Analytical tools for optimizing the error correction performance of arithmetic codes

International audienceIn joint source-channel arithmetic coding (JSCAC) schemes, additional redundancy may be introduced into an arithmetic source code in order to be more robust against transmission errors. The purpose of this work is to provide analytical tools to predict and evaluate the effectiveness of that redundancy. Integer binary Arithmetic Coding (AC) is modeled by a reduced-state automaton in order to obtain a bit-clock trellis describing the encoding process. Considering AC as a trellis code, distance spectra are then derived. In particular, an algorithm to compute the free distance of an arithmetic code is proposed. The obtained code properties allow to compute upper bounds on both bit error and symbol error probabilities and thus provide an objective criterion to analyze the behavior of JSCAC schemes when used on noisy channels. This criterion is then exploited to design efficient error-correcting arithmetic codes. Simulation results highlight the validity of the theoretical error bounds and show that for equivalent rate and complexity, a simple optimization yields JSCACs that outperform classical tandem schemes at low to medium SNR

Analysis of Joint Source Channel LDPC Coding for Correlated Sources Transmission over Noisy Channels

In this paper, a Joint Source Channel coding scheme based on LDPC codes is investigated. We consider two concatenated LDPC codes, one allows to compress a correlated source and the second to protect it against channel degradations. The original information can be reconstructed at the receiver by a joint decoder, where the source decoder and the channel decoder run in parallel by transferring extrinsic information. We investigate the performance of the JSC LDPC code in terms of Bit-Error Rate (BER) in the case of transmission over an Additive White Gaussian Noise (AWGN) channel, and for different source and channel rate parameters. We emphasize how JSC LDPC presents a performance tradeoff depending on the channel state and on the source correlation. We show that, the JSC LDPC is an efficient solution for a relatively low Signal-to-Noise Ratio (SNR) channel, especially with highly correlated sources. Finally, a source-channel rate optimization has to be applied to guarantee the best JSC LDPC system performance for a given channel

Study and simulation of low rate video coding schemes

The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design

Joint Exploitation of Residual Source Information and MAC Layer CRC Redundancy for Robust Video Decoding

International audienceThis paper presents a MAP estimation method allowing the robust decoding of compressed video streams by exploiting the bitstream structure (i.e., information about the source, related to variable-length codes and source characteristics) together with the knowledge of the MAC layer CRC (here considered as additional redundancy on the MAC packet). This method is implemented via a sequential decoding algorithm in which the branch selection metric in the decoding trellis incorporates a CRC-dependent factor, and the paths which are not compatible with the source constraints are pruned. A first implementation of the proposed algorithm performs exact computations of the metrics, and is thus computationally expensive. Therefore, we also introduce a suboptimal (with tunable complexity) version of the proposed metric computation. This technique is then applied to the robust decoding of sequences encoded using the H.264/AVC standard based on CAVLC, and transmitted using aWiFi-like packet structure. Significant link budget improvement results are demonstrated for BPSK modulated signals sent over AWGN channels, even in the presence of channel coding