Masters Thesis: Reinforcement learning for Radio Resource Management applications

Job Description

Date: Oct 11, 2019

Do you want to do your thesis with us in Kista? 


Come and start your professional journey at Ericsson! 

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With the growth in number of connected devices and increased requirements and expectations towards mobile communications, the 5th generation (5G) core network defined by 3GPP standard offers new degrees of flexibility to support new use-cases and service demands as compared to classic mobile broadband networks in 3G and 4G. With these new degrees of flexibility, radio resource management (RRM), e.g. power control, cell shaping, link adaptation, scheduling, etc., will become an even more demanding task with extended number of decision variables and higher levels of complexity.



5G network is expected to provide higher service rates for users compared to 4G. Moreover, the number of connected devices constantly increases. To be able to keep up with higher traffic demands 5G networks will be more heterogeneous and denser. These networks often require sophisticated and complicated algorithms for scheduling, link adaptation and power control as the degree of freedom of these systems increase. One way of solving this is by using reinforcement learning where the algorithm learns the system dynamics on the go and controls it adaptively.



The aim of this thesis is to investigate the possibility of utilising reinforcement techniques in for different radio resource management problems in dense 5G networks. Developing and evaluating found solutions in Ericsson system-level simulators which reflect some practical aspects of real-networks is also a part of the objective.



You should be self-motivated and used to working with others in project teams. The positions also require you to be fluent in English, both written and spoken. In return, you will get to perform your thesis work with cutting-edge technology in a stimulating learning environment with a friendly atmosphere.


Key qualifications:


  • Background in Electrical Engineering, Control and Robotics, Telecommunications, Machine learning, Computer Science, or similar
  • Significant part of courses associated with the degree are accomplished
  • Strong analytical and mathematical skills and ability to acquire new knowledge and apply it in the job 
  • Ability to formulate problems and solve them independently and with the team
  • Very good programming skills (Java/Python)
  • Good understanding of different optimization and learning methods, i.e. dynamic programming, reinforcement learning
  • Basic understanding of mobile networks, radio resource management in particular
  • Willingness to write publication


We will provide active support for the motivated thesis worker in the work to successfully fulfil the requirements for the Master Thesis.


Are you in?  

Then send in your application (CV, current grades and cover letter written in English collected into one document) as soon as possible.   

The application deadline is the 31st October. The process will be ongoing and we will let you know as soon as we can if you move forward.

Any questions? Please email Recruitment Specialist, Sylwia Kwiecień at 


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Primary country and city: Sweden (SE) || || Stockholm || Stud&YP

Req ID: 300526