A Study of Cooperative and Non-Cooperative Wideband Spectrum Sensing Radio Networks in the Cognitive Radio 5G Era

The advent of 5G technologies has ushered in unprecedented demands for efficient spectrum utilization to accommodate a surge in data traffic and diverse communication services. In this context, accurate and reliable spectrum sensing is crucial. We investigated wideband spectrum sensing strategies by comparing non-cooperative cognitive radio (CR) approaches with cooperative methods across multiple sub-bands. Our research led to the development of a sophisticated cooperative wideband spectrum sensing framework that incorporates a K-out-of-N fusion rule at the fusion center to make optimal decisions, selecting an appropriate K for a given number of cooperating CRs. This method aims to combat the noise uncertainty typically affecting traditional non-cooperative energy detection methods in 5G environments under Additive White Gaussian Noise (AWGN) conditions, assumed to be identically and independently distributed (i.i.d). However, our findings indicate that while cooperative sensing significantly improves detection in scenarios with poor signal-to-noise ratios (SNRs) and higher false alarm rates (between 0.5 and 1), it does not consistently outperform non-cooperative methods at very low false alarm rates (0.01 and 0.1). This finding suggests the limited effectiveness of the cooperative sensing method under certain conditions, underscoring the need for further research to optimize these strategies for diverse operational environments.