Joint Source Channel Decoding Exploiting 2D Source Correlation with Parameter Estimation for Image Transmission over Rayleigh Fading Channels
Keywords:Joint Source Channel Coding, Baum-Welsh Algorithm, Markov Chain, 2-Dimensional Source Correlation, Turbo Coding
AbstractThisÂ paperÂ investigatesÂ theÂ performanceÂ ofÂ aÂ 2- DimensionalÂ (2D)Â JointÂ SourceÂ ChannelÂ CodingÂ (JSCC)Â system assistedÂ withÂ parameterÂ estimationÂ forÂ 2DÂ imageÂ transmission overÂ anÂ AdditiveÂ WhiteÂ GaussianÂ NoiseÂ (AWGN)Â channelÂ and aÂ RayleighÂ fadingÂ channel.Â Baum-WelshÂ AlgorithmÂ (BWA) Â is employedÂ inÂ theÂ proposedÂ 2DÂ JSCCÂ systemÂ toÂ estimateÂ the source correlation statistics during channel decoding. The source correlation is then exploited during channel decoding using a Modified Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. The performance of the 2D JSCC system with the BWA-based parameter estimation technique (2D-JSCC-PET1) is evaluated via image transmission simulations.Â TwoÂ images,Â eachÂ exhibitsÂ strongÂ and weakÂ sourceÂ correlationÂ areÂ consideredÂ inÂ theÂ evaluationÂ by measuring the Peak Signal Noise Ratio of the decoded images at theÂ receiver.Â The proposed 2D-JSCC-PET1 system is compared with various benchmark systems. Simulation results reveal that the 2D-JSCC-PET1 system outperforms the other benchmark systems (performance gain of 4.23 dB over the 2D-JSCC-PET2 system and 6.10 dB over the 2D JSCC system).Â The proposed system also can perform very close to the ideal 2D JSCC system relying on the assumption of perfect source correlation knowledge at the receiver that shown only 0.88 dB difference in performance gain.
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