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/Job opportunities/Indoor Localization using a Distributed Massive MIMO System

Indoor Localization using a Distributed Massive MIMO System

Research & development - Leuven | More than two weeks ago

You will use a wireless network infrastructure as a distributed radar

Localization in wireless communications is a research topic which has attracted notable attention in both academic and industrial labs. In line with this, the recent advent of distributed massive MIMO systems offers an interesting opportunity, where the large number of antennas may serve as an enabler for obtaining accurate localization performances. In this interest, this project considers the problem of user positioning using a distributed massive MIMO system.


In this thesis, the student will learn how to build a signal processing chain for user positioning. A simulator will be programmed to allow for validation. The student will learn the fundamentals of positioning, including performance analysis and assessment, and implement various localization algorithms based on time (difference) of arrivals, direction of arrivals and received signal strengths, as well as experiment with direct localization approaches.


After validating the algorithms on synthetic data, the student will test the algorithms on annotated measurements from a real massive MIMO testbed. The student will then study the trade-offs between utilizing small arrays with wide signal bandwidths, versus large arrays with narrow signal bandwidths. Depending on the time and ambition level, the student may proceed with a topic of choice, which may include robust statistics, sensor fusion, tracking and filtering.


The successful candidate should be proficient with the Python programming language and the numpy/scipy stack and must show a strong understanding of signal processing, linear algebra, statistics and optimization theory. Knowledge of wireless communications and/or radar concepts is a plus.



  • Master Thesis internship (6 months)
  • Preceded by optional summer internship (3 months)


Responsible scientist(s): Adham Sakhnini ( ), PhD Researcher

Type of project: Combination of internship and thesis

Duration: 6 months

Required degree: Master of Engineering Science, Master of Engineering Technology

Required background: Electrotechnics/Electrical Engineering

Supervising scientist(s): For further information or for application, please contact: Adham Sakhnini (

Only for self-supporting students.