Recursive Feature Elimination Based Feature Selection in Modulation Classification for MIMO Systems

被引：0

作者：

ZHOU Shuai ^{[1
]}

LI Tao ^{[1
]}

LI Yongzhao ^{[1
]}

机构：

[1] School of Telecommunications Engineering, Xidian University

来源：

Chinese Journal of Electronics | 2023年 / 32卷 / 04期

基金：

中国国家自然科学基金; 国家重点研发计划; 中央高校基本科研业务费专项资金资助; 美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TN911.3 [调制理论];

学科分类号：

081002 ;

摘要：

The feature-based(FB) algorithms are widely used in modulation classification due to their low complexity. As a prerequisite step of FB, feature selection can reduce the computational complexity without significant performance loss. In this paper, according to the linear separability of cumulant features, the hyperplane of the support vector machine is used to classify modulation types, and the contribution of different features is ranked through the weight vector. Then, cumulant features are selected using recursive feature elimination(RFE) to identify the modulation type employed at the transmitter. We compare the performance of the proposed algorithm with existing feature selection algorithms and analyze the complexity of all the mentioned algorithms. Simulation results verify that the proposed RFE algorithm can optimize the selection of the features to realize modulation recognition and improve identification efficiency.

引用

页码：785 / 792

页数：8

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