: The ideal candidate has experience in research on the physical, medium access control, or radio resource management layers of wirelesss communication systems, e.g. through their Master thesis. Knowledge and experience in MIMO communications, channel characterization, and/or 5G New Radio standards will be highly valued, as well as expertise in statistical signal processing and machine learning tools and prior experience with publication of scientific articles.

• Other skills: Good skill and experience with programming frameworks typically used in the field: C, C++, MATLAB, Python, etc.

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