| Cognitive radio is an effective solution to spectrum sharing program, and is an intelligent wireless communication technology. Based on an in-depth understanding of the fundamental knowledge of cognitive radio technology, this dissertation focuses on the spectrum sensing technology in cognitive radio, and completes the following innovative research results:For the channel fading and multipath fading effect on the performance of collaborative spectrum sensing in cognitive radio, the dissertation optimizes multi-cluster cooperative spectrum sensing based on both the location and channel, and combined with improved double-threshold energy detection to improve the performance of spectrum sensing. The improved double-threshold energy detection also transmits the detected energy values among in two thresholds to data fusion center, and the data fusion center gets the network threshold value by depended on the desired target false alarm probability. According to the network threshold value, the detected energy values are fused, and participate in the network’s decision. Simulation analyses show that the proposed algorithm’s perception accuracy is higher than traditional multi-cluster cooperative spectrum sensing based on location, and the proposed algorithm can significantly improve collaborative spectrum sensing ability of the cognitive radio network.The network using double-threshold energy detection needs to transfer large traffic and occupy channel wide. For this question, on the premise of ensuring detection performance, this dissertation optimizes the above spectrum sensing algorithm, in which properly reduces the number of cognitive users participating the sensing in one cluster. Simulation results show that when the SNR is10dB, the detection probability of the entire network can be increased from75%to99%.Finally, the full text is summarized in this dissertation, and the clustering collaborative spectrum sensing technology is prospected. |
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