Research On Optimization Of Threshold For Spectrum Sensing In Cognitive Radio Networks

As the rapid development of wireless communications services, the available spectrum resources become more and more scarce. A large number of authorized spectrums are in free at most time and imbalance frequency spectrum occupancy causes great waste of resources. In this case, in order to improve the spectrum utilization of authorized spectrums, cognitive radio came into being. Considering the influence of detected threshold on cooperative spectrum sensing, this dissertation mainly focuses on the optimization of threshold based on hard decision fusion and soft decision fusion for collaborative spectrum sensing. The main research contents are as follows:This dissertation researches the detection threshold optimization of collaborative spectrum sensing based on hard decision, which includes AND rule, OR rule and K rule. In order to improve the spectrum sensing detection performance of cognitive radio, to avoid interference with primary users, meanwhile, to increase the utilization of spectrum resources, this paper analyzes the spectrum sensing threshold optimization based on three kinds of hard decision fusion. The optimization of detection threshold is completed by minimizing the error detection probability and maximizing throughput. The relationship between threshold and the overall error probability as well as the throughput are simulated and analyzed and the three kinds of fusion rules are compared. The results show that the optimal threshold made the detection performance of the cooperative spectrum sensing higher.This dissertation researches the detection threshold optimization of cooperative spectrum sensing based on soft decision fusion. The optimization of detection threshold is achieved considering two aspects: to minimize the error detection probability and to maximize the throughput by using linear weighed cooperative spectrum sensing algorithm. The mathematical function models of error probability and throughput of threshold are established and the expressions of the optimal threshold are derived. The simulation results and analysis demonstrate that the improved algorithm based on soft decision fusion has better detection performance when a suitable threshold is selected, which can decrease the error probability to improve the detection accuracy. When the throughput reaches maximum, the optimal threshold received by soft decision fusion algorithm makes the detection probability higher and the performance of cognitive system better, which has practical significance to the study of cognitive radio spectrum sensing.