Abstract
This article proposes a joint source-channel coding technique for two-dimensional (2D) binary Markov sources by using concatenated turbo block codes composed of two Bose, Chaudhuri, Hocquenghem (BCH) codes, of which output is followed by a rate-1 recursive systematic convolutional code. The source correlation of all rows and columns of the 2D source is well exploited by using a modified Bahl–Cocke–Jelinek–Raviv (BCJR) algorithm for the decoding of the BCH codes. Simulation results show that the proposed technique outperforms in terms of bit error rate the codes that exploits one-dimensional (1D) source correlation using the modified BCJR algorithm, and obviously the conventional system without source correlation exploitation. In order to further improve the performance, this article aims to make fine-tuning of the code parameters, given the source correlation property, that can achieve performance even closer to the theoretical limit than without the fine-tuning. Finally, results of image transmission simulations using two images, one having strong and the other weak 2D correlation, are presented to demonstrate the effectiveness of our proposed technique.
Highlights
According to the Shannon’s separation theorem, the optimal design of the source and channel codes can be sought for independently, so far as the source entropy rate is lower than the channel capacity [1]
In order to reduce the gap to the limit especially for strong source correlation case, we have evaluated the bit error rate (BER) performance by using different BCH codes for C1 and C2, and different recursive systematic convolutional (RSC) codes for C3
6 Conclusions In this article, a joint source-channel coding (JSCC) technique utilizing the correlation of 2D binary Markov sources using high rate codes has been proposed
Summary
According to the Shannon’s separation theorem, the optimal design of the source and channel codes can be sought for independently, so far as the source entropy rate is lower than the channel capacity [1]. For the 2D Markov source, the output Un,t of the current state is determined by two factors; the previous state in the horizontal direction, Un,t−1 and that in the vertical direction, Un−1,t, where t and n are the timing indexes of the 2D source in the horizontal and vertical directions, respectively. This 2D source correlation model can be considered as a two-dimensionally coupled first-order Markov chains and the corresponding transition matrix of the 2D source can be represented by using a coupled Markov chain (CMC) model [15].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: EURASIP Journal on Wireless Communications and Networking
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
