Spectrum Sensing Technology Research Based On Quantum Swarm Intelligence Optimization Algorithm

Radio spectrum may be one of the most tightly regulated resources of all time, which has the characteristic of scarceness and can not be reproduced. The scarceness of wireless spectrum hampers the rapid development of wireless communication service. How to use wireless spectrum is the hot issue of wireless communication field. Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio spectrum, it is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment.Spectrum sensing, as a key technology in cognitive radio, needs to reliably detect signals from licensed primary radios to avoid harmful interference. In our paper, we adopt an optimal linear cooperation framework for spectrum sensing model.In order to improve the performance of swarm intelligence algorithm, two novel algorithms based on the theory of quantum computing are proposed. The simulation results show that the newly proposed algorithms have a better searching speed and an obvious accuracy. In addition, we applied our newly designed algorithm in spectrum sensing.Based on shuffled frog leaping algorithm and quatum theory, quantum frog leaping algorithm is proposed. Then, we applied our novel algorithm in the spectrum sensing issue and proposed the optimal linear cooperation model for spectrum sensing based on quantum frog leaping algorithm. Based on bacterial foraging algorithm and quatum theory, quantum bacterial foraging algorithm is proposed. Then, we applied our novel algorithm in the spectrum sensing issue and proposed the optimal linear cooperation model for spectrum sensing based on quantum bacterial foraging algorithm.