We study, from an information theoretic perspective, the merits of joint sourcechannel (JSC) coding versus traditional tandem coding, which consists of separately performing and concatenating source and channel coding. Specifically, we provide a systematic comparison of the JSC coding error exponent EJ (Q, W ) with the tandem coding error exponent ET (Q, W ) for communication systems with discr...

This paper presents a practical architecture for joint source-channel coding of human visual model based video transmission over satellite channel. Perceptual distortion model justnoticeable-distortion (JND) is applied to improve the subjective quality of compressed videos. 3-D wavelet decomposition can remove spatial and temporal redundancy and provide scalability of video quality. In order to...

The turbo principle (iterative decoding between component decoders) is a general scheme, which we apply to joint source-channel decoding. As a realistic (e.g. speech parameter coding) example we discuss joint source-channel decoding for auto-correlated continuousamplitude source samples. At the transmitter the source samples are quantized and their indexes are appropriately mapped onto bitvecto...

We consider coding for transmission of a source through a channel without error when the receiver has side information about the source. We show that separate source and channel coding is asymptotically suboptimal in general. By contrast, in the case of vanishingly small probability of error, separate source and channel coding is known to be asymptotically optimal. For the zero-error case, we s...

The optimization of joint source and channel coding for a sequence of numerous progressive packets is a challenging problem. Further, the problem becomes more complicated if the space-time coding is also involved with the optimization in a multiple-input multiple-output (MIMO) system. This is because the number of ways of jointly assigning channels codes and space-time codes to progressive pack...

The turbo principle (iterative decoding between component decoders) is a general scheme, which we apply to joint source-channel decoding. As a realistic (e.g. speech parameter coding) example we discuss joint source-channel decoding for auto-correlated continuousamplitude source samples. At the transmitter the source samples are quantized and their indexes are appropriately mapped onto bitvecto...

The aim of source coding is to represent information as accurately as possible using as few bits as possible and in order to do so redundancy from the source needs to be removed. The aim of channel coding is in some sense the contrary, namely to introduce redundancy that can be exploited to protect the information when being transmitted over a nonideal channel. Combining these two techniques le...

English We consider the joint source-channel coding problem of sending a Gaussian source over a multiple input-multiple output (MIMO) fading channel when the decoder has additional correlated side information whose quality is also time-varying. We assume a block fading model for both the channel and side information qualities, and assume perfect state information at the receiver, while the tran...

We investigate joint source channel coding (JSCC) for wireless image transmission over multipath fading channels. Inspired by recent works on deep learning based JSCC and model-based methods, we combine an autoencoder with orthogonal frequency division multiplexing (OFDM) to cope fading. The proposed encoder decoder use convolutional neural networks (CNNs) directly map the images complex-valued...