Feature based Modulation Classification using Multiple Cumulants and Antenna Array

摘要

Automatic modulation classification (AMC) conducted by a single receiver plays a crucial role in spectrum monitoring and signal interception. To improve the accuracy of feature based AMC, a novel multi-cumulant based modulation classification scheme using uniform linear array is proposed in this paper. Moreover, two methods are formulated to combine the signal from different antenna branches, i.e., DOAC (Direction of arrival estimation based Combination) and CC (Cooperative Combination). With an estimate of the incident angle of the signal, DOAC combines signals from different branches using maximum ratio combining. CC calculates the feature value of each branch independently and utilizes the average feature value of all branches for classification. Simulation results prove that using multiple cumulants yields performance gain over traditional methods using a single cumulant. Moreover, the influence of antenna number and sample length on performance is also explored.