系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (2): 589-596.doi: 10.12305/j.issn.1001-506X.2023.02.32

• 通信与网络 • 上一篇    

利用联合特征参数的卫星单-混信号调制识别

龚佩, 李天昀, 章昕亮, 寸陈韬   

  1. 信息工程大学信息系统工程学院, 河南 郑州 450001
  • 收稿日期:2021-09-26 出版日期:2023-01-13 发布日期:2023-02-04
  • 通讯作者: 李天昀
  • 作者简介:龚佩(1998—), 女, 硕士研究生, 主要研究方向为通信信号处理
    李天昀(1979—), 男, 副教授, 博士, 主要研究方向为通信信号处理、软件无线电
    章昕亮(1998—), 男, 硕士研究生, 主要研究方向为通信信号处理
    寸陈韬(1994—), 男, 硕士研究生, 主要研究方向为通信信号处理

Modulation recognition for satellite single-mixed signals using joint characteristic parameters

Pei GONG, Tianyun LI, Xinliang ZHANG, Chentao CUN   

  1. College of Information System Engineering, Information Engineering University, Zhengzhou 450001, China
  • Received:2021-09-26 Online:2023-01-13 Published:2023-02-04
  • Contact: Tianyun LI

摘要:

针对卫星通信中常见的单-混二进制相移键控(binary phase shift keying, BPSK)、正交相移键控(quadrature phase shift keying, QPSK)、8进制相移键控(8 phase shift keying, 8PSK)、16进制正交幅度调制(16 quadrature amplitude modulation, 16QAM)信号调制识别问题, 本文基于不同信号的累积量差异和方谱特性, 充分利用累积量和谱线特征并构造合理的特征参数, 最终构建决策树分类器, 实现了这些信号的调制识别, 并有效实现了混合QPSK和混合8PSK信号的识别。实验表明, 该算法能够实现高斯白噪声条件下的单-混BPSK、QPSK、8PSK、16QAM信号的分类。当信噪比大于6 dB时, 除混合QPSK和混合8PSK信号外, 其他信号的调制识别率能达到98%, 当信噪比大于10 dB时, 混合QPSK和混合8PSK信号的调制识别率能达到92%。与现有算法相比, 识别率更高, 由此证明所提算法的有效性。

关键词: 调制识别, 累积量, 方谱特性, 特征参数, 决策树分类器

Abstract:

In view of the common single-mix binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), 8 phase shift keying (8PSK) and 16 quadrature amplitude modulation (16QAM) signal modulation recognition problems in satellite communications, based on the cumulative differencesand spectrum characteristics of different modulating signal, we make full use of the cumulants and spectral characteristics and construct reasonable characteristic parameters, and finally build a decision tree classifier. It achieves the modulation recognition of these signal, and effectively realizes the recognition of mixed QPSK and mixed 8PSK signals. Test shows that the algorithm can achieve the classification of single-mix BPSK, QPSK, 8PSK and 16QAM signals affected by Gaussian white noise. When the signal-to-noise ratio is greater than 6 dB, except mixed QPSK and mixed 8PSK signals, the modulation recognition rate of other signals can reach 98%. When the signal-to-noise ratio is greater than 10 dB, the modulation recognition rate of mixed QPSK and mixed 8PSK signals can reach 92%. Compared with the existing algorithms, the recognition rate is higher, which proves the effectiveness of the proposed algorithm.

Key words: modulation recognition, cumulant, spectrum characteristics, characteristic parameters, decision tree classifier

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