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Key machine learning techniques used in 6G air interface research include reinforcement learning for optimizing network resources, deep learning for channel estimation and prediction, and generative adversarial networks for synthesizing realistic wireless channel data. EDA (Electronic Design Automation) software is used extensively in developing 6G technology. It enables researchers to design and simulate complex integrated circuits with high accuracy and efficiency. Through EDA software, researchers can model the behavior of various components and systems, analyze performance metrics, and optimize designs for better functionality and cost-effectiveness.
The course will introduce how the EDA software has been used for studying 6G technologies from the perspective of the physical layer.
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