Deep-Learning-based Channel Estimation for Chaotic Wireless Communication

A deep-learning-based channel estimation method for chaotic wireless communication is proposed in this letter, which is based on a deep neural network (DNN) pre-trained by the stacked denoising autoencoder (SDAE) structure. The DNN learns the channel parameters by using the autocorrelation function...

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Vydané v:	IEEE wireless communications letters Ročník 13; číslo 1; s. 1
Hlavní autori:	Yin, Hui-Ping, Zhao, Xiao-Hui, Yao, Jun-Ling, Ren, Hai-Peng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Artificial neural networks Autocorrelation functions Channel estimation chaotic baseband wireless communication system (CBWCS) Chaotic communication Communications systems Decoding Deep learning deep neural network (DNN) Estimation Identification methods Machine learning Noise reduction Robustness (mathematics) stacked denoising autoencoder (SDAE) Wireless communication Wireless communications
ISSN:	2162-2337, 2162-2345
On-line prístup:	Získať plný text
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