Systems Engineering and Electronics ›› 2024, Vol. 46 ›› Issue (11): 3920-3929.doi: 10.12305/j.issn.1001-506X.2024.11.34

• Communications and Networks • Previous Articles     Next Articles

Modulation recognition of unmanned aerial vehicle swarm MIMO signals under Alpha stable distribution noise and multipath interference

Jiarong PING, Sai LI, Yunhang LIN   

  1. School of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2023-07-24 Online:2024-10-28 Published:2024-11-30
  • Contact: Jiarong PING

Abstract:

Aiming at the problem of signal modulation recognition of multiple-input multiple-output (MIMO) channel of unmanned aerial vehicle (UAV) swarm with multipath effect, atmospheric noise and other interference factors, a modulation recognition method based on cyclic spectral features and high-order cumulant features is proposed. Firstly, according to the characteristics of the complex communication channel of the UAV swarm, the UAV swarm channel with Alpha stable distribution noise interference and multipath interference is established. Secondly, the high-order cumulants and cyclic spectral features of MIMO received signals are analyzed, and the feature values with strong discriminative ability are extracted to construct swarm signal samples. Finally, the samples are fed into the deep sparse autoencoder network to realize recognition of six modulation types. The simulation results show that this modulation recognition method is feasible in complex channel environment of UAV swarm. When the accuracy is 90%, the recognition performance of the deep sparse autoencoder network is about 1 dB better than that of the multilayer perceptron. The accuracy of the method can reach 96% in the MIMO multipath channel with line of sight path when the mixed signal-to-noise ratio is 0 dB, indicating that it has a high recognition accuracy at low signal-to-noise ratio, and it is robust to modulation recognition in complex MIMO communication channels.

Key words: modulation recognition, multiple-input multiple-output (MIMO), cyclic spectrum, high-order cumulant, deep sparse autoencoder network

CLC Number: 

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