Abstract
Abstract Motivated by recent results in Joint Source/Channel coding and decoding, we consider the decoding problem of Arithmetic Codes (AC). In fact, in this article we provide different approaches which allow one to unify the arithmetic decoding and error correction tasks. A novel length-constrained arithmetic decoding algorithm based on Maximum A Posteriori sequence estimation is proposed. The latter is based on soft-input decoding using a priori knowledge of the source-symbol sequence and the compressed bit-stream lengths. Performance in the case of transmission over an Additive White Gaussian Noise channel is evaluated in terms of Packet Error Rate. Simulation results show that the proposed decoding algorithm leads to significant performance gain while exhibiting very low complexity. The proposed soft input arithmetic decoder can also generate additional information regarding the reliability of the compressed bit-stream components. We consider the serial concatenation of the AC with a Recursive Systematic Convolutional Code, and perform iterative decoding. We show that, compared to tandem and to trellis-based Soft-Input Soft-Output decoding schemes, the proposed decoder exhibits the best performance/complexity tradeoff. Finally, the practical relevance of the presented iterative decoding system is validated under an image transmission scheme based on the JPEG 2000 standard and excellent results in terms of decoded image quality are obtained.
Highlights
1 Introduction Joint Source/Channel (JSC) coding and decoding have become an area of strong interest because the separation between source and channel coding has turned out to be unjustified in practical systems due to limited block lengths and the residual redundancy in the data bits which remain after source encoding
The schemes were tested for transmission across an Additive White Gaussian Noise (AWGN) channel with Binary Phase Shift Keying (BPSK) signaling and shows numerous significant advantages
We showed that the soft-input arithmetic decoder achieves good error correction performance, has low complexity and can be extended to adaptive Arithmetic Codes (AC), unlike the trellis-based arithmetic decoders
Summary
Joint Source/Channel (JSC) coding and decoding have become an area of strong interest because the separation between source and channel coding has turned out to be unjustified in practical systems due to limited block lengths and the residual redundancy in the data bits which remain after source encoding. We propose a new low-complexity arithmetic decoder that supposes the decoder to know the source symbol sequence length L and the compressed bit-stream size l. Static arithmetic coding supposes that source statistics were transmitted to the decoder with no error, which results in additional bits and a compression loss Such situation is outperformed with adaptive arithmetic coding, where p0 and p1 are initialized to 0.5, for every symbol encoding step they are updated. We address new soft-input decoding scheme which can be applied to both adaptive and static ACs. To manage AC sensitivity to errors, authors of [6] proposed to use an extra symbol μ with probability ε > 0 to detect transmission errors. In the presence of transmission error, due to the low resynchronization probability, the decoder will reveal a forbidden symbol after a delay that is inversely proportional to ε
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