Deep Learning Based Automatic Modulation Classification With Long-Short Term Memory Networks
Sümeye Nur Karahan, Aykut Kalaycıoğlu · 2020
The automatic modulation classification (AMC) process is used to determine the modulation format of the transmitted signal at the receiver side without any prior knowledge. Deep learning is a type of machine learning that consists of multiple layers in which raw data is taken as input. This study analyzes the AMC process with a deep learning approach. In this context, performances of LSTM (Long-Short Term Memory) and Bi-LSTM (Bidirectional LSTM) methods on the modulation classification problem are compared. Simulation results show that Bi-LSTM method has a higher performance than does the LSTM method.