Joint Source-Channel (De)Coding/Modulation In Communication Systems

The development of wireless and multimedia communications has changed people's lives dramatically. The next generation wireless communications call for ubiquitous, high rate and high quality mobile multimedia transmission. However, limited bandwidth, severe channel and the restriction of resources such as the complexity and power in the terminal especially portable equipments, reveal the limitation of the independent design of source and channel based on Shannon's separation theorem.On the one hand, some residual redundancy is inevitable in the output of the source encoder because of the constraint of complexity and delay in practical encoders, and some redundancy is left in order to improve the robustness at the same time; on the other hand, perfect protection can not be provided by channel encoder because of the limited bandwidth and the effect of the fading and noise simultaneously in wireless channels, so transmission errors are inevitable. Therefore, the novel system design scheme which breaks away from convention and joint information processing to seek for greater performance improvement is needed.Joint source-channel coding/modulation combined source coding (decoding) with channel coding (decoding) and modulation to optimize the communication system synthetically. The destination of this technique is to optimize the communication system from the whole and to reduce the error and distortion from point to point in the system including source and channel. The mainly work is described as follows:1,A joint source-channel coding and modulation scheme is presented. The mapping between source symbols and modulation signals is optimized through the switch search algorithm to decrease the mean square distortion of the false source symbols induced by channel errors. At the same time, the source quantizing distortion is reduced because more bits are allocated to source encoding. The end-to-end performance and robustness of the proposed low complexity joint source-channel coding and modulation system exceed the tandem system.2,The reconstruction of compressed images from the soft output of noisy channel is studied. Combined with SOVA algorithm, the redundancy between the symbols after compression is utilized. Not only the symbol error rate is reduced, but also the soft information of symbols is obtained. According to the correlation between the error square of the symbol value in compression field and the PSNR of reconstructed image, the symbol value is estimated by MMSE estimation with the soft information and used to reconstruct the image to improve PSNR.3,In order to avoid the inaccuracy and transmission cost of the residual redundancy information obtained by the training sequence, an algorithm to estimate the statistical structure of...