On Cyclostationary Spectrum Sensing For Cognitive Radio Systems

With the rapid development of wireless communication technologies,wireless communication services and users,together with their requirement of spectrum resources,also grown explosively.However,current static spectrum allocation policy causes low utilization efficiency of spectrum resources.Cognitive radio,which allows users to dynamically access to the licensed channels and to share spectrum resources with primary users,may solve this contradiction.Spectrum sensing is one of the key technologies in cognitive radio.This thesis focuses on the spectrum sensing by using the cyclostationary feature of primary signals.The main contributions are as follows.(1)The detection performance of cyclostationary detection is much better than energy detection.However,noise uncertainty will severely degrade its performance.Aiming at this problem,a cyclostationary detection resisting to noise uncertainty is proposed.It is proved that the noise cyclic spectrum components at different cycle frequencies are independent and identically distributed in two-dimensional cyclic spectrum.Based on this,the noise distribution at the cycle peak was estimated using all values except the spectrum peak positions of licensed user signal,and decision threshold was obtained without noise power prior knowledge,so as to avoid the influence of noise uncertainties.Simulation results demonstrate that the performance of the proposed method is close to that of cyclostationary detection method with known noise power.(2)After configuring an OFDM(Orthogonal Frequency Division Multiplexing)wireless communications system using GNU Radio and USRP(Universal Software Radio Peripheral),we propose a novel cyclostationary spectrum sensing method for detecting OFDM signals.Different from the conventional cyclostationary-based spectrum sensing methods,the proposed one requires no prior knowledge of noise power.Hence,the proposed detector is robust to noise uncertainty.Finally,experimental results demonstrate the performance of the proposed detector.