We consider distributed image transmission over a noisy multiple access channel (MAC) using deep joint source-channel coding (DeepJSCC). It is known that Shannon's separation theorem holds when transmitting independent sources over a MAC in the asymptotic infinite block length regime. However, we are interested in the practical finite block length regime, in which case separate source and channel coding is known to be suboptimal. We introduce a novel joint image compression and transmission scheme, where the devices send their compressed image representations in a non-orthogonal manner. While non-orthogonal multiple access (NOMA) is known to achieve the capacity region, to the best of our knowledge, non-orthogonal joint source channel coding (JSCC) scheme for practical systems has not been studied before. Through extensive experiments, we show significant improvements in terms of the quality of the reconstructed images compared to orthogonal transmission employing current DeepJSCC approaches particularly for low bandwidth ratios. We publicly share source code to facilitate further research and reproducibility.
翻译:我们认为,在噪音的多个接入频道(MAC)上,使用深层联合源链编码(DeepJSCC)进行分布式图像传输。众所周知,香农的分离理论在无同步无限区块长度制度下向MAC传输独立源码时会维持。然而,我们感兴趣的是实际的有限区块长度制度,在这种制度下,已知单独的源码和频道编码不尽人意。我们引入了一种新的联合图像压缩和传输计划,在这种制度下,装置以非垂直方式发送压缩图像显示。虽然已知非横向多重访问(NOMA)是为了实现能力区域,但我们最了解的是,对实用系统的非横向联合源码(JSCC)计划尚未进行过研究。通过广泛的实验,我们展示了重塑图像质量的显著改善,而使用当前的深、JSCC方法则特别为低频率传输。我们公开分享源码,以便利进一步的研究和再生。