Soft and Joint Source-Channel Decoding of Quasi-Arithmetic Codes

Abstract

The issue of robust and joint source-channel decoding of quasi-arithmetic codes is addressed. Quasi-arithmetic coding is a reduced precision and complexity implementation of arithmetic coding. This amounts to approximating the distribution of the source. The approximation of the source distribution leads to the introduction of redundancy that can be exploited for robust decoding in presence of transmission errors. Hence, this approximation controls both the trade-off between compression efficiency and complexity and at the same time the redundancy (excess rate) introduced by this suboptimality. This paper provides first a state model of a quasi-arithmetic coder and decoder for binary and -ary sources. The design of an error-resilient soft decoding algorithm follows quite naturally. The compression efficiency of quasi-arithmetic codes allows to add extra redundancy in the form of markers designed specifically to prevent desynchronization. The algorithm is directly amenable for iterative source-channel decoding in the spirit of serial turbo codes. The coding and decoding algorithms have been tested for a wide range of channel signal-to-noise ratios (SNRs). Experimental results reveal improved symbol error rate (SER) and SNR performances against Huffman and optimal arithmetic codes.

Keywords

• robust arithmetic and quasi-arithmetic coding
• joint source-channel coding
• soft decoding
• estimation
• MAP