Study Of Spectrum Sensing In Cognitive Radio

With the development of mobile communication technology, the limited wirelessspectrum resources grow to be scantier gradually. Cognitive radio technology is anefficient approach to solve the deficiency problem of spectrum resources. As theprimary key technology of cognitive radio, spectrum sensing technology has becomethe hot spot of current research. The thesis studies of the spectrum sensing technologyin cognitive radio.The thesis mainly studies single node spectrum sensing algorithms which are basedon cyclostationary features. Firstly, the thesis studies the second-order cyclostationaryfeature of communication signals. In allusion to cyclostationary feature detectionalgorithm is high in computing complexity and poor in real-time performance, the thesisproposes a spectrum sensing algorithm based on cyclic spectrum section by studying thecyclic spectrum density functions of commonly used modulation signals and theirspectral section properties. The simulation results show that the algorithm mentioned inthe thesis has better detection performance. Secondly, the thesis studies the higher-ordercyclic statistical properties of communication signals. As higher-order cyclic statisticscan suppress noise, the spectrum sensing model based on fourth-order cyclic cumulantsis built, and the existence of primary users can be detected by peak detection algorithm.The simulation results show that fourth-order cyclic cumulants have excellent immunityto noise, provide more reliable results of spectrum sensing.