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 of Serially Concatenated Arithmetic and Channel Codes With JPEG 2000 Applications

Error detection in arithmetic code is usually achieved by inserting markers in the source sequence during encoding. Transmission errors can then be detected in the decoding process if the inserted markers do not appear at the expected positions. Unlike the existing approaches in which the marker symbol is selected from the set of source symbols, we propose that the marker be created artificially so as not to affect the original distribution of the source symbols. Our scheme is proved to possess a better compression ratio than existing marker approaches at the same error misdetection probability. The relationship between codeword length expansion and error misdetection probability within a coded block is well formulated, which makes it easy to adapt to channels with different bit error rates. Simulation results show that, for adaptive arithmetic coding implemented using finite-precision computation, the distribution of error detection delay has a peak at a value slightly larger than the length of the decoding register. With a sufficiently long register, our approach can detect most error patterns in long source sequences at a high probability.

Error detection in arithmetic coding with artificial markers

This paper highlights the implementation challenges faced by the current high performing error resilient joint source channel coding (JSCC) techniques based on the concept of soft-input soft-output (SISO) decoding of arithmetic codes (AC). Further, it proposes several efficient algorithmic and a very large scale integration (VLSI) architectural techniques to improve the throughput performance of SISO for JSCC. The VLSI hardware implementation of the proposed algorithm, when implemented on a 90 nm standard cells technology running at 588 MHz, achieves a decoding throughput of up to 2.63 Mbits/s capable of decoding QCIF format for video conferencing.

A 2.63 Mbit/s VLSI Implementation of SISO Arithmetic Decoders for High Performance Joint Source Channel Codes

We propose an effective error correction technique for arithmetic coding with forbidden symbol. By predicting the occurrence of the subsequent forbidden symbols, the forbidden region is actually expanded and theoretically, a better error correction performance can be achieved. Moreover, a generalized stack algorithm is exploited to detect the forbidden symbol beforehand. The proposed approach is combined with the maximum a posteriori (MAP) metric to keep the highly probable decoding paths in the stack. Simulation results justify that our scheme performs better than the existing MAP methods on the error correction performance, especially at a low coding rate.

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An Effective Error Correction Scheme for Arithmetic Coding

We propose an improved error correction technique for arithmetic coding. By forecasting the forbidden symbols, the effective forbidden region is expanded and a better error correction performance is achieved. A generalized stack algorithm is employed to detect the forbidden symbol beforehand and the maximum a posteriori (MAP) metric is adopted to preserve the most probable decoding paths in the stack. Simulation results justify the effectiveness of our scheme in improving the error correction performance of arithmetic coding, especially at a low coding rate.

Improving the error correction capability of arithmetic coding by forecasting forbidden symbols

This paper provides a joint source channel coding method based on arithmetic coding. The proposed method gives arithmetic coding error detection capability by using its error propagation property and markers. This paper provides theoretical analysis and an experiment with text files.

S. Chokchaitam

Papers

Embedded error detection in arithmetic coding using markers