系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (1): 19-25.doi: 10.3969/j.issn.1001-506X.2021.01.03

• 电子技术 • 上一篇    下一篇

AL-OFDM和SM-OFDM空频分组码信号盲识别方法

凌青1(), 闫文君2,*(), 张立民2(), 于柯远2()   

  1. 1. 海军航空大学航空通信教研室, 山东 烟台 264001
    2. 海军航空大学信息融合研究所, 山东 烟台 264001
  • 收稿日期:2020-02-19 出版日期:2020-12-25 发布日期:2020-12-30
  • 通讯作者: 闫文君 E-mail:linqing19870522@163.com;wj_yan@foxmial.com;iamzlm@163.com;gfsskfqp@163.com
  • 作者简介:凌青(1987-),女,副教授,博士,主要研究方向为通信信号智能处理。E-mail:linqing19870522@163.com|张立民(1966-),男,教授,博士研究生导师,博士,主要研究方向为电子设备仿真以及信号处理。E-mail:iamzlm@163.com|于柯远(1992-),男,博士研究生,主要研究方向为空频分组码智能处理。E-mail:gfsskfqp@163.com
  • 基金资助:
    泰山学者工程专项基金(ts201511020);国家自然科学基金重大研究计划(91538201)

Blind signal recognition method of AL-OFDM and SM-OFDM space-frequency block codes

Qing LING1(), Wenjun YAN2,*(), Limin ZHANG2(), Keyuan YU2()   

  1. 1. Aeronautical Communications Teaching and Research Office, Naval Aviation University, Yantai 264001, China
    2. Information Fusion Institute, Naval Aviation University, Yantai 264001, China
  • Received:2020-02-19 Online:2020-12-25 Published:2020-12-30
  • Contact: Wenjun YAN E-mail:linqing19870522@163.com;wj_yan@foxmial.com;iamzlm@163.com;gfsskfqp@163.com

摘要:

针对空频分组码-正交频分复用(space-frequency block codes with orthogonal frequency division multiplexing, SFBC-OFDM)信号盲识别问题,提出了一种基于互相关函数的空频分组码信号盲识别方法。首先根据不同SFBC-OFDM元素的相关性,推导了发射信号端信号的相关特性;然后根据发射端信号的相关性,推导了接收端SFBC-OFDM信号的相关特性;最后提出了基于峰值检测的识别算法。仿真结果表明,该算法在较低的信噪比(0 dB)下正确识别概率达到95%,且不需要预先知道信道信息、噪声信息和调制信息。该算法在不同调制方式、时延和频率偏移下正确识别概率在90%以上,能够应用于认知无线电、频谱监控等工程领域中。

关键词: 信号盲识别, 空频分组码, 互相关函数, 峰值检测, 认知无线电

Abstract:

To solve the problem of the space-frequency block codes with orthogonal frequency division multiplexing (SFBC-OFDM) blind signal recognition, a space-frequency block codes signal recognition method based on correlation function is proposed. Firstly, the correlation characteristic of transmit signal is obtained based on correlation among the different SFBC-OFDM elements. Then, the correlation characteristic of the receive signal is obtained based on the correlation among the transmit signals. Finally, the automatic signal recognition algorithm based on the peak test is proposed. The simulation result shows that the recognition probability of the proposed algorithm is 95% at a low signal to noise ratio (0 dB), and does not need channel coefficient, noise information and modulation types, and the correct identification probability is over 90% under the different modulation scheme, time offset and frequency offset. It can be applied in the engineer field such as cognitive radio systems, spectrum surveillance, and so on.

Key words: blind signal recognition, space-frequency block code (SFBC), correlation function, peak test, cognitive radio

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