IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Regular Section
Feature Based Modulation Classification for Overlapped Signals
Yizhou JIANGSai HUANGYixin ZHANGZhiyong FENGDi ZHANGCelimuge WU
著者情報
ジャーナル 認証あり

2018 年 E101.A 巻 7 号 p. 1123-1126

詳細
抄録

This letter proposes a novel modulation classification method for overlapped sources named LRGP involving multinomial logistic regression (MLR) and multi-gene genetic programming (MGGP). MGGP based feature engineering is conducted to transform the cumulants of the received signals into highly discriminative features and a MLR based classifier is trained to identify the combination of the modulation formats of the overlapped sources instead of signal separation. Extensive simulations demonstrate that LRGP yields superior performance compared with existing methods.

著者関連情報
© 2018 The Institute of Electronics, Information and Communication Engineers
前の記事 次の記事
feedback
Top