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.
|ジャーナル||IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences|
|出版ステータス||Published - 2018 7月|
ASJC Scopus subject areas
- コンピュータ グラフィックスおよびコンピュータ支援設計