Research Of Cooperative Spectrum Sensing Technology Based On Fuzzy Integral

People demand more and more wireless resources with the development of wirelesscommunication technologies. But as a result of the policy of fixed spectrum allocation, the availablespectrum will become less and less. Cognitive radio technology, by reusing authorized spectrum,alleviate the situation of fewer and fewer spectrum resources. Therefore, cognitive radio technologyis a revolutionary technology. And spectrum sensing technology is the key technology of cognitive,and is the important foundation of the practical application of cognitive radio.The thesis analyzes the concept of cognitive radio technology, the current situation of thedomestic and foreign research, as well as the common technologies of spectrum sensing. And thesecontents have laid a theoretical basis for the development of the project. In the process of spectrumsensing, because of the wireless channel fading, shadow effect and noise uncertainty, theperformance of spectrum sensing of signal node is not very well. However the technologies ofmulti-user collaboration spectrum sensing can effectively solve these problems, so the technologiesbecome the hotspot and focus in current research of spectrum sensing.The thesis mainly discusses a problem of collaborative spectrum sensing. First of all, the thesisstudies the common technologies of spectrum sensing and introduces the common technologies ofdata fusion in collaborative spectrum sensing. And then the thesis puts forward a kind of a newcooperative spectrum sensing that is introducing fuzzy integral into spectrum sensing. Thesimulation analysis of this method shows that in low signal-to-noise, no matter the environment ofevery cognitive user is the same or not, the performance of spectrum sensing of this method issuperior to traditional collaborative spectrum sensing schemes. Finally in order to get higherperformance of collaborative spectrum sensing, the thesis puts forward a new cooperative spectrumsensing algorithm which is using the D-S evidence theory to fuse in the time domain and usingfuzzy integral to fuse in the airspace. The algorithm can be effectively applied to a cooperativespectrum sensing in which the real time requirement of the network is not tall and there are a largenumber of cognitive users. And the simulation results shows that the algorithm has goodsignal-to-noise robustness, compared with the collaborative spectrum sensing in which the fusionmethod is only used in the airspace.