Distributed Joint Source-Channel Coding for Correlated Sources Using Non-systematic Repeat-Accumulate Based Codes

In this paper, we propose a technique for coding the data from multiple correlated binary sources, with the aim of providing an alternative solution to the correlated source compression problem. Using non-systematic repeat-accumulate based codes, it is possible to achieve compression which is close to the Slepian–Wolf bound without relying on massive puncturing. With the technique proposed in this paper, instead of puncturing, compression is achieved by increasing check node degrees. Hence, the code rate can be more flexibly adjusted with the proposed technique in comparison with the puncturing-based schemes. Furthermore, the technique is applied to distributed joint source-channel coding (DJSCC). It is shown that in many cases tested, the proposed scheme can achieve mutual information very close to one with the lower signal-to-noise power ratio than turbo and low density generator matrix based DJSCC in additive white Gaussian noise channel. The convergence property of the system is also evaluated via the extrinsic information transfer analysis.