Research On Cognitive Radio Spectrum Allocation Strategy Based On Intelligence Algorithm

With the improvement of human society, various wireless signals have become more and more significant. However, the more types in the communication business, the more deficient spectrum resources become. In fact, the low utilization of spectrum is the reason why spectrum resources become so deficient. So the cognitive radio was born to solve the problem. How to improve the utilization rate of the spectrum resources is very significant and also is the key problem of cognitive radio spectrum allocation.Among the all the cognitive radio spectrum strategy, color sensitive graph coloring model based techniques are much more mature. Accordingly, this thesis is based on this model. Some scholars had proposed some spectrum allocation algorithms that based on Binary Particle Swarm Optimization. But the BPSO algorithm has the problem of low convergence rate and lack of theory research on the settings of parameters.On the basis of researching on the fundamental principle and the computation procedure of BPSO, this thesis has discussed the difference between the BPSO and PSO on the inertial factor. Then, this thesis proposed a suitable value of the inertial factor. Also, this thesis made some improvement on the basic BPSO. Including the chaos based initiation of original population which makes the initial population more homogeneous, changing of the formula about location updating which makes the algorithm a more powerful local searching ability and introducing of particle mutation based on the degree of population aggregation which makes the algorithm less likely falling into local optimum. Finally, this thesis proved that the proposed algorithm is superior to SCGC, SAGA and BPSO algorithms through emulation.