SNR-adaptive deep joint source-channel coding for wireless image transmission
M Ding, J Li, M Ma, X Fan - ICASSP 2021-2021 IEEE …, 2021 - ieeexplore.ieee.org
M Ding, J Li, M Ma, X Fan
ICASSP 2021-2021 IEEE International Conference on Acoustics …, 2021•ieeexplore.ieee.orgConsidering the problem of joint source-channel coding (JSCC) for multi-user transmission
of images over noisy channels, an autoencoder-based novel deep joint source-channel
coding scheme is proposed in this paper. In the proposed JSCC scheme, the decoder can
estimate the signal-to-noise ratio (SNR) and use it to adaptively decode the transmitted
image. Experiments demonstrate that the proposed scheme achieves impressive results in
adaptability for different SNRs and is robust to the noise in the SNR estimation of the …
of images over noisy channels, an autoencoder-based novel deep joint source-channel
coding scheme is proposed in this paper. In the proposed JSCC scheme, the decoder can
estimate the signal-to-noise ratio (SNR) and use it to adaptively decode the transmitted
image. Experiments demonstrate that the proposed scheme achieves impressive results in
adaptability for different SNRs and is robust to the noise in the SNR estimation of the …
Considering the problem of joint source-channel coding (JSCC) for multi-user transmission of images over noisy channels, an autoencoder-based novel deep joint source-channel coding scheme is proposed in this paper. In the proposed JSCC scheme, the decoder can estimate the signal-to-noise ratio (SNR) and use it to adaptively decode the transmitted image. Experiments demonstrate that the proposed scheme achieves impressive results in adaptability for different SNRs and is robust to the noise in the SNR estimation of the decoder. To the best of our knowledge, this is the first deep JSCC scheme that focuses on the adaptability for different SNRs and can be applied to multi-user scenarios.
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