基于自适应小波消噪的数字调制识别优化算法

谭晓衡; 鄢海燕; 苏萌

doi:10.3724/SP.J.1146.2010.00349

基于自适应小波消噪的数字调制识别优化算法

doi: 10.3724/SP.J.1146.2010.00349

基金项目:

中央高校基本科研业务费(CDJZR10 16 00 11)和重庆市自然科学基金(2010BB2049)资助课题

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出版历程
- 收稿日期: 2010-04-06
- 修回日期: 2010-09-21
- 刊出日期: 2011-02-19

An Optimal Algorithm of Digital Modulation Recognition Based on Adaptive Wavelet De-noising

摘要

摘要: 为了改善数字调制识别在低信噪比下的识别性能，该文提出了基于瞬时信息的自适应小波阈值消噪的调制识别优化算法。该方法采用自适应小波阈值消噪算法对瞬时信息进行消噪以提高瞬时信息的信噪比，并在已有的两个特征参数ap和df的基础上，改进了特征参数Ra和Ra，以降低判决门限设置的敏感度。仿真结果表明，即使在信噪比低达1 dB时，7种数字调制的成功识别率都达到96%以上。与已有算法相比，该优化算法具有实现简单、计算量小和极低信噪比下识别率高等优点。
- 数字调制识别 /
- 瞬时信息 /
- 自适应小波阈值消噪
Abstract: An optimal algorithm based on adaptive wavelet de-noising is proposed to improve effectively the performance of digital modulation recognition under low Signal to Noise Ratio (SNR). An adaptive wavelet threshold de-noising filter is used to eliminate the noise in instantaneous information and improve the SNR. And two parameters Ra, Ra are improved based on two existing parameters ap, df to reduce the sensitivity to noise threshold. Simulation results show that recognition probability of 7 types of digital modulation signals is all above 96%, even SNR is down to 1 dB. Compared with existing algorithm, the proposed algorithm is easy to implement, which has lower computational costs, higher recognition probability.
- Digital modulation recognition /
- Instantaneous information /
- Adaptive wavelet threshold de-noising

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