国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

基于深度卷積神經(jīng)網(wǎng)絡(luò )的數字調制方式識別
DOI:
CSTR:
作者:
作者單位:

中國空間技術(shù)研究院載人航天總體部,,

作者簡(jiǎn)介:

通訊作者:

中圖分類(lèi)號:

基金項目:


Digital modulation recognition based on deep convolutional neural network
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪(fǎng)問(wèn)統計
  • |
  • 參考文獻
  • |
  • 相似文獻
  • |
  • 引證文獻
  • |
  • 資源附件
  • |
  • 文章評論
    摘要:

    針對非協(xié)作通信條件下信號調制方式識別問(wèn)題,提出了一種基于深度神經(jīng)網(wǎng)絡(luò )的調制方式自動(dòng)識別新方法。該方法對接收到的信號進(jìn)行預處理,生成星座圖,并將星座圖形狀作為深度卷積神經(jīng)網(wǎng)絡(luò )的輸入,根據訓練好的網(wǎng)絡(luò )模型對調制信號進(jìn)行分類(lèi)識別。與以往的識別方法相比,該方法利用卷積神經(jīng)網(wǎng)絡(luò )自動(dòng)學(xué)習各種數字調制信號的星座圖特征,克服了特征提取困難,通用性不強,抗噪聲性能差等缺點(diǎn),處理流程簡(jiǎn)單,并對星座圖的形變具有不敏感性。針對4QAM、16QAM和64QAM三種典型的數字調制方式,進(jìn)行了仿真實(shí)驗,當信噪比大于4時(shí),調制方式的識別正確率大于95%,實(shí)驗結果表明,基于深度卷積神經(jīng)網(wǎng)絡(luò )的信號調制方式識別方法是有效的。

    Abstract:

    A novel method of automatic modulation recognition in non-cooperation communication systems, which is based on deep convolutional neural network, is proposed. Firstly, the received signal is preprocessed and generates the constellation diagram. Then, the shape of the constellation diagram is used as the input of the deep convolution neural network, which is trained to classify the modulated signal. The convolution neural network can automatically learn the constellation diagram features of various digital modulation signals, which can simplify the processing procedures and overcome the weaknesses of traditional techniques, such as the difficulty in extracting the features, the absence of universal property, and the poor anti-noise performance. In addition, the deformation of the constellation diagram is insensitive to the final classification performance by using convolution neural network. Three typical digital modulation schemes including 4QAM, 16QAM and 64QAM are used in the simulation test, and the results show that when the SNR is greater than 4, the accuracy of modulation recognition is more than 95%, which confirmed that the proposed method is effective.

    參考文獻
    相似文獻
    引證文獻
引用本文

彭超然,刁偉鶴,杜振宇.基于深度卷積神經(jīng)網(wǎng)絡(luò )的數字調制方式識別計算機測量與控制[J].,2018,26(8):222-226.

復制
分享
文章指標
  • 點(diǎn)擊次數:
  • 下載次數:
  • HTML閱讀次數:
  • 引用次數:
歷史
  • 收稿日期:2018-07-18
  • 最后修改日期:2018-07-18
  • 錄用日期:2018-07-25
  • 在線(xiàn)發(fā)布日期: 2018-09-04
  • 出版日期:
文章二維碼
大同市| 从江县| 阜新市| 周至县| 将乐县| 章丘市| 郑州市| 右玉县| 安泽县| 长葛市| 新乐市| 海盐县| 莱芜市| 通州市| 嫩江县| 侯马市| 甘德县| 廉江市| 石柱| 额尔古纳市| 吴江市| 福泉市| 四平市| 平罗县| 繁峙县| 秦皇岛市| 鸡泽县| 武山县| 建瓯市| 库尔勒市| 大田县| 扎赉特旗| 玉龙| 武强县| 齐河县| 牟定县| 西乌珠穆沁旗| 唐河县| 青阳县| 吴桥县| 榆林市|