Modulation Recognition Algorithm Based on GWO-SA-LSTM Model
Addressing the issue of traditional automatic modulation recognition methods'low accuracy for modern sig-nals,this paper introduces the GWO-SA-LSTM model.This model enhances the capability of long short-term memory(LSTM)networks to capture key features through a self-attention mechanism and utilizes the grey wolf optimizer(GWO)to optimize hyperparameters.Experiments conducted on a real-world modulation recognition dataset demon-strate that the proposed model achieves a highest accuracy of 97%at a 10 dB signal-to-noise ratio,outperforming the standalone LSTM model in overall performance.
radio monitoringmodulation recognitionlong short-term memory(LSTM)grey wolf algorithm(GWO)self-attention mechanism
NETL
NSTL
万方数据
维普
