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A Survey of modulation recognition algorithms in non-cooperative communication
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Science & Technology Review | 2019, 37(4) : 55 - 62
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Science & Technology Review | 2019, 37(4): 55-62
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A Survey of modulation recognition algorithms in non-cooperative communication
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HUANG Zhitao1, YANG Jie1, WANG Xiang1, CUI Xuan2, WANG Yongfang2
Affiliations
    1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China;
    2. East Sea Fleet, People's Liberation Army Navy of China, Ningbo 315000, China
Published: 2019-02-28 doi: 10.3981/j.issn.1000-7857.2019.04.010
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Based on a comprehensive study of the modulation recognition algorithm in the non-cooperative communication, this paper reviews the current research status of the communication signal classical modulation recognition algorithm and the intelligent modulation recognition algorithm based on the deep learning. The concept and the connotation of the modulation recognition technology in the noncooperative communication are explained, focusing on the basic principle and the processing flow of the classical modulation recognition algorithm and the intelligent modulation recognition algorithm, the advantages and disadvantages of each kind of algorithms are analyzed, and the future development direction of the modulation recognition algorithm in the non-cooperative communication are discussed.
non-cooperative communication  /  modulation recognition  /  feature extraction  /  maximum likelihood  /  deep learning
黄知涛, 杨杰, 王翔, 崔轩, 王永芳. 非合作通信中调制识别算法研究进展. 科技导报, 2019 , 37 (4) : 55 -62 . DOI: 10.3981/j.issn.1000-7857.2019.04.010
HUANG Zhitao, YANG Jie, WANG Xiang, CUI Xuan, WANG Yongfang. A Survey of modulation recognition algorithms in non-cooperative communication[J]. Science & Technology Review, 2019 , 37 (4) : 55 -62 . DOI: 10.3981/j.issn.1000-7857.2019.04.010
Year 2019 volume 37 Issue 4
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doi: 10.3981/j.issn.1000-7857.2019.04.010
  • Receive Date:2018-10-29
  • Online Date:2019-03-08
  • Published:2019-02-28
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  • Received:2018-10-29
  • Revised:2018-12-11
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表12种不同金属材料的力学参数
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Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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