Cooperative Spectrum Sensing Deployment for Cognitive Radio Networks for Internet of Things 5G Wireless Communication

Recently, Cooperative Spectrum Sensing (CSS) for Cognitive Radio Networks (CRN) plays a significant role in efficient 5G wireless communication. Spectrum sensing is a significant technology in CRN to identify underutilized spectrums. The CSS technique is highly applicable due to its fast and efficient performance. 5G wireless communication is widely employed for the continuous development of efficient and accurate Internet of Things (IoT) networks. 5G wireless communication will potentially lead the way for next generation IoT communication. CSS has established significant consideration as a feasible resource to improve identification performance by developing spatial diversity in receiving signal strength in IoT. In this paper, an optimal CSS for CRN is performed using Offset Quadrature Amplitude Modulation Universal Filtered Multi-Carrier Non-Orthogonal Multiple Access (OQAM/UFMC/NOMA) methodologies. Availability of spectrum and bandwidth utilization is a key challenge in CRN for IoT 5G wireless communication. The optimal solution for CRN in IoT-based 5G communication should be able to provide optimal bandwidth and CSS, low latency, Signal Noise Ratio (SNR) improvement, maximum capacity, offset synchronization, and Peak Average Power Ratio (PAPR) reduction. The Energy Efficient All-Pass Filter (EEAPF) algorithm is used to eliminate PAPR. The deployment approach improves Quality of Service (QoS) in terms of system reliability, throughput, and energy efficiency. Our in-depth experimental results show that the proposed methodology provides an optimal solution when directly compares against current existing methodologies.