Exploiting 2-Dimensional Source Correlation in Channel Decoding with Parameter Estimation

Traditionally, it is assumed that source coding is perfect and therefore, the redundancy of the source encoded bit-stream is zero. However, in reality, this is not the case as the existing source encoders are imperfect and yield residual redundancy at the output. The residual redundancy can be exploited by using Joint Source Channel Coding (JSCC) with Markov chain as the source. In several studies, the statistical knowledge of the sources has been assumed to be perfectly available at the receiver. Although the result was better in terms of the BER performance, practically, the source correlation knowledge were not always available at the receiver and thus, this could affect the reliability of the outcome. The source correlation on all rows and columns of the 2D sources were well exploited by using a modified Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm in the decoder. A parameter estimation technique was used jointly with the decoder to estimate the source correlation knowledge. Hence, this research aims to investigate the parameter estimation for 2D JSCC system which reflects a practical scenario where the source correlation knowledge are not always available. We compare the performance of the proposed joint decoding and estimation technique with the ideal 2D JSCC system with perfect knowledge of the source correlation knowledge. Simulation results reveal that our proposed coding scheme performs very close to the ideal 2D JSCC system

EXIT Chart Based Joint Source-Channel Coding for Binary Markov Sources

In this paper, we propose a new joint source-channel decoding technique for transmitting binary Markov sources over AWGN channels. Our approach is based on serially concatenated coding and code doping for inner code. By combining the Markov source and the outer code trellis diagrams, a super trellis is constructed to exploit the time-domain correlation of the source. A modified version of BCJR algorithm is derived based on this super trellis, that can achieve considerable gain in terms of mutual information. The standard BCJR algorithm is used for decoding of inner code where code doping is adopted for better matching of extrinsic information transfer (EXIT) characteristics. EXIT chart analysis is performed to investigate convergence property of the proposed technique and to optimize the code parameters. Simulation results for bit error rate (BER) evaluation and EXIT chart analysis indicate that the proposed technique can achieve significant gains over the system in which source redundancy are not exploited, and thereby the BER performance of the proposed system is very close to the Shannon limit