Anomaly detection using machine learning and adopted digital twin concepts in radio environments

Our methodology begins with creating a dataset using system parameters referenced in Reference Paper¹¹. This data generation was accomplished using our Python framework, which consists of six dedicated code modules. Each module handles a specific part of data