ConvAE: A New Channel Autoencoder Based on Convolutional Layers and Residual Connections
In this letter, we propose ConvAE, a new channel autoencoder structure. ConvAE uses residual blocks with convolutional layers. This configuration increases performance while decreasing computational complexity at run-time compared with conventional channel autoencoders. The simulations using both co...
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Veröffentlicht in: | IEEE communications letters 2019-10, Vol.23 (10), p.1769-1772 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this letter, we propose ConvAE, a new channel autoencoder structure. ConvAE uses residual blocks with convolutional layers. This configuration increases performance while decreasing computational complexity at run-time compared with conventional channel autoencoders. The simulations using both conventional and proposed autoencoders for a 2-by-2 multiple-input multiple-output (MIMO) system under Rayleigh and Nakagami-m fading show that the ConvAE is able to attain a lower bit error rate and higher achievable rate relative to the conventional channel autoencoder schemes. |
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ISSN: | 1089-7798 1558-2558 |
DOI: | 10.1109/LCOMM.2019.2930287 |