DC2: Robust mmWave communication and sensing in smart environments

Task: Robust mmWave communication and sensing in smart environments (WP1)

Host institution: TU Delft

Country: The Netherlands

Supervisors: Dr. A. Asadi [TUDa]

Co-supervisors/mentors: Dr. Gek Hong Sim, Dr. Uusitalo

Objectives: To detect/track objects based on the Doppler shift and the AoA analysis of the CSI at the mmWave receiver; To dynamically configure and allocate the RIS elements for optimising dedicated sensing and communication task; To evaluate the performance of the solutions on the TUDa testbed facilities (Obj1b).

Expected Results: RIS-assisted sensing for high accuracy and low latency object tracking and detection. Online reinforcement learning algorithms for RIS element clustering that jointly maximises sensing accuracy and data rate. Working prototype in using RIS prototypes.

PhD enrolment: Doctoral School of TU Delft

Planned secondments:

  • Princeton (5 months, M18-M22): Single-shot RIS-configuration for fast object tracking, with Y. Ghasempour (KPI: joint journal paper)
  • Nokia-DE (3 months, M27-M29): Multi-RIS coordination for outdoor JCAS, with S. Mandelli and T. Wild (KPI: joint conference paper)

Candidate profile: Telecommunications, Electrical Engineering

Desirable skills/interests: signal processing, optimization, machine learning, programming & implementation skills (the applicant should be proficient in at least one or two of the skills)