CAJ | 학술논문

针对认知无线电系统中传统数字调制识别方法在非高斯Alpha稳定分布噪声下识别性能差、计算复杂度高的问题，提出了一种基于分数低阶循环谱相关系数的数字调制识别新方法。该方法提取分数低阶循环谱截面和频率谱截面以及其投影面的5个相关系数作为识别特征参数，并采用判决树分类器，实现了非高斯噪声下数字调制信号识别。仿真结果表明，在非高斯Alpha稳定分布噪声下，该识别方法不仅具有较高的识别率和良好的稳健性并且计算复杂度更低，更适合于认知无线电系统。
침대인지무선전계통중전통수자조제식별방법재비고사Alpha은정분포조성하식별성능차、계산복잡도고적문제，제출료일충기우분수저계순배보상관계수적수자조제식별신방법。해방법제취분수저계순배보절면화빈솔보절면이급기투영면적5개상관계수작위식별특정삼수，병채용판결수분류기，실현료비고사조성하수자조제신호식별。방진결과표명，재비고사Alpha은정분포조성하，해식별방법불부구유교고적식별솔화량호적은건성병차계산복잡도경저，경괄합우인지무선전계통。
In cognitive radio system, the traditional methods of digital modulation signals recognition with Alpha stable distribution noise have the problems of poor performance and high computation complexity. A novel recognition method based on correlation coefficient of fractional lower order cyclic spectrum was proposed to solve this problem. The me-thod extracts the recognition characteristic parameters which are five correlation coefficients of the fractional lower order cyclic spectrum’s section and frequency spectrum’s section and projection planes of both, and then decision tree was used as a classifier to achieve digital modulation signals recognition. Simulation results show that the proposed method not only has higher recognition rates and better robustness but also has lower computation complexity in an Alpha stable dis-tribution noise environment, which is more suitable for cognitive radio system.