Series-Constellation Feature Based Blind Modulation Recognition for Beyond 5G MIMO-OFDM Systems With Channel Fading
Author:
Affiliation:
1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China
2. Department of Electronic Systems, Aalborg University, Aalborg, Denmark
Funder
National Natural Science Foundation of China
Project of Key Laboratory of Signal and Information Processing of Chongqing
Natural Science Foundation of Chongqing
Research Project of Chongqing Educational Commission
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture
Link
http://xplorestaging.ieee.org/ielx7/6687307/9790075/09749759.pdf?arnumber=9749759
Reference54 articles.
1. Modulation classification for MIMO-OFDM signals via Gibbs sampling
2. Modulation Classification for MIMO-OFDM Signals via Approximate Bayesian Inference
3. A Deep Neural Network Method for Automatic Modulation Recognition in OFDM with Index Modulation
4. Convolutional Neural Network Aided Signal Modulation Recognition in OFDM Systems
5. Exploiting Spatio-Temporal Properties of I/Q Signal Data Using 3D Convolution for RF Transmitter Identification
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