Blind Equalization Based on FABA-SISO for Continuous Phase Modulation Signals over Time-varying Frequency-selective Fading Channels

Zhong Kai; Peng Hua; Ge Lin-dong

doi:10.11999/JEIT150026

Volume 37 Issue 11

Nov. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(11): 2672-2677

Zhong Kai, Peng Hua, Ge Lin-dong. Blind Equalization Based on FABA-SISO for Continuous Phase Modulation Signals over Time-varying Frequency-selective Fading Channels[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2672-2677. doi: 10.11999/JEIT150026

Citation:

Zhong Kai, Peng Hua, Ge Lin-dong. Blind Equalization Based on FABA-SISO for Continuous Phase Modulation Signals over Time-varying Frequency-selective Fading Channels[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2672-2677. doi: 10.11999/JEIT150026

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Blind Equalization Based on FABA-SISO for Continuous Phase Modulation Signals over Time-varying Frequency-selective Fading Channels

doi: 10.11999/JEIT150026

Funds:

The National Natural Science Foundation of?China?(61072046)

Received Date: 2015-01-06
Rev Recd Date: 2015-07-03
Publish Date: 2015-11-19

Abstract

Abstract

To solve the issues of the high complexity, poor performance, and slow convergence speed in the blind equalization of high order Continuous Phase Modulation (CPM) signals, a new blind equalization method based on Forward Adaptive Backward Adaptive Soft-Input Soft-Output (FABA-SISO) algorithm used in linear modulation signals is developed from the perspective of bidirectional adaptive channel equalization. A novel adaptive blind equalization algorithm for high order CPM signals is proposed based on the combination of Per-Survivor Processing (PSP) and Kalman filtering. The algorithm improves the equalization performance by applying the FABA-SISO which uses the past, the present and the future observation to implement Kalman filtering channel estimation. Simultaneously, a PSP algorithm is used for further improvement of the system complexity, so that the algorithm is better suitable for engineering application. The simulation results show that the proposed algorithm provides a good blind equalization performance and convergence.

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References(16)

References

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