Improved Automatic Modulation Recognition Algorithm for OFDM Based on SVM

SHI Wen-juan; FENG Quan-yuan

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Improved Automatic Modulation Recognition Algorithm for OFDM Based on SVM

更新时间：2026-09-04

- Improved Automatic Modulation Recognition Algorithm for OFDM Based on SVM
- Vol. 31, Issue 10, Pages: 98-102(2014)
- 作者机构：
  
  西南交通大学微电子所,四川,成都,610031
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
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史文娟, 冯全源. 一种改进的基于支持向量机的OFDM识别算法[J]. 微电子学与计算机, 2014, 31(10): 98-102.

SHI Wen-juan, FENG Quan-yuan. Improved Automatic Modulation Recognition Algorithm for OFDM Based on SVM[J]. 2014, 31(10): 98-102.
史文娟, 冯全源. 一种改进的基于支持向量机的OFDM识别算法[J]. 微电子学与计算机, 2014, 31(10): 98-102. DOI：

SHI Wen-juan, FENG Quan-yuan. Improved Automatic Modulation Recognition Algorithm for OFDM Based on SVM[J]. 2014, 31(10): 98-102. DOI：

摘要

针对OFDM信号与单载波信号调制识别

提出了一种基于高阶累积量特征的改进方法.通过分析复信号幅值的归一化四阶累积量特性

以及信号的瞬时频率和功率谱特征

改进和提出新的特征参数

采用支持向量机分类器

实现了AWGN信道下包括OFDM在内的9种信号的制式自动识别.该方法具有特征参数易于提取、抗噪性好、识别准确率高的优点.利用MATLAB仿真证明在信噪比不小于7dB的情况下

OFDM信号的识别准确率达99%.

Abstract

Aiming at the automatic modulation recognition of OFDM signal and Single carrier signals

this paper proposes a improved method based on high-order cumulants.By analysing the normalized fourth-order cumulant features of the complex signal amplitude

the characteristics of instantaneous frequency and power spectrum

new feature parameters are proposed.With support vector machine (SVM) classifier

the automatic identification of 9kinds of signals including OFDM in the AWGN channel is achieved.The method has lots of advantages

such as the feature parameters could be extracted easily and have good anti-noise performance

and recognition accuracy rates are also very high.When SNR is not less than 7dB

the simulation results on MATLAB indicate that identification probability of this proposed method is 99%.

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Related Author

HUA Xiang

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Related Institution

1 College of Technological Information Engineering, Xi′an Technological University, Xi′an

2 Xidian University, Xi′an

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