Study Of Spectrum Sensing Algortihms For Cognitive Radio Algorithm Of Single-Node

With the development of wireless communication technologies, the increasing communication services made the available spectrum resources less and less, in this context, cognitive radio technology came into being. Cognitive radio technology is based on the spectral detection, and spectrum sensing is based on single-node detection (cooperative detection is detected in the single-node data fusion on the basis of or extract). The detection of a single node contain matched filter detection, energy detection and cyclostationary feature detection. Matched filter using the process too restrictive, which not suitable for practical application. Single-node cyclostationary feature detection method, while computational complexity is high, but not only can detect the presence or absence of signals, and can describe many features of the desired signal, such as the phase information, frequency information,etc; become an indispensable method of spectrum detection; single node energy detection method implements simplely, and lower computational complexity. In practice, knowing the address of the received signal noise power, then there are completely a set of statistical signal detection theory spectrum detection; energy detection method in the case of high signal to noise ratio is very effective, and when the signal to noise ratio is low, the performance becomes far from ideal.Based on energy detection and cyclostationary feature detection method of the advantages and disadvantages of the spectrum is proposed two stage of coarse-fine detection methods, using a coarse energy detection method, the level of fine is cyclostationary feature detection. The basic idea of the algorithm for the continuous received signal is first started testing coarse level, estimated by statistical theory of probability test, when testing the high threshold value is greater than the probability that the detected signal, the frequency spectrum is occupied; when the probability is less than the low threshold that the signal is not detected, the spectrum of this band is empty,cognitive radio systems can communicate with the band;when the test threshold probability ranged between the two, start the second stage testing (Fine-level detection)-cyclostationary feature detection method,the signal to be detected when there is a nonzero cycle frequency, is that the band has been occupied, and when the signal to be detected only when there is zero cycle frequency is that there is no master user signal,the band is idle.In this paper, based on theoretical analysis, the energy detection,cyclostationary detection and the proposed two stage of coarse-fine detection were carried out matlab simulation, the performance of the first two methods to do the depth comparison, proposed a environment noise power estimation. Simulation results show that the proposed algorithm in a complex environment more than cyclostationary detection on computational complexity, higher detection probability with the energy detection method.