UAV Based Efficient Cooperative Spectrum Sensing in CRN: Time-Slot Optimization

Abstract

Cooperative spectrum sensing in cognitive radio networks provides a strong way to increase the throughput, spectral efficiency, and energy efficiency. However, the increased number of secondary users increases the energy consumption, thereby reducing the energy efficiency. To overcome this, a novel technique called unmanned aerial vehicles based on cooperative spectrum sensing has been proposed to reduce energy consumption and enhance the throughput and energy efficiency in a cognitive radio network. In this paper, a UAV-based cognitive radio network is considered to improve the throughput.  The performance of unmanned aerial vehicles is closely verified with parameters such as sensing time, path radius, and UAV velocity.  Optimization of the number of time slots is considered to further enhance the throughput. Simulation results indicate that the maximum optimal N is 18 when the detection probability is 0.9, with a sensing time of 2 ms. However, as the sensing time increases to 10 ms, the optimal N decreases to 3. Thus, maximum throughput is achieved by either selecting a higher optimal N with a high detection probability and lower sensing time or a lower optimal N with a lower detection probability and higher sensing time. This optimization strategy improves the throughput of virtual cooperative spectrum sensing compared to conventional approaches.