PhD Position: Structured Signal Processing and Learning for Wireless Communications

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PhD Position: Structured Signal Processing and Learning for Wireless Communications

Delft University of Technology
Country of Position: 
Contact Name: 
Geethu Joseph
Subject Area: 
Signal Processing for Communications and Networking
Machine Learning for Signal Processing
Start Date: 
02 November 2021
Expiration Date: 
31 January 2022
Position Description: 

Job description

The wireless communication systems beyond 5G aim to enhance connectivity with a drastic increase in the number of connected devices and improved quality of service requirements in terms of data rate, latency, reliability, and scalability. To this end, we need new physical layer signal processing for the futuristic systems to efficiently acquire and process the resulting enormous amount of data. An important emerging approach is the deep learning-based techniques. The state-of-the-art deep learning solutions for wireless communications are indeed very promising due to their learning abilities. However, they lack interpretability and come with no performance guarantees. In this PhD project, we will investigate the integration of the traditional signal processing algorithms with performance guarantees, and the tools from deep learning, combining the best of both worlds. The challenge here is to understand the right balance between the model-driven and data-driven methods. Our goal is to explore the different combinations of the two approaches and develop new solutions for signal detection and channel acquisition. We also characterize the performance limits of this hybrid analytical framework, aiming at new wireless system designs with improved reliability and connectivity.

The Circuits and System Group seeks for enthusiastic PhD candidates to work on this project. The research will focus on

  • Understanding the limitations and challenges of the signal processing for wireless technologies beyond 5G
  • Developing new solutions for signal detection and channel acquisition using model-based deep learning
  • Analyzing the performance guarantees of the derived solutions in terms of achievable data rates and reliability of the communication (outage and error probabilities)


  • An MSc degree in an engineering discipline relevant to PhD research.
  • Strong background in applied mathematics, particularly, real analysis, probability, and linear algebra.
  • Background in wireless communications is desirable, but not mandatory.
  • Experience in programming e.g., Python, MATLAB, R.
  • Good verbal and written English skills.
  • Excellent communication and interpersonal skills.
  • Ability to work in a collaborative environment.

To apply, please follow the process indicated on the formal vacancy announcement

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