In this work, we investigate the MARC (Multiple Access Relay Channel) setup, in which two Markov sources communicate to a single destination, aided by one relay, based on Joint Source Channel Network (JSCN) LDPC codes. In addition, the two source nodes compress the information sequences with an LDPC source code. The compressed symbols are directly transmitted to both a relay and a destination nodes in two transportation phases. Indeed, the relay performs the concatenation of the received compressed sequences to obtain a recovered sequence, which is encoded with an LDPC channel code, before being forwarded to the destination. At the receiver, we propose an iterative joint decoding algorithm that exploits the correlation between the two sources-relay data and takes into account the errors occurring in the sources-relay links to estimate the source data. We show based on simulation results that the JSCN coding and decoding scheme into a MARC setup achieves a good performance with a gain of about 5 dB compared to a conventional LDPC code.

During the last decade, the need for visual content applications over mobile wireless environments have been progressively widespread. Motivated by the OSI layered approach, most visual applications make separation between content compression, and data transmission. Then, the received multimedia quality is degraded because of the sensitivity of the compressed stream to the transmission errors. In this paper, we propose a solution where the physical layer is scaled according to the compressed stream importance. The target application, which is visual multimedia sensor networks, motivated the use of the high-rate Ultra Wide Band (UWB) Audio Visual (AV) PHY IEEE 802.15.3c standard. We consider an embedded image compression scheme where bits are hierarchically organized, and we make different modulation, error-protection and sub-carrier assignments to them to improve the reconstructed image quality while keeping the same data-rate performance. We investigate the performance of the adaptive approach in terms of Peak Signal-to-Noise Ratio (PSNR) against Signal-to-Noise Ratio (SNR) for UWB-modeled channels. Moreover, we emphasize the gains induced by the adaptive UWB on the reconstructed image quality. It is demonstrated that dynamically assigning the symbols to sub-carriers allows a 0.5dB PSNR quality improvement while keeping the same rate is the same. Allocating different channel codes and different modulation orders improves the reconstructed PSNR by 3.SdB when Eb/N0= 5dB.

In this paper, we design a unified framework decoder for relay systems with iterative decoding. In the proposed scheme, the source node needs to transmit a correlated content to a destination with the help of a relay. Then, a distributed Joint Source Channel (JSC) Low-Density-Parity-Check (LDPC) encoding is applied at the source and the relay. The destination receives simultaneously the source compressed data from the source node, and the source/channel encoded data from the relay node. The cooperative network is mapped into a factor graph on which message passing iterative decoding is applied to estimate the source information. The JSC decoder takes into account the source-relay correlation which involves remarkable improvements even if errors occur at the source-relay link. The Bit Error-Rate (BER) system performance are investigated for different scenario, according to the relay position, and it is shown that the performance of the proposed cooperative scheme is typically about 0.5–1.0 dB better than an equivalent rate point-to-point system.

In order to retrieve multimedia content like video and audio at indoor environments, wireless multimedia sensor networks have recently emerged as a good solution. Moreover, Ultra Wide Band technology (UWB) can provide high data rates to transfer the multimedia content in a point-to-point mode. In this paper, we explain the features of UWB technology and investigate the performance of the IEEE 802.15.3c standard in terms of Bit Error Rate (BER) against Signal to Noise Ratio (SNR). The Audio Visual Physical (AV PHY) mode has been implemented and simulated and our results show that encoded AV PHY outperforms the uncoded AV PHY for high and low Convolutional encoder rates. Finally, we emphasized the quality improvements with different UWB standard parameters (coding and modulation) in the context of JPEG image compression.

Most source coding standards (voice, audio, image and video) use Variable-Length Codes (VLCs) for compression. However, the VLC decoder is very sensitive to transmission errors in the compressed bit-stream. Previous contributions, using a trellis description of the VLC codewords to perform soft decoding, have been proposed. Significant improvements are achieved by this approach when compared with prefix decoding. Nevertheless, for realistic VLCs, the complexity of the trellis technique becomes intractable. In this paper, we propose a soft-input VLC decoding method using an a priori knowledge of the lengths of the source-symbol sequence and the compressed bit-stream with Maximum A Posteriori (MAP) sequence estimation. Performance in the case of transmission over an Additive White Gaussian Noise (AWGN) channel is evaluated. Simulation results show that the proposed decoding algorithm leads to significant performance gain in comparison with the prefix VLC decoding besides exhibiting very low complexity. A new VLC decoding method generating additional information regarding the reliability of the bits of the compressed bit-stream is also proposed. We consider the serial concatenation of a VLC with two types of channel code and perform iterative decoding. Results show that, when concatenated with a recursive systematic convolutional code (RSCC), iterative decoding provides remarkable error correction performance. In fact, a gain of about 2.3 dB is achieved, in the case of transmission over an AWGN channel, with respect to tandem decoding. Second, we consider a concatenation with a low-density parity-check (LDPC) code and it is shown that iterative joint source/channel decoding outperforms tandem decoding and an additional coding gain of 0.25 dB is achieved.

In this paper a novel joint source channel (JSC) decoding technique is presented. The proposed approach enables iterative decoding for serially concatenated arithmetic codes and convolutional codes. Iterations are performed between Soft In Soft Out (SISO) component decoders. For arithmetic decoding, we proposed to employ a low complex trellis search technique to estimate the best transmitted codewords and generate soft outputs. Performance of the presented system are evaluated in terms of PER, in the case of transmission across the AWGN channel. Simulation results show that the proposed JSC iterative scheme leads to significant gain in comparison with a traditional separated decoding. Finally, the practical relevance of the proposed technique is validated under an image transmission system using the SPIHT codec.