In this paper, an innovative joint-source channel coding scheme is presented. The proposed approach enables iterative soft decoding of arithmetic codes by means of a soft-in soft- out decoder based on suboptimal search and pruning of a binary tree. An error-resilient arithmetic coder with a forbidden symbol is used in order to improve the performance of the joint source/channel scheme. The performance in the case of transmission across the AWGN channel is evaluated in terms of word error probability and compared to a traditional separated approach. The interleaver gain, the convergence property of the system, and the optimal source/channel rate allocation are investigated. Finally, the practical relevance of the proposed joint decoding approach is demonstrated within the JPEG 2000 coding standard. In particular, an iterative channel and JPEG 2000 decoder is designed and tested in the case of image transmission across the AWGN channel.

Iterative decoding algorithms may be viewed as high-dimensional nonlinear dynamical systems, depending on a large number of parameters. In this work, we introduce a simplified description of several iterative decoding algorithms in terms of the a posteriori average entropy, and study them as a function of a single parameter that closely approximates the signal-to-noise ratio (SNR). Using this approach, we show that virtually all the iterative decoding schemes in use today exhibit similar qualitative dynamics. In particular, a whole range of phenomena known to occur in nonlinear systems, such as existence of multiple fixed points, oscillatory behavior, bifurcations, chaos, and transient chaos are found in iterative decoding algorithms. As an application, we develop an adaptive technique to control transient chaos in the turbo-decoding algorithm, leading to a substantial improvement in performance. We also propose a new stopping criterion for turbo codes that achieves the same performance with considerably fewer iterations.

This paper addresses the design of semi-random, prunable interleavers for parallel concatenated convolutional codes (PCCC). The proposed technique is iterative and is based on the growth of a smaller interleaver up to the desired length N. The optimization is achieved via a minimization using a cost-function strictly related to both the correlation properties of the extrinsic information and the concept of spread of an interleaver. Performance of the designed interleavers are given in terms of bit error rate (BER) and frame error rate (FER). Comparisons are given with respect to other prunable and ad-hoc interleaver design techniques already proposed in literature. The designed interleavers are prunable and have a behavior very similar to the interleavers designed with techniques which maximize the spread of the permutation

In this paper, we introduce the concept of nonsystematic turbo codes and compare them with classical systematic turbo codes. Nonsystematic turbo codes can achieve lower error floors than systematic turbo codes because of their superior effective free distance properties. Moreover, they can achieve comparable performance in the waterfall region if the nonsystematic constituent encoder has a low-weight feedforward inverse. A uniform interleaver analysis is used to show that rate R=1/3 turbo codes using nonsystematic constituent encoders have larger effective free distances than when systematic constituent encoders are used. Also, mutual information-based transfer characteristics and extrinsic information transfer charts are used to show that rate R=1/3 turbo codes with nonsystematic constituent encoders having low-weight feedforward inverses achieve convergence thresholds comparable to those achieved with systematic constituent encoders. Catastrophic encoders, which do not possess a feedforward inverse, are shown to be capable of achieving low convergence thresholds by doping the code with a small fraction of systematic bits. Finally, we give tables of good nonsystematic turbo codes and present simulation results comparing the performance of systematic and nonsystematic turbo codes.

In this paper an innovative joint source channel coding scheme is presented. The system is based on iterative soft decoding of arithmetic codes, by means of a novel soft-in soft-out decoder based on suboptimal search and pruning of a binary tree. An error resilient arithmetic coder with a forbidden symbol is used in order to improve the performance of the joint source/channel scheme. The performance in the case of transmission across the AWGN channel is evaluated in terms of frame error rate, and compared to a traditional separated approach. Finally the convergence property of the system is analyzed by means of the EXIT chart technique.

In this paper, we address the design of high rate turbo codes using high rate nonsystematic constituent encoders and compare their distance and iterative decoding convergence properties with systematic turbo coding schemes.

We treat the turbo decoding algorithm as a dynamical system parameterized by a single parameter that closely approximates the signal-to-noise ratio (SNR). A whole range of phenomena known to occur in nonlinear systems, like the existence of multiple fixed points, oscillatory behavior, bifurcations, chaos and transient chaos are found in the turbo decoding algorithm. As an application, we have developed a novel stopping criterion based on the average entropy of an information block and propose an adaptive strategy as a function of the SNR.

We compare the convergence thresholds of parallel and serially concatenated codes with interleaver that employ iterative decoding algorithms working at bit or symbol level. The analysis technique is an extension to that of the symbol-level decoder presented by S. ten Brink (see Electron. Lett., vol.35, no.10, p.806-8, 1999), and is valid for very large interleavers. The comparison shows that working at symbol level always yields a lower convergence threshold. In the serial concatenation, the advantage is quite significant.