Optimal Node Selection for Cooperative Spectrum Sensing in Cognitive Radio Sensor Networks with Energy Harvesting

5G communication technology supports the Internet of Things, remote health care centers, and cloud computing by tuning their communication services over a very wide range of frequency bands with low-cost, low-battery consumption, and low latency. However, the development of such wireless technology is highly dependent on radio frequency spectra. The Cognitive Radio Sensor Network (CRSN) is an excellent candidate to improve radio spectrum utilization and manage the heavy communication data traffic in 5G wireless networks. CRSN can sense the frequency channels, making it possible for secondary users (who are denied service) to use the free channels. Despite the outstanding features of CRSNs, some limitations overshadow their performance. The most critical limitation is energy and its optimal consumption to increase the network's lifetime. Recent research has shown that energy harvesting can be an effective way to increase the lifetime of CRSNs. However, the sensors should sense the frequency spectrum with a high success rate. In this paper, several optimal sensor nodes using energy harvesting with the approach of increasing the network's lifetime are proposed to solve the mentioned challenge. This way, the sensor nodes are divided into two independent groups for simultaneous spectrum sensing and energy harvesting in each time frame. We will solve this problem based on mathematical optimization and the use of proposed solutions for convex problems. Finally, simulations are developed to evaluate the ability of the proposed solution, assuming the systems use IEEE802.15.4/Zigbee and IEEE802.11af.