Research On Interference Temperature In Cognitive Radio Networks

Radio technology is used more and more widely today. It is applied to every fieldof our life and production. With the development of the wireless communicationtechnology, more and more radio spectra are needed. It causes the shortage of spectrumresource. At present, the spectrum allocations of many countries are fixed, which leadsto the low availability of frequency spectrum and the contradictions between supply anddemand. Cognitive radio technology is a good way to solve those problems. Cognitiveradio is an intelligent system based on software radio. It is able to sense the radioenvironment and find spectrum holes. It makes use of these frequencies withoutinterfering authorized users. So, it is able to improve the availability of frequencyspectrum.Spectrum sensing provides the surrounding environment of the wireless spectruminformation for cognitive radio, which is the basis and premise of the application ofcognitive radio. This paper mainly studies the spectrum sensing technology of cognitiveradio technology and focus on the spectrum sensing technology based on interferencetemperature.First of all, this paper refers to a large number of materials and discusses thesignificance of the cognitive radio. At the same time, it introduces the current studies ofcognitive radio at home and abroad, and analyzes a variety of spectrum sensingtechnologies at present.Moreover, this paper introduces the concept of cognitive radio, and therelationships between cognitive radio and software radio. Then it introduces the keytechnology of cognitive radio and analyzes the spectrum sensing technology based oninterference temperature. And the models of the interference temperature are studied init. All of them give an important theoretic foundation for interference temperaturealgorithm.Thirdly，this paper researches and analyzes a few of nonparametric spectrumestimations, and then gives the simulation analysis of periodogram method, Welchmethod and MTM method.Last but not least, in the actual environment, estimating interference temperaturerequires the cooperative work of many sensors, so this paper researches the MTM-SVDalgorithm. Calculation of the singular value decomposition is complex. What’s worse, it influences the real-time of interference temperature estimation. Therefore, this paperadopts the improved MTM-SVD algorithm. This algorithm reduces the amount ofcalculation, and is propitious to the application of interference temperature estimation.