Research On Key Technique Of Spectrum Access In Cognitive Radio Networks

With the development of wireless communication technology,spectrum resource is being more and scarcer, while cognitive radionetwork can dynamically utilize spare spectrum, and help cognitiveusers realize data transmission. In the design of cognitive radio networks,less consideration is taken on the aspect of energy efficiency, while withthe proposing of “green communication”, it is significant that designinga spectrum sensing and transmission strategy with high energyefficiency.In this thesis, we firstly research on the problem of designingoptimal spectrum sensing parameters in wide band cognitive radiosystem. Based on the two different network model in one primary user&multiple secondary users wide band cognitive radio system and theenergy consumption model of spectrum sensing, we propose the energyefficiency function of the system with the consideration of spectrumsensing and transmission. By converting energy efficiency function intoa parametric problem, we prove the feasible area of parametric problemis a convex set and the value of the determinant of its Hessian matrix isnegative for all case. Thus the optimal solution of parametric can beobtained on the boundary of feasible area. Then we investigate therelationship between parametric problem and original problem, andprove that as long as we can find the specific parameter which can makethe maximum value of parametric problem zero, we can obtain theoptimal solution of original problem. Then we proposed a fast algorithmcombined with bisection search approach, solve the energy efficiencymaximization problem under two network structures and givescorresponding simulation results.In addition, we also research on the problem of modeling primaryusers’ occupancy activities and the problem of designing optimal sensing and transmission strategy based on partial observable Markovdecision process model in this thesis, where we formulate the problem ofspectrum sensing and access as a problem of maximizing primary user’slong term energy efficiency, and gives the solution structure of optimalstrategy. As the computational complexity of solving optimal strategy istoo high, motivated by acquiring a sensing and access strategy with lowcomplexity, we focus on the architect of myopic strategy. Bymaximizing the reward expectation of excess channels, we obtain thesensing order of channels. Then we prove that the stopping rule ofmyopic strategy is threshold based and gives the closed form of thatthreshold. Simulation results show that, the gap between our proposedmyopic channel sensing&access strategy and the optimal strategy isless that8%.