Energy Detection-Based Spectrum Sensing over Shadowed UAV-to-Ground Channels

Recent research has focused on exploring uncrewed aerial vehicle (UAV)-to-ground communication channels, leading to the development of new fading channel models that incorporate both fading and shadowing phenomena. It is well established that the performance of sensing techniques is significantly impacted by fading effects. Therefore, this paper examines the performance of energy detection-based spectrum sensing in shadowed UAV-to-ground channels by deriving novel analytical expressions for the average detection probability. Subsequently, These expressions are then extended to include collaborative spectrum sensing. The analysis delves into the complementary receiver operating characteristics (ROC), taking into account factors such as average signal-to-noise ratio (SNR), multipath fading, shadowing, and the number of collaborating sensing nodes. The analytical results are validated by comparing them with those obtained through Monte Carlo simulations.