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基于特征序列的时域STBC-OFDM盲识别算法

于柯远 张立民 闫文君 金堃

于柯远, 张立民, 闫文君, 等 . 基于特征序列的时域STBC-OFDM盲识别算法[J]. 北京航空航天大学学报, 2021, 47(8): 1524-1532. doi: 10.13700/j.bh.1001-5965.2020.0262
引用本文: 于柯远, 张立民, 闫文君, 等 . 基于特征序列的时域STBC-OFDM盲识别算法[J]. 北京航空航天大学学报, 2021, 47(8): 1524-1532. doi: 10.13700/j.bh.1001-5965.2020.0262
YU Keyuan, ZHANG Limin, YAN Wenjun, et al. Blind identification algorithm of time-domain STBC-OFDM based on feature sequence[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(8): 1524-1532. doi: 10.13700/j.bh.1001-5965.2020.0262(in Chinese)
Citation: YU Keyuan, ZHANG Limin, YAN Wenjun, et al. Blind identification algorithm of time-domain STBC-OFDM based on feature sequence[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(8): 1524-1532. doi: 10.13700/j.bh.1001-5965.2020.0262(in Chinese)

基于特征序列的时域STBC-OFDM盲识别算法

doi: 10.13700/j.bh.1001-5965.2020.0262
基金项目: 

国家自然基金重大研究计划 91538201

“泰山学者”建设工程专项 201511020

详细信息
    通讯作者:

    张立民, E-mail: gfsskfqp@163.com

  • 中图分类号: TN911.7

Blind identification algorithm of time-domain STBC-OFDM based on feature sequence

Funds: 

National Natural Science Foundtion Monumental Projects of China 91538201

Taishan Scholar Special Foundation 201511020

More Information
  • 摘要:

    为有效解决STBC-OFDM信号盲识别过程中存在的低信噪比适应能力弱等问题,在OFDM块大小已知的前提下,提出了一种在时域上构造特征序列的识别算法。该算法推导了空时分组码接收信号的时域特性,以及四阶特征向量,并构造特征序列,通过检测特征序列达到识别4种STBC-OFDM信号的目的。推导和仿真结果表明:所提算法无需信道、噪声、调制方式和OFDM块起始位置等先验信息,在较低信噪比条件下也具有良好的识别性能,且对频偏、多普勒频移和时延的鲁棒性能好,计算量较低,具有较高的实用价值。

     

  • 图 1  STBC-OFDM通信系统结构

    Figure 1.  STBC-OFDM communication system structure

    图 2  STBC-OFDM信号的四阶特征向量序列

    Figure 2.  Fourth-order eigenvector sequence of STBC-OFDM signal

    图 3  识别算法决策树

    Figure 3.  Decision tree of identification algorithm

    图 4  四种STBC-OFDM信号的正确识别概率

    Figure 4.  Correct recognition probability of four STBC-OFDM signals

    图 5  算法性能与OFDM子载波数的关系

    Figure 5.  Relationship between algorithm performance and OFDM subcarrier number

    图 6  算法性能与OFDM块数量的关系

    Figure 6.  Relationship between algorithm performance and number of OFDM blocks

    图 7  算法性能与循环前缀数的关系

    Figure 7.  Relationship between algorithm performance and cyclic prefixes

    图 8  算法性能与时延的关系

    Figure 8.  Relationship between algorithm performance and time delay

    图 9  算法性能与频偏的关系

    Figure 9.  Relationship between algorithm performance and frequency offset

    图 10  算法性能与多普勒频移的关系

    Figure 10.  Relationship between algorithm performance and Doppler frequency

    图 11  算法性能与调制方式的关系

    Figure 11.  Relationship between algorithm performance and modulation mode

    图 12  不同算法识别性能比较

    Figure 12.  Comparison of identification performance among different algorithms

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出版历程
  • 收稿日期:  2020-06-15
  • 录用日期:  2020-09-19
  • 刊出日期:  2021-08-20

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