基于隐马尔科夫模型的CPM信号盲Turbo均衡算法

钟凯; 彭华; 葛临东

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

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基于隐马尔科夫模型的CPM信号盲Turbo均衡算法

学术论文 | 更新时间：2024-06-05

- 基于隐马尔科夫模型的CPM信号盲Turbo均衡算法
- Blind Turbo equalization algorithm based on hidden Markov model for continuous phase modulation signals
- 通信学报 2015年36卷第3期页码：170-178
- 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：
  
  [ "钟凯（1987-），男，江苏宿迁人，解放军信息工程大学博士生，主要研究方向为通信信号处理、编码调制。" ]
  [ "彭华（1973-），男，江西萍乡人，解放军信息工程大学教授、博士生导师，主要研究方向为通信信号处理、软件无线电。" ]
  [ "葛临东（1946-），男，安徽怀远人，解放军信息工程大学教授、博士生导师，主要研究方向为通信信号处理、软件无线电。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61072046);河南省基础与前沿技术研究计划基金资助项目(102300410008)
- DOI：10.11959/j.issn.1000-436x.2015071
  中图分类号： TN927
- 网络出版日期：2015-03，
  
  纸质出版日期：2015-03-25
- 稿件说明：
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钟凯, 彭华, 葛临东. 基于隐马尔科夫模型的CPM信号盲Turbo均衡算法[J]. 通信学报, 2015,36(3):170-178.

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.
钟凯, 彭华, 葛临东. 基于隐马尔科夫模型的CPM信号盲Turbo均衡算法[J]. 通信学报, 2015,36(3):170-178. DOI： 10.11959/j.issn.1000-436x.2015071.

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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