Spectrum Sensing and Management in Cognitive Radio Networks using Genetic Algorithm based Soft Decision Fusion
Rana Veer Samara Sihman Brahmatej Rupavath, Suganya. E, Saef Obidhusin, Payal Soni Gupta, R. Anitha · 2025
In recent years, the advancements of wireless technologies have led to a significant demand in radio frequency spectrum. Cognitive Radio Networks (CRN) are used among the intelligent wireless communication systems that enhanced spectrum efficiency. However, CRN with their help in enhancing the spectrum but possesses various challenges such as noise, dynamic environments that complicate the process of sensing. Therefore, in this research Genetic Algorithm based Soft Decision Fusion (GASDF) model is proposed for an effective Spectrum Sensing and Management in CRN. Primarily, the input data is collected through radio network signals, then the signals are preprocessed using the Z-score normalization to reduce the noise from the signals. Further, the relevant features are extracted using Continuous Wavelet Transform (CWT). Then, spectrum allocation is done using Differential Evolution (DE) and the spectrum sensing is done through GASDF. From the results, proposed model attained better outcomes compared to existing Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) with 2.45% Probability of false alarm (Pf) rate.