Spatio-Temporal Iterative Source–Channel Decoding Aided Video Transmission

Low-complexity uncompressed video transmission meets the requirements of home networking and quality/delay-sensitive medical applications. Hence, it has attracted research attention in recent years. The redundancy inherent in the uncompressed video signals may be exploited by joint source-channel decoding to improve the attainable error resilience. Hence, in this treatise, we study the application of iterative joint source-channel decoding aided uncompressed video transmission, where correlation inherent in the video signals is modeled by a first-order Markov process. First, we propose a spatiotemporal joint source-channel decoding system using a recursive systematic convolutional codec, where both the horizontal and vertical intraframe correlations, as well as the interframe correlations, are exploited by the receiver, hence relying on 3-D information exchange. This scheme may be combined with arbitrary channel codecs. Then, we analyze the three-stage decoder´s convergence behavior using 3-D extrinsic information transfer (EXIT) charts. Finally, we benchmark the attainable system performance against a couple of video communication systems, including our previously proposed 2-D scheme, where only intraframe correlations were exploited without invoking a channel codec. Our simulation results show that substantial E_b/N₀ improvements are attainable by the proposed technique.