Internship | AI-based management for sustainability in 6G Cell-Free Networks

Become an intern at TNO and work on AI-based management for sustainability in 6G Cell-Free Networks.

About this position

Energy savings and sustainability are a big challenge in mobile networks, with energy consumption continuously increasing due to ever-increasing mobile network traffic. Although efforts are being made to reduce energy consumption in various ways, the radio infrastructure, in particular the base stations, consumes the largest amount of energy within the network. A promising new architecture for achieving lower energy consumption while further enhancing spatial performance fairness compared to traditional cellular networks is cell-free networks (CFN).

CFNs consist of multiple simple low-power access points (APs), which are spatially distributed and can be seen as a distributed MIMO system. Multiple APs can be assigned to serve a single device. The intelligence of the network, for example AP clustering, scheduling, and sleep mode management, is located in a centralized processing unit that coordinates and manages the APs. Because networks are designed to handle peak-hour traffic, during non-peak hours some APs can go into sleep mode in order to reduce network energy consumption. Hence, sleep mode management (SMM) algorithms are developed to dynamically adapt the mode, i.e. active or light/deep sleep, of the APs according to the traffic load in the network while still satisfying coverage and throughput performance requirements. The goal of this project is to deploy deep reinforcement learning (DRL) methods for the SMM of the APs. A realistic scenario will be considered for the evaluations, where APs are deployed on lampposts in the city centre of Amsterdam.

What will be your role?

During this project, a number of key activities will be performed:

• Gain deep understanding of cell-free networks, as well as DRL methods.
• Develop a DRL-based SMM algorithm and integrate it into an existing simulator of a realistic cell-free network. The developed algorithm will be evaluated in the simulator in different scenarios and configurations, including testing in conditions different from those used in training.
• Implement state-of-the-art SMM algorithms from the literature to be used as baselines for evaluating the developed DRL-based SMM algorithm.
• Derive key insights and conclusions with respect to the performance of the algorithm, as well as the challenges and gains of using DRL compared to heuristic algorithms.

This graduation project involves close collaboration with TNO employees. The project will also be conducted as part of the large nationally funded research programme Future Network Services (FNS), bringing together more than 60 partners until the middle of 2030. The proposed project is envisioned to involve collaborations and/or regular interactions with other FNS partners.

What we expect from you

For this graduation project, TNO is looking for a graduate student pursuing a Master’s degree, preferably in Electrical Engineering or Computer Science. Candidates should have affinity with or interest in mobile networks, deep reinforcement learning, and software development. The duration of the project is 9 months. The key strengths sought are:

• Previous knowledge of or experience with concepts such as 5G/6G and wireless communications, as well as programming experience in Python. Experience with deep reinforcement learning is preferred.
• Ability to conduct research independently under mentorship or supervision, and to work together with others in a flexible and diverse environment.
• Fluency in English, spoken as well as written.

What you'll get in return

An internship at TNO means working in an environment where substance and impact are central. You will become part of a knowledge organisation where research and practice come together, and where experts collaborate on solutions to current societal and technological challenges.

Your internship is a period in which you can discover what suits you, where your strengths lie and what you would like to learn next. You are part of a professional working environment, gain insight into how things work in practice, and have the opportunity to build experience that goes beyond this internship alone. For many students, an internship is therefore also a first step in discovering whether TNO could be a potential next step after graduation.

In addition, TNO offers:

• A professional and innovative internship environment in which you actively contribute to societal and technological challenges, working alongside leading experts in your field.
• Personal and dedicated supervision, with focus on your learning objectives, development and study assignment.
• Room to develop: you gain relevant work experience, develop both your subject-specific and professional skills, and build a valuable network.
• Use of a laptop and the facilities you need to perform your work effectively.
• A monthly internship allowance of € 615 for a full-time internship, for MSc, BSc and vocational education (MBO) students.
• Up to eight hours of leave per internship month for a full-time internship, allowing you to balance your internship with your studies and personal life.
• A contribution towards travel expenses if you are not entitled to a student travel card.
• A free membership to Jong TNO: the network for young colleagues, where you can meet other TNO colleagues and participate in sports activities, professional and personal development activities, and social events such as the annual ski trip.

TNO as an employer

Our people are at the heart of TNO. Their curiosity, expertise and entrepreneurial mindset make it possible to deliver high-impact research and innovations that contribute to society’s sustainable wellbeing and prosperity.

Your talent and ambition have every opportunity to flourish at TNO. You work with experts, both within and beyond TNO, have access to advanced technology and the freedom to explore, experiment and innovate. TNO’s strength lies in independence, reliability and collaboration.