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We consider low-latency image transmission over a noisy wireless channel whencorrelated side information is present only at the receiver side (the Wyner-Zivscenario). In particular, we are interested in developing practical schemesusing a data-driven joint source-channel coding (JSCC) approach, which has beenpreviously shown to outperform conventional separation-based approaches in thepractical finite blocklength regimes, and to provide graceful degradation withchannel quality. We propose a novel neural network architecture thatincorporates the decoder-only side information at multiple stages at thereceiver side. Our results demonstrate that the proposed method succeeds inintegrating the side information, yielding improved performance at all channelnoise levels in terms of the various distortion criteria considered here,especially at low channel signal-to-noise ratios (SNRs) and small bandwidthratios (BRs). We also provide the source code of the proposed method to enablefurther research and reproducibility of the results.

Distributed Deep Joint Source-Channel Coding with Decoder-Only Side Information