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Ongoing PhD projects

CMI PhD projects

WindMill - Optimizing URLLC Metadata and Data Flows Using Machine Learning

The research mainly concentrates on the Ultra-Reliable Low Latency Communication (URLLC) metadata and data flows optimization via Machine Learning (ML) and will explore feasible models with efficient ML algorithms.

The efficiency and feasibility could be analyzed by the theoretical bounds of the improvements on latency/reliability which can be obtained from using the anticipatory protocol information. Based on the purposed model and algorithms, we aim to design an ML-augmented protocol stack with the flexible organisation of control/user planes and to implement a proof-of-concept system for ML in the URLLC demonstration.

Student: Chien-Cheng Wu (Stanley) Supervisor: Cedomir Stefanovic