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Using LMS weighting value as the CSI for soft decision Viterbi decoder

Using LMS weighting value as the CSI for soft decision Viterbi decoder. Advisor : Yung-An Kao Student : Chi-Ting Wu 2005.01.28. Outline. Introduction Block diagram Formula computation Simulation results Conclusion. Introduction.

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Using LMS weighting value as the CSI for soft decision Viterbi decoder

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  1. Using LMS weighting value as the CSI for soft decision Viterbi decoder Advisor : Yung-An Kao Student : Chi-Ting Wu 2005.01.28

  2. Outline • Introduction • Block diagram • Formula computation • Simulation results • Conclusion

  3. Introduction • For Viterbi decoder, we view different sub-carriers in the same channel condition • Actually, different sub-carrier suffers different channel condition • Using the CSI for each sub-carriers • long train symbol? What else? • equalizer weighting values !!

  4. Block diagram

  5. Formula computation • According to the Central Limit Theorem, after we transmit lots of symbols, they all seems like Gaussian distribution • The likelihood function will become

  6. Formula computation And we know that the weighting value is The received signal after phase compensation is

  7. Formula computation We want the same weighting value for Therefore, we use the weighting value : And we take the expected value

  8. Simulation ~ interleaver 500 symbols 100 times average 1:1:15 dB CFO=0.01 No SFO Trms=50ns 4 bit quantization No weighting value

  9. Simulation ~ quantization 100 symbols 100 times average 1:1:15 dB CFO=0.01 No SFO Trms=50ns No weighting value

  10. Simulation ~ weighted CSI 500 symbols 100 times average 1:1:15 dB CFO=0.01 No SFO Trms=50ns 4 bit quantization With interleaver

  11. Simulation ~ weighted CSI 1000 symbols 100 times average 1:1:15 dB CFO=0.01 No SFO Trms=50ns 4 bit quantization With interleaver

  12. Conclusion • Weighting values added should has better performance • Some dimension problems should take notice

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