Mobile Advanced Networks


Mobile communication networks are undergoing a rapid revolution and are becoming multi-disciplinary with a blend of advanced networking, computing, and data analysis. This course, by focus on modern mobile networks, will explore these key technologies and concepts that are either used in the le networks or expected to be deployed in the future.

This course is a research-oriented course on mobile networking (algorithm, protocol, and architectures) and is prepared to stimulate students' critical thinking and analysis.

Teaching and Learning Methods: Lectures, Homework (2-3), and a case study (study and present a research paper in a group of 2-3 students). 

Course Policies: Mandatory participation, Case study optional, but recommended.


Some overview papers will be distributed in class.


Basic knowledge in networking and wireless systems.


It starts by introducing modern mobile networks (5G and 6G) and a survey on expectations from such networks and covers a fusion of possible solutions in the areas of:

  • Networking technologies/protocols (new network paradigms, 4 sessions)
  • Network virtualization and slicing following emerging enabling technologies including NFV, SDN, MEC
  • Autonomous and self-organized networking
  • Ultra-dense and heterogeneous networking in an urban environment
  • Intelligent Mobile Advanced Networks (2 sessions)
  • Data-Driven Network Control and Management
  • Applications of AI, Machin Learning and Deep Learning in 5G and 6G

Case Study:

  • Pick an open research problem
  • Analyze the proposed solution and try to improve it by applying some of the techniques learned during the course
  • Evaluate the performance of the proposed approach

Learning Outcomes: 

  • Provide an in-depth understanding of new network paradigms and technology enablers for Mobile Advanced Networks
  • Understand protocol and networking issues of future Mobile Communication Networks, esp. Mesh and Self-organizing Networks
  • Develop critical analysis and thinking on mobile networking, and get prepared for interdisciplinary research in future Data-Driven Mobile Networks.

Nb hours: 21,00

Evaluation: Best score according to these two methods of calculation:

  • Homework (20% of the final grade) and final exam (80% of the final grade)
  • Homework (20% of the final grade), Final Exam (50% of the final grade) and case study (30% of the final grade)