Research On Spectrum Sensing Technology Base On Cognitive Radio

Cognitive radio developed from software radio technology is an intelligent wireless communication technology. Spectrum holes are quickly captured and used from the main user, which greatly improve the spectral efficiency. The core idea of cognitive radio is to find and use spectrum holes. Cognitive radio can resolve the contradictions of intrinsic spectrum allocation strategy and low spectral efficiency. Cognitive radio technology opens up a new path to comumunicate under the conditions of the limited spectrum resources.Spectrum sensing is an important prerequisite and prerequisite of cognitive radio technology. Perceived performance is measured by two parameters, detection probability and false alarm probability. Probability of detection is on behalf of the effectiveness of cognitive radio systems, and the false alarm probability is on behalf of the reliability of cognitive radio.Most previous work focused on improving the perceived performance of a single user, such as analysis and comparison of the local detection algorithm. The local algorithms of spectrum sensing technology are energy detection algorithm, matched filter detection algorithm, cyclostationary feature detection algorithm, detection algorithm based on interference temperature and wavelet transform. Because of simple operation and easily realization of energy detection algorithm, it is often as the local detection algorithm in a research of co-operation spectrum sensing technology. Cooperative spectrum sensing technology can overcome problem of the hidden terminal and improve the performance of spectrum sensing. Therefore cooperative spectrum sensing is currently research focus and emphasis. In this paper spectrum sensing technologies of cognitive radio are studied, the main work is as follows: First, the paper analyzes the local spectrum sensing technology based on the energy detection algorithm. The principle of energy detection algorithm and the selected model of energy detection algorithm are discussed. In addition performance evaluation parameters of spectrum sensing in cognitive radio were discussed, too. Meanwhile, the energy detection algorithm is simulated in the OR and AND fusion rule. The performance of spectrum sensing based on the evaluation parameters are analyzed. The advantages and disadvantages of energy detection algorithms are pointed out.Second, through simulation spectrum sensing system models based three users are analyzed and compared. The distributed system has a small probability of missed detection and large probability of false alarm. The centralized system is at the expense of the missed detection probability in exchange for reducing false alarm probability. In terms of the comprehensive performance, when the report error probability is small. The distributed system is superior to a centralized system. But for the specific systems, the distributed system increases the complexity of the design. Each sensing user has the ability of sharing and fusing the information, which increases costs. How to reduce report error probability needs to be paid more attention in the future.Next, in order to reduce the transmission report error probability, the traditional clustering technique and based on Time Division Multiplexing clustering strategy for spectrum sensing are analyzed and compared. Simulation results show the use of clustering technology can effectively reduce the reporting error probability and improve the overall performance of spectrum sensing in cognitive radio. On the another hand becasuse the actual channel environment is considered in the clustering technology based on Time Division Multiplexing, and its detection Performance is lower than traditional clustering technique.At the end of this paper, in order to further reduce the channel transmission error probability, the spatial diversity and selection diversity combined are taken into account. this paper proposes a robust cooperative spectrum sensing scheme based on multi-antenna and cluster. Simulation results show that the detection performance in this new scheme compared with the ideal cluster-based cooperative spectrum sensing scheme is poor. But the excellent performance is gaied relative to the actual cluster-based cooperative spectrum sensing scheme. Finally, the number of users in a cluster of the proposed strategy is disscussed. The two users in a cluster is not the optimal solution to the overall implementation of cognitive radio.