Modulation Classification Based on Signal Constellation Diagrams and Deep Learning

• Published in: IEEE transaction on neural networks and learning systems Vol. 30; no. 3; pp. 718 - 727
• Main Authors: Peng, Shengliang, Jiang, Hanyu, Wang, Huaxia, Alwageed, Hathal, Zhou, Yu, Sebdani, Marjan Mazrouei, Yao, Yu-Dong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Biological neural networks; Classification; Communication systems; Communications; Communications systems; Constellations; Convolution; Convolutional neural network (CNN); data conversion; Data processing; Deep learning; deep learning (DL); Domains; Feasibility studies; Feature extraction; Learning algorithms; Machine learning; Modulation; modulation classification; Neural networks; Neurons; Signal classification; Task complexity; Training

Deep learning (DL) is a new machine learning (ML) methodology that has found successful implementations in many application domains. However, its usage in communications systems has not been well explored. This paper investigates the use of the DL in modulation classification, which is a major task...