Abstract

Abstract

Multi-Channel Sequential Sensing In Cognitive Radio Networks

Finding white spaces and using them are major goals of cognitive radio networks. In this research work, we investigate multi-channel spectrum sensing for secondary users (SUs), and make improvements by forming sequential sensing as long as the secondary user does not get a channel to transmit on, and also as long as the user still has time left for transmission since waiting for the next cycle might not be the best scenario for the use of
spectrum radio. We first formulate an optimization problem that maximizes the throughput of the system. Then, we introduce a power consumption model for our system since SUs are battery powered devices and the effectiveness of the system is jointly coupled with the energy consumption. Finally, we introduce an energy utility function, and we optimize it by considering both the throughput of the system and the amount of power consumed to
achieve the optimal throughput. Numerical and simulation results are introduced at the end of this research, and they show better performance by the use of our suggested model compared to the work i the literature. The results also showed how to find the optimal number of channels to be sensed considering an efficient use of the SU’s battery.