CIT 09-Mobile Networks

Optimizing 5G/6G Radio Access Network Performance

CIT - Electrical and Computer Engineering

Chair of Communication Networks (Prof. Kellerer)

Mobile Communication Systems (Radio Access Networks), 5G/6G

Computer EngineeringComputer ScienceElectrical Engineering

Participation also possible online only:

Planned project location:

TUM City Campus, Building 9, next to the Audimax.

M.Sc.

Valentin

Haider

valentin.haider@tum.de

TUM - 28044

Dr. Ph.D.

Fidan

Mehmeti

fidan.mehmeti@tum.de

With the recent roll-out of the new 5G/NR cellular communication technology throughout the world, new research projects on the 6th generation of mobile communications have been founded both nationally, e.g., in Japan, Germany, Finland, or the USA, but also more globally organized within the EU, North America, or even worldwide. One of the most important parts of a mobile communication system is the Radio Access Network (RAN), which ensures the wireless accessibility of the mobile communication network from a user equipment (UE) such as a mobile phone. Throughout the various generations of mobile communication systems, many different techniques have been developed and employed to improve the performance of the RANs in terms of, e.g., security, energy efficiency, resource utilization, or flexibility.

The supervisors’ research focuses on resource management in RANs. Resource management includes but is not limited to tasks like radio and computing resource allocation (scheduling), network slicing, or admission control. Radio and computing resource allocation guarantees the fulfillment of specific Quality of Service (QoS) requirements under given network conditions. Network slicing allows for the virtual isolation and reservation of RAN resources. Lastly, admission control, both for users and slice requests, ensures that the network load is still manageable and that the guaranteed QoS of previously accepted users or slices is not deteriorated. Hence, developing efficient algorithms for these tasks with objectives like revenue maximization, fairness, or energy consumption minimization is inevitable to further enhance the current and future mobile communication systems. The supervisors employ classical mathematical optimization, machine learning, the implementation of simulations, and the performance of testbed measurements to tackle these problems and evaluate their work.

The student will work on developing and solving an optimization problem with the objective of maximizing a given network performance measure in close collaboration with their supervisors. Depending on the type of optimization problem, the problem will be tackled analytically or by proposing low-complexity algorithms (heuristics). Afterward, the developed algorithm will be implemented either in our open-source SW 5G network (OpenAirInterface) or in our 5G campus network equipped with multiple commercially available Base Stations and a standard-compliant 5G network core from a start-up company.

35

3 years of bachelor studies completed

Basic knowledge of communication systems, optimization problems, and probability theory.

Motivation to propose and pursue own ideas, ability to present technical concepts clearly, strong organizational skills