Blind Turbo equalization algorithm based on hidden Markov model for continuous phase modulation signals

Kai ZHONG; Hua PENG; Lin-dong GE

doi:10.11959/j.issn.1000-436x.2015071

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Blind Turbo equalization algorithm based on hidden Markov model for continuous phase modulation signals

Academic paper | 更新时间：2024-06-05

- Blind Turbo equalization algorithm based on hidden Markov model for continuous phase modulation signals
- Journal of Communications Vol. 36, Issue 3, Pages: 170-178(2015)
- 作者机构：
  
  解放军信息工程大学信息系统工程学院，河南郑州 450002
- 作者简介：
- 基金信息：
  
  TheNationalNaturalScienceFoundationofChina(61072046);The Foundation and Frontier Technology Re-search Program of Henan Province(102300410008)
- DOI：10.11959/j.issn.1000-436x.2015071
  CLC： TN927
- Online First：2015-03，
  
  Published：25 March 2015
- 稿件说明：
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Kai ZHONG, Hua PENG, Lin-dong GE. Blind Turbo equalization algorithm based on hidden Markov model for continuous phase modulation signals[J]. Journal of Communications, 2015, 36(3): 170-178.
DOI：

Kai ZHONG, Hua PENG, Lin-dong GE. Blind Turbo equalization algorithm based on hidden Markov model for continuous phase modulation signals[J]. Journal of Communications, 2015, 36(3): 170-178. DOI： 10.11959/j.issn.1000-436x.2015071.

摘要

针对高阶连续相位调制信号(CPM)盲均衡中存在的均衡性能较差以及不容易收敛等问题，从隐马尔科夫模型(HMM)的角度出发，建立一种新的EM-SOVA信道盲均衡方法，并结合Turbo均衡思想，提出了一种适用于高阶CPM信号的盲Turbo均衡算法。该算法通过将SOVA内嵌到EM算法的迭代过程中，有效改善了信道均衡效果，同时使用Turbo均衡的软信息迭代处理来进一步提高低信噪比条件下系统性能。理论分析和仿真结果表明，所提算法具有良好的盲均衡性能以及收敛性。

Abstract

To solve the issues of the poor performance and convergence difficulties in the blind equalization of high order continuous phase modulation (CPM) signals

a new EM-SOVA channel blind equalization method was developed from the perspective of hidden Markov model(HMM). A novel blind Turbo equalization algorithm for high order CPM signals was proposed based on the combination of this method and Turbo equalization. The algorithm improved the equalization performance by applying the soft-output Viterbi algorithm(SOVA) within an EM iteration. Simultaneously

a soft infor-mation iterative process was used for further improvement of the system performance at a low signal-to-noise ratio. The analysis and simulation results show that the proposed algorithm provides a good blind equalization performance and convergence.

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references

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