计算机应用 ›› 2012, Vol. 32 ›› Issue (08): 2123-2127.DOI: 10.3724/SP.J.1087.2012.02123

• 网络与通信 • 上一篇    下一篇

多径信道下基于循环谱特征的调制识别算法

李世平,陈方超,王隆,王爱红   

  1. 东北大学 信息科学与工程学院,沈阳 110819
  • 收稿日期:2012-02-13 修回日期:2012-03-28 发布日期:2012-08-28 出版日期:2012-08-01
  • 通讯作者: 陈方超
  • 作者简介:李世平(1960-),男,辽宁沈阳人,副教授,博士研究生,主要研究方向:信号处理;
    陈方超(1987-),男,辽宁沈阳人,硕士研究生,主要研究方向:信号处理、通信信号调制识别;
    王隆(1988-),男,湖南张家界人,硕士研究生,主要研究方向:MIMO通信系统的信号检测
    王爱红(1988-),女,山东菏泽人,硕士研究生,主要研究方向:无线通信、通信系统中信道均衡。

Modulation identification algorithm based on cyclic spectrum characteristics in multipath channel

LI Shi-ping,CHEN Fang-chao,WANG Long,WANG Ai-hong   

  1. College of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110819, China
  • Received:2012-02-13 Revised:2012-03-28 Online:2012-08-28 Published:2012-08-01
  • Contact: CHEN Fang-chao

摘要: 针对多径衰落环境下通信信号调制方式识别算法识别类型少、稳定的特征参数提取困难、识别率低的问题,提出一种基于循环谱特征的自动识别算法。首先,提取待识别信号循环谱、平方循环谱及四次方循环谱的特征面和投影面;然后,利用特征面和投影面的相关系数作为特征参数;最后,选择合适的判决门限,对BPSK、QPSK、2FSK、4FSK、MSK、16QAM和OFDM信号进行自动识别。实验表明,该算法提取的特征参数抗多径干扰能力强,识别率高;当信噪比大于2dB时其总体识别率达到94%以上。与已有算法的比较结果也证明了该算法的优越性。

关键词: 多径信道, 循环谱特征, 调制识别, 特征参数, 识别率

Abstract: A new algorithm based on cyclic spectrum was proposed for classification of communication signals in multipath channel, which solved the problems of fewer identification types, difficults table feature parameters extraction and low recognition rate. Firstly, the features face and projective planes of cyclic spectrum, square cyclic spectrum and the fourth power cyclic spectrum were extracted. Secondly, correlation coefficients of features face and projective planes were used as the characteristic parameters. At last, the suitable decision threshold was chosen and seven signals of BPSK, QPSK, 2FSK, 4FSK, MSK, 16QAM and OFDM were identified automatically. The experimental results show that the characteristic parameters have great ability for multipath interference and high recognition rate is acquired at last. When the Signal-to-Noise Ratio (SNR) is higher than 2dB, its overall recognition rate is up to 94%. Compared with the existing algorithms, the simulation results prove that the algorithm is superior.

Key words: multipath channel, cyclic spectrum characteristic, modulation identification, characteristic parameter, recognition rate

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