Sliding Window-Based Spectrum Sensing with Deep Learning for Pulse Radar Signals

A sliding window-based spectrum sensing method determines the presence or absence of a primary user by comparing the maximum of the received signal energies from multiple sliding windows with a threshold. In this letter, aiming to enhance this scheme, we present a deep learning-based approach for exploiting the pattern of the received signal energies from sliding windows and investigate its sensing performance.