mlsanityData to 14 Oct 2026

SNR-adaptive deep joint source-channel coding for wireless image transmission

arXiv 2102.00202 ↗First posted 30 Jan 2021eess.SP eess.IVcited by 10

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Abstract (arXiv)

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 decoder's estimation error of the SNR. 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.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Jan 2021.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 2; 2025: 2; 2026: 3.

10 papers.