针对非合作通信条件下的调制方式识别问题，提出了一种正交频分复用( OFDM) 信号的多重分形谱特征盲识别算法．该算法首先提取通信信号多重分形谱最大值对应的奇异性指数以及通信解析信号平方处理后经两次傅里叶变换的幅频信号的多重分形谱跨度作为信号特征参数，然后通过多层决策树分类器完成对OFDM 信号和单载波信号的识别．该算法提取的特征参数对OFDM 信号子载波数目及循环前缀长度、单载波升余弦成形系数及信噪比的变化具有鲁棒性，且该算法在中频处理信号，无需时频同步．仿真结果表明，文中算法在很宽的信噪比范围内对OFDM 具有较高的平均识别率．

Proposed in this paper is a blind identification algorithm of orthogonal frequency division multiplexing ( OFDM) signals based on multifractal features,which is applied to the modulation identification in non-cooperative communication. In this algorithm,first,two items,namely the singularity exponent of the maximum multifractal value from communication signals and the span of multifractal from the amplitude of twice Fourier transform of
squared analytic communication signals,are extracted as signal feature parameters. Then,a multi-layer decision tree separator is constructed to identify OFDM signals and single-carrier signals. The feature parameters extracted by this algorithm are robust to the number of subcarriers,the length of the cyclic prefix of OFDM signals,the raised-cosine shaping roll-off factor of single-carrier signals and the signal-to-noise ratio ( SNR) ,and the signals are processed in intermediate frequency channel. Thus,the synchronization in time and frequency domains is not required. Simulated results show that the proposed algorithm can identify OFDM signals with a high average identification rate in a wide SNR range.