THE TEAM YOU’LL BE PART OF

Nokia Standards is seeking RAN Architecture PhD student to research in our Architecture, Security and Automation Group. You will work in one of our teams defining the global evolution of RAN architecture from 5G to 6G as well as supporting 3GPP standardization work. A candidate should have knowledge on cellular mobile communication networks, strong research skills with outstanding analytical/theoretical capabilities and simulation experience. Successful candidates are expected to have research mindset, solve complex problems, analyze and prove the benefits of the concepts and contribute these concepts to standardization bodies, mainly 3GPP and ORAN.
The department of RAN Architecture in Nokia Standards, Munich, offers the opportunity for a master graduate to pursue a Ph.D. degree in communication engineering or computer science in collaboration with one of Nokia’s renown partner universities. The thesis work will be conducted in Munich and is expected to be completed within 3 years.
Making mobility procedures as seamless as possible is the main unique selling point of cellular mobile networks. One promising improvement with the rise of computing capabilities is to use AI/ML techniques to detect the UE mobility and environment with finer granularity to remove any possible handover failures. Moreover, as sustainability is becoming one of the most important metric in the network, such prediction and detection probability becomes of utmost importance. Such prediction capability would decrease the need for transmission of wireless signals saving base station and user equipment power consumption.
Simulations using stochastic channel models are a good way to train, implement, and test such AI/ML models. The underlying training data can be collected from the same simulations.

With the emergence of the GPU-based computing capabilities, not only AI/ML techniques become a possibility but also ray tracing capabilities make it possible to run simulations in a reasonable run time that clearly indicate the spatial correlation characteristics. This enables AI/ML techniques to learn clear correlations for specific environments and outperform stochastic channel model-based scenarios and adapt better to real world deployments. However, even with increased computing techniques it is quite challenging to collect sufficient information that can generalize to many complex mobility scenarios. Thus, the aim would be to investigate ways to fine-tune ray tracing techniques in order to obtain granular data in needed cases. Such techniques shall also work in close coordination with AI/ML model testing to keep the highest reasonable performance. In short, the PhD includes the following topics:

• Testing and implementation of both Nokia proprietary and public ray tracing libraries for measurements that can be used in mobility procedures e.g., Sionna from Nvidia
• Integration of data collection, model building, and testing to the ray tracing-based simulations
• Calibration of ray tracing simulations to have a reasonable run time that enables broad coverage mobility scenarios
• Investigation of applicability of the ray tracing to a broader range of scenarios such as UL timing advance acquisition, TCI state activation, early CSI acquisition, and joint sensing and communication

Further, general targets of the PhD work include the protection of the generated Intellectual Property (IP), scientific publications and, where applicable, contributions to standardization.

YOUR SKILLS AND EXPERIENCE

We are looking for highly motivated candidates who are enthusiastic about developing breakthrough innovations and participate in cutting-edge research in Nokia. Applicants should fulfill the following qualifications:

• A diploma or master’s degree in communications engineering, information theory, or computer science with a grade of at least 2.0 (German grade system equivalent).
• Good knowledge in wireless communication, cellular networks, and mobility procedures.
• High proficiency in relevant programming languages for quantitative evaluations (e.g., Python, C++, Matlab).
• Strong theoretical skills in mathematics and physics.
• Highly proficient in spoken and written English.
• Good grasp of AI/ML work and understanding of mobility procedures
• Ability to work independently and proactively define research targets and methodology and ready to collaborate in a diverse team with members of different cultural backgrounds.

Willingness and ability to get engaged in novel disruptive research areas, which will require the applicant to learn new skills.

Please refer the Job description for details