Cooperative Spectrum Sensing Algorithm Based On Maximum-minimum Eigenvalue

This paper introduces the technology of spectrum sensing in the cognitive radio, analyzes the cooperative spectrum sensing algorithm based on maximum-minimum eigenvalue. The emergence of the cognitive radio is to solve the problem caused by spectrum crowding, mainly through analyzing the spectrum which hasn't been widely used by the primary users. The core and prerequisite part is to detect of the presence of primary user accurately. As a solution to this problem, spectrum sensing technology is the most important part of the cognitive radio.At the present time, technology of spectrum sensing contains two aspects:First is the local spectrum sensing technology; second is multi-node cooperative spectrum sensing technology. This paper focuses on both of the two aspects, especially discusses the multi-node cooperative spectrum sensing technology.The second chapter discusses the existing technology of spectrum sensing. Firstly, summarize the algorithm of local spectrum sensing technology for energy detection, matched filter detection and cyclostationary feature detection of the Transmitter perception, and LO power leakage detection and detection algorithm based on interference temperature for receiver perception, discusses both the advantages and disadvantages of these algorithms, analyzes some of the classical algorithm, such as'or','and' and K out of N of the cooperative sensing, solutions for common problems in spectrum sensing.In the third chapter, the article mainly discusses a new algorithm of the local spectrum sensing technology, which is called'the maximum and minimum eigenvalue', introduces the process of the sensing model, steps of the algorithm, and the threshold of the derivation.Based on this algorithm, the article gives a new algorithm called data centralized cooperative spectrum sensing algorithm based on maximum-minimum eigenvalue, it changes the sampling methods of the local algorithm and collects different types of sampling matrix, provides the progress of the algorithm. Meanwhile, the simulation part proves the effectiveness of the threshold and the advantages compared to the algorithm of the energy detection, also shows that this sampling method can meet relevant requirements. The fourth chapter focuses on the problem that the central maximum and minimum eigenvalue takes up too much control bandwidth, prposed the 1 bit combined cooperative spectrum sensing algorithm based on maximum-minimum eigenvalue. Firstly, it analyzes the two factors which affects the data weighting coefficient:signal and noise, confirms its relation to the capability of the testing. In order to meet the actual demands, the analyzing result uses the distance instead of the signal of the primary user, finally determines the two factors, signal and noise, of the weighting coefficient. In conclusion, this article gives the cooperative spectrum sensing algorithm based on maximum-minimum eigenvalue based on the accurately detection of the primary users. The ratio of maximum-minimum eigenvalue of the vice base station will be weighted by the algorithm, which determine the existence of the signal. Then the algorithm was simulated to verify the detection performance, and compared with the energy detection method.Furthermore, the article analyzes the weighting coefficient of the primary users of uncertain locations by cumulating the results of the detection performance of the vice base station to replace the unknown distance, to achieve the weighting coefficient algorithm for primary users of uncertain locations, at the same time, it changes the process of the algorithm, then the algorithm was simulated to verify the detection performance, and compared with the energy detection method.In conclusion, the fifth chapter is a summary of the article, analyzes some existing problems in this algorithm, proposed new items for further research.