CS-Based Modulation Recognition of Sparse Multiband Signals Exploiting Cyclic Spectral Density and MLP

Modulation recognition of sparse multiband signals is a key technology for intelligent signal processing. However, the existing method suffers from high sampling rate and poor anti-noise performance. Therefore, compressed sensing and cyclic spectral density are combined to cope with the shortcomings of existing methods followed by the multi-layer perceptron (MLP) to recognize modulation mode of signal. Some simulations are carried out, and the simulation results show that the proposed algorithm is correct and effective.