Joint Decoding and Estimation of Spatio-Temporally Correlated Binary Sources

In the context of distributed joint source-channel coding, we conceive a joint decoding and estimation scheme for binary Markov sources exhibiting spatio-temporal correlation. The proposed scheme is designed based on the serial concatenation of a trellis coded modulation (TCM) scheme and a unity-rate code. The symbol-based maximum a posteriori algorithm employed for TCM decoding is modified in order to exploit the source correlation. The estimation of both the spatial and temporal correlation parameters is performed jointly with the iterative decoding, hence allowing the estimated parameters to be updated after each iteration. Our simulation results reveal that when both the spatial and temporal correlation parameters are unknown, the proposed joint decoding and estimation scheme approaches the performance to the ideal system relying on perfectly known correlation parameters, therefore, demonstrating the superiority of the proposed scheme.

[1]  Xiaobo Zhou,et al.  Exploitation of 2D binary source correlation using turbo block codes with fine-tuning , 2013, EURASIP J. Wirel. Commun. Netw..

[2]  T. H. Liew,et al.  Turbo Coding, Turbo Equalisation and Space-Time Coding: EXIT-Chart-Aided Near-Capacity Designs for Wireless Channels , 2011 .

[3]  Fred Daneshgaran,et al.  LDPC-based channel coding of correlated sources with iterative joint decoding , 2006, IEEE Transactions on Communications.

[4]  B. L. Yeap,et al.  Turbo Coding, Turbo Equalisation and Space-Time Coding , 2002 .

[5]  Gottfried Ungerboeck,et al.  Channel coding with multilevel/phase signals , 1982, IEEE Trans. Inf. Theory.

[6]  Xiaobo Zhou,et al.  Serially concatenated joint source-channel coding for binary Markov sources , 2011, 2011 6th International ICST Conference on Communications and Networking in China (CHINACOM).

[7]  Ying Zhao,et al.  Near-Shannon/Slepian-Wolf performance for unknown correlated sources over AWGN channels , 2005, IEEE Transactions on Communications.

[8]  Lajos Hanzo,et al.  Distributed Source Coding and Its Applications in Relaying-Based Transmission , 2016, IEEE Access.

[9]  Lie-Liang Yang,et al.  Iteratively Decoded Variable Length Space-Time Coded Modulation: Code Construction and Convergence Analysis , 2007, IEEE Transactions on Wireless Communications.

[10]  Jingxian Wu,et al.  Distributed joint source-channel code for spatial-temporally correlated Markov sources , 2013, 2013 IEEE International Conference on Communications (ICC).

[11]  Ying Zhao,et al.  Joint estimation and compression of correlated nonbinary sources using punctured turbo codes , 2005, IEEE Transactions on Communications.

[12]  Fred Daneshgaran,et al.  Iterative joint channel decoding of correlated sources employing serially concatenated convolutional codes , 2005, IEEE Transactions on Information Theory.

[13]  Lajos Hanzo,et al.  Distributed Joint Source Coding and Trellis Coded Modulation for Symbol-Based Markov Sources , 2018, IEEE Transactions on Vehicular Technology.

[14]  Lajos Hanzo,et al.  Distributed Source–Channel Coding Using Reduced-Complexity Syndrome-Based TTCM , 2016, IEEE Communications Letters.

[15]  Lajos Hanzo,et al.  TTCM-Aided Rate-Adaptive Distributed Source Coding for Rayleigh Fading Channels , 2014, IEEE Transactions on Vehicular Technology.

[16]  Xiaobo Zhou,et al.  Distributed joint source-channel coding for relay systems exploiting source-relay correlation and source memory , 2012, EURASIP J. Wirel. Commun. Netw..

[17]  Pradeepa Yahampath,et al.  Distributed Joint Source-Channel Coding Using Unequal Error Protection LDPC Codes , 2013, IEEE Transactions on Communications.

[18]  Lajos Hanzo,et al.  Spatio-Temporal Iterative Source–Channel Decoding Aided Video Transmission , 2013, IEEE Transactions on Vehicular Technology.