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UTILIZING CHANNEL CODING INFORMATION IN CIVA-BASED BLIND SEQUENCE DETECTORS

UTILIZING CHANNEL CODING INFORMATION IN CIVA-BASED BLIND SEQUENCE DETECTORS. Xiaohua(Edward) Li Department of Electrical and Computer Engineering State University of New York at Binghamton xli@binghamton.edu, http://ucesp.ee.binghamton.edu/~xli. Contents. Introduction System models

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UTILIZING CHANNEL CODING INFORMATION IN CIVA-BASED BLIND SEQUENCE DETECTORS

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  1. UTILIZING CHANNEL CODING INFORMATION IN CIVA-BASED BLIND SEQUENCE DETECTORS Xiaohua(Edward) Li Department of Electrical and Computer Engineering State University of New York at Binghamton xli@binghamton.edu, http://ucesp.ee.binghamton.edu/~xli

  2. Contents • Introduction • System models • Joint CIVA and channel decoding • Simulations • Conclusions

  3. I Introduction • Problems in blind equalization • Not robust to ill-conditioned channels • Local convergence, slow convergence (SISO methods) • Can not resolve common roots among sub-channels (SIMO methods)

  4. CIVA(channel independent Viterbi algorithm) [1]: effective blind equalizer • Robust to all channel conditions • Superior near MLSE performance • Fast convergence • Propose: CIVA/decoder • Integrate convolutional decoder in CIVA • Use channel coding information to reduce complexity, save hardware

  5. II System Model

  6. Vector model

  7. III CIVA/Decoder • Blind sequence detection

  8. Implement as trellis search • Metric updating rule • Example of trellis and probe

  9. CIVA/Decoder Properties • Have the advantages of both CIVA and channel decoder • Reduce complexity and hardware

  10. IV Simulations • Convolutional encoder: rate ½ • Channel length: 3 • CIVA/Decoder: 32 states • CIVA: 128 states • CIVA/decoder performs better with reduced complexity

  11. Random 3-tap channels. BPSK. 400 samples. Compare: • CIVA: blind CIVA/decoder • MLSE: optimal • VA: training • MMSE: training • PSP: with decision feedback

  12. V Conclusions • CIVA/Decoder: new blind equalizer, integrate convolutional decoding in the channel-independent Viterbi algorithm • Superior near MLSE performance • Robust to even ill-conditioned channels • Reduced complexity and hardware • Reference: • X. Li, “Blind sequence detection without channel estimation,” to appear in IEEE Trans. Signal Processing. A part appears in the 35th Asilomar Conf. Signals, Syst., Comput., Oct 2001.

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