Continuous phase signal modulation recognition based on combined spectral features using ResNeXt50 with channel and spatial attention mechanism

In the realm of ultra short wave satellite communication channels, various forms of continuous phase signal transmission exist. However, distinguishing between these signals poses a challenge due to their similar frequency domain characteristics. This paper introduces a novel modulation recognition algorithm for continuous phase signals (including MSK, single modulation index CPM, multiple modulation index CPM, SOQPSK, SBPSK) that is based on combined spectral features using ResNeXt-50 with channel and spatial attention mechanism (CS-ResNeXt50). The algorithm first proposes a combined diagrams based on quadratic and quartic spectrum analysis, which exploits the unique characteristics of the impulse spectral lines to differentiate signals with varying continuous phases. Compared to FFT and time-frequency spectrums, the combined diagrams demonstrates superior discrimination capabilities. Simultaneously, the CS-ResNeXt50 network is introduced, incorporating a Channel and Spatial (CS) attention mechanism to enhance feature learning from the combined diagrams. The integration of cross entropy and triplet loss functions further refines feature extraction within the network. Experimental results show that the proposed combined diagrams improves recognition performance by 15.4%, 10.8%, 2.8%, and 4.7% compared to FFT, time-frequency, quadratic, and quartic spectrums, respectively. Moreover, under the combined diagrams framework, the proposed network exhibits a 3.1%, 4.0%, 4.4%, and 5.1% enhancement in recognition performance compared to the ResNeXt-50, ResNet-50, ResNet-34, and ResNet-18 networks, respectively.