Research On Cognitive Radio Spectrum Sensing Technology

With the development of wireless communication,all kinds of wireless services have sprung up in recent years,like visual telephone,mobile TV,which need higher data transmission rate.However,former data transmission rate satisfying the voice services is not enough for current services.Furthermore,the overuse of large numbers of wireless devices causes the scarcity of frequency spectrum.However,after investigating,we know the scarcity of frequency spectrum is not resulted from the overuse of it.On the contrary,the dilemma turns up because of the policy of static allocation.Therefore,Dr.Mitola proposed Cognitive Radio,a radio or system which can sense the electromagnetic environment and change its operating parameter automatically.In cognitive radio networks,spectrum sensing is the core technology which realizes the cognitive radio and builds the network;it also helps the primary users avoid harmful interference and increase the utilization rate of cognitive network.This paper selects the cognitive radio spectrum sensing as a research topic.First of all,four classic models of energy detection are simulated;and the N-SNR relationship of these models in both AWGN and Rayleigh channels is analyzed.Then,a linear spectrum sensing algorithm is proposed,and compared with traditional one.Finally,owing to the advantages,chaotic systems are applied in the spectrum sensing.The contributions of this paper can be summarized as follows:(1)The analysis of performances of energy detectors in different channelsThis chapter deduces and analyzes the performances of exact models,Edell models,Torrieri models and Berkeley models in both AWGN and Rayleigh channels.The results of the simulation show that in AWGN channel,Torrieri model is the best,while Edell is the worst;in Rayleigh channel,all of three models can replace the exact model well.(2)Linear algorithm of spectrum sensing based on energy detectionAccording to the disadvantages of traditional sensing methods CFAR and CDR,this chapter proposed a linear algorithm of spectrum sensing based on energy detection.This algorithm combines the false alarm probability with the detection probability as a target function;in the given constraint condition,the optimum threshold can be calculated.The results of simulation show that the performance of linear algorithm is better than traditional ones,especially in low signal-to-noise ratio conditions.(3)The application of chaotic systems in spectrum sensingThis chapter applies the chaotic systems in the spectrum sensing of cognitive radio.We choose Duffing equation and weak sinusoidal signal as objectives.Firstly,we prove the characters of chaotic systems that are sensitive to periodic signals and immune to noise.Besides,after adding signals of different frequencies into AWGN channels,we obtain the signal-to-noise ratio of the system input,around-20dB,which is satisfying.