CAJ | 학술논문

为了对OFDM信号进行识别，针对高阶矩算法的运算量大的不足，提出一种基于经验分布函数统计量法用于识别OFDM信号和单载波信号。提出单载波/OFDM信号识别模型，建立了最优经验分布函数评价准则，推导了最优经验分布函数；详细阐述了基于KS检验法的OFDM信号识别流程；理论分析及仿真结果表明，该统计量提高了对高斯分布的拟合能力，进而提高了对OFDM信号的识别能力，同时相比高阶矩法，运算量少。
위료대OFDM신호진행식별，침대고계구산법적운산량대적불족，제출일충기우경험분포함수통계량법용우식별OFDM신호화단재파신호。제출단재파/OFDM신호식별모형，건립료최우경험분포함수평개준칙，추도료최우경험분포함수；상세천술료기우KS검험법적OFDM신호식별류정；이론분석급방진결과표명，해통계량제고료대고사분포적의합능력，진이제고료대OFDM신호적식별능력，동시상비고계구법，운산량소。
In order to achieve OFDM modulation identification,a modified empirical-distribution-function ( EDF) based test statistics is proposed, instead of based on test statistic high-order Cumulants with high computational complexity. And also a single carrier / OFDM signal recognition model is presented, the op-timal empirical distribution evaluation criteria function established, the optimal empirical distribution func-tion derived and KS test method based on OFDM signal identification process described in detail. Simula-tion and analysis indicate that the modified empirical-distribution-function ( EDF) could improve the fit capability for Gaussian distribution,and thus raise the performance of OFDM modulation identification. The computational complexity of EDF based on test statistics is remarkably lower than that based on high-order Cumulants.