• Title/Summary/Keyword: joint parallel iterative decoding

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Generalized Distributed Multiple Turbo Coded Cooperative Differential Spatial Modulation

  • Jiangli Zeng;Sanya Liu;Hui Wang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.3
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    • pp.999-1021
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    • 2023
  • Differential spatial modulation uses the antenna index to transmit information, which improves the spectral efficiency, and completely bypasses any channel side information in the recommended setting. A generalized distributed multiple turbo coded-cooperative differential spatial modulation based on distributed multiple turbo code is put forward and its performances in Rayleigh fading channels is analyzed. The generalized distributed multiple turbo coded-cooperative differential spatial modulation scheme is a coded-cooperation communication scheme, in which we proposed a new joint parallel iterative decoding method. Moreover, the code matched interleaver is considered to be the best choice for the generalized multiple turbo coded-cooperative differential spatial modulation schemes, which is the key factor of turbo code. Monte Carlo simulated results show that the proposed cooperative differential spatial modulation scheme is better than the corresponding non-cooperative scheme over Rayleigh fading channels in multiple input and output communication system under the same conditions. In addition, the simulation results show that the code matched interleaver scheme gets a better diversity gain as compared to the random interleaver.

Error Resilience in Image Transmission Using LVQ and Turbo Coding

  • Hwang, Junghyeun;Joo, Sanghyun;Kikuchi, Hisakazu;Sasaki, Shigenobu;Muramatsu, Shogo;Shin, JaeHo
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.478-481
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    • 2000
  • In this paper, we propose a joint coding system for still images using source coding and powerful error correcting code schemes. Our system comprises an LVQ (lattice vector quantization) source coding for wavelet transformed images and turbo coding for channel coding. The parameters of the image encoder and channel encoder have been optimized for an n-D (dimension) cubic lattice (D$_{n}$, Z$_{n}$), parallel concatenation fur two simple RSC (recursive systematic convolutional code) and an interleaver. For decoding the received image in the case of the AWGN (additive white gaussian noise) channel, we used an iterative joint source-channel decoding algorithm for a SISO (soft-input soft-output) MAP (maximum a posteriori) module. The performance of transmission system has been evaluated in the PSNR, BER and iteration times. A very small degradation of the PSNR and an improvement in BER were compared to a system without joint source-channel decoding at the input of the receiver.ver.

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