Researches On Cooperative Spectrum Sensing Technology In Cognitive Wireless Sensor Networks

Cognitive Wireless Sensor Networks can utilize the idle licensed spectrum resources legitimately to overcome the spectrum shortage which is one of the bottlenecks that restricting the development of Wireless Sensor Networks. Cognitive Wireless Sensor Networks are different from traditional Wireless Sensor Networks. In addition to the conventional communication in the ISM band, Cognitive Wireless Sensor Networks also use sensing technology to communicate in the spectrum hole. The performance of Wireless Sensor Networks gets improved. Cognitive Wireless Sensor Networks are based on the traditional Wireless Sensor Networks,so the energy of the nodes is limited. It is nessary to consider energy saving and node cooperation. The traditional technologies of Cognitive Radio Networks can not apply to Cognitive Wireless Sensor Networks directly. In this thesis, the sensing technologies of Cognitive Wireless Sensor Networks are researched.Detecting the licensed spectrum and confirming the presence or absence status of the primary users are the the primary tasks for cognitive ability. Spectrum sensing has been extensively researched. In this thesis, the optimization of cooperative spectrum sensing based on double threshold energy detection is studied. First of all, the voting threshold of the voting fusion rule is optimized under the circumstance of fixed detection thresholds, which makes the global error probability reach the minimum value. Then the detection thresholds of energy detection are optimized under the optimal voting fusion rule. The optimal detection thresholds are dynamic under different SNR conditions, so the performance of cooperative spectrum sensing gets improved. Simulation results show that the lowest global error probability is achieved when the voting threshold of the voting fusion rule and the detection thresholds of energy detection reach their optimum values respectively.The channels between the primary users and the sensing nodes are time-varying due to the channel fading. In this thesis, we propose a multiple mini-slots sensing mode and assume that the channel state is static during each mini-slot sensing time. The nodes sense each mini-slot’s data separately and then fuse the sensing result of each mini-slot. The cluster heads fuse the sensing result of each node in the cluster and then send the sensing results to the fusion center. The fusion center fuses the sensing result of each cluster head to achieve the final sensing result. So Cognitive Wireless Sensor Networks perform three-steps fusion during the spectrum sensing. Moreover, we optimize the clustering rule and the number of mini-slots in order to achieve the maximum ratio of throughput to energy consumption. According to the simulation results, the maximum ratio of throughput to energy consumption is achieved when the number of mini-slots reaches a specific value and the optimal clustering rule is adopted under the premise that the primary users are well protected.