Automatic modulation recognition .1.

被引:21
|
作者
Azzouz, EE [1 ]
Nandi, AK [1 ]
机构
[1] UNIV STRATHCLYDE, DEPT ELECT & ELECT ENGN, GLASGOW G1 1XW, LANARK, SCOTLAND
关键词
D O I
10.1016/S0016-0032(96)00069-5
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a review of the mole recent papers published in the area of modulation recognition is introduced. Three alternative algorithms, representing modifications of earlier works and based on the decision-theoretic approach, are presented. These appear to offer the best performance over a large number of modulation types. For example, the average analogue modulations recognition success rate is approximate to 99% at 10 dB SNR, the average digital modulations recognition success rate is approximate to 99% at the SNR of 10 dB, and the average analogue and digital modulations recognition success rate is approximate to 93% at 15 dB SNR. Copyright (C) 1997 Published by Elsevier Science Ltd.
引用
收藏
页码:241 / 273
页数:33
相关论文
共 50 条
  • [21] Automatic Modulation Recognition Based on Morphological Operations
    Yuan Zhang
    Xiurong Ma
    Duo Cao
    Circuits, Systems, and Signal Processing, 2013, 32 : 2517 - 2525
  • [22] Automatic Modulation Recognition for Secondary Modulated Signals
    Chu, Peng
    Xie, Lijin
    Dai, Chuanjin
    Chen, Yarong
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2021, 10 (05) : 962 - 965
  • [23] Automatic Modulation Recognition Based on CNN and GRU
    Fugang Liu
    Ziwei Zhang
    Ruolin Zhou
    Tsinghua Science and Technology, 2022, 27 (02) : 422 - 431
  • [24] MOLECULAR RECOGNITION .1. AUTOMATIC IDENTIFICATION OF TOPOGRAPHIC SURFACE-FEATURES
    LEE, RH
    ROSE, GD
    BIOPOLYMERS, 1985, 24 (08) : 1613 - 1627
  • [25] CNN-based automatic modulation recognition for index modulation systems
    Leblebici, Merih
    Calhan, Ali
    Cicioglu, Murtaza
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 240
  • [26] On properties of modulation spectrum for robust automatic speech recognition
    Kanedera, N
    Hermansky, H
    Arai, T
    PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, 1998, : 613 - 616
  • [27] Deep Learning Aided Method for Automatic Modulation Recognition
    Yang, Cheng
    He, Zhimin
    Peng, Yang
    Wang, Yu
    Yang, Jie
    IEEE ACCESS, 2019, 7 : 109063 - 109068
  • [28] A Novel Attention Cooperative Framework for Automatic Modulation Recognition
    Chen, Shiyao
    Zhang, Yan
    He, Zunwen
    Nie, Jinbo
    Zhang, Wancheng
    IEEE ACCESS, 2020, 8 : 15673 - 15686
  • [29] Automatic Modulation Recognition Using Neural Architecture Search
    Wei, Shengyun
    Zou, Shun
    Liao, Feifan
    Lang, Weimin
    Wu, Wenhui
    2019 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE BIG DATA AND INTELLIGENT SYSTEMS (HPBD&IS), 2019, : 151 - 156
  • [30] Sparsely Connected CNN for Efficient Automatic Modulation Recognition
    Tunze, Godwin Brown
    Huynh-The, Thien
    Lee, Jae-Min
    Kim, Dong-Seong
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (12) : 15557 - 15568