Research On The Spectrum Access Technologies Of Cognitive Radio System

In order to enhance the spectrum utilization, opportunistic spectrumaccess of cognitive radio system is widely studied. The basic idea is thatsecondary users could utilize the spatial and temporal spectrum white spacewhile limiting the interference perceived by primary users. As the basis ofspectrum access technologies, how to model the channel occupancy ofprimary users is an important topic. Therefore, this thesis mainly addressessuch issues as parameter estimation and channel access scheme ofopportunistic spectrum access based on continuous time Markov model andslotted Markov model.For parameter estimation problem in slotted Markov model, maximumlikelihood criterion is used to get a low complexity estimator of channel statetransition probabilities. Central Limit Theorem is then introduced to analyzethe convergence and get the relationship between the precision, sample timesand channel state transition probability values. Simulation results show themerits in terms of low estimation errors and fast convergence.A spectrum access scheme based on continuous time Markov channelmodel is then proposed. Firstly, we use a method similar to the slottedMarkov channel model to get the parameter estimators, which are simpler instructure and convergence. Secondly, the optimal data transmission time ofsecondary user is found by solving object function. A conversion factor ofguard interval is then used so as to guarantee that the system interferenceprobability is always below the threshold. We also determine when to beginthe re-estimation of channel parameters by tracking their changes through interference detection. Simulation results show the efficiency and feasibilityof this scheme.