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We study the scenario of pixel-domain distributed video coding for noisy transmission environments and propose a method to allocate the available rate between source coding and channel coding to generate a robust video stream. Having observed in experiments the uncertainty of the source and the channel coding rate, we model them as random variables via offline training, estimate the decoding failure probability and calculate the mean end-to-end distortion. Adaptive quantization is performed for each slice to minimize its mean end-to-end distortion. With this joint source-channel rate allocation, we compare the robustness of two coding prototypes, namely distributed video coding and distributed video coding with forward error correction. According to our experimental results, under same total bit budget, the distributed video coding only scheme proves more robust than the latter one and the gain is up to 1 dB in PSNR.