分枝定界在多级动态频谱分配中的应用

Application of Branch and Bound Theory to the Multi-level Dynamic Spectrum Allocation

针对认知无线电动态频谱分配中认知用户较多,传统优化算法收敛时间较长的问题,本文结合分枝定界原理提出一种多级动态频谱分配算法。首先建立基于用户需求的多级动态频谱分配模型,然后借助图着色理论,将问题转化为函数优化问题,最后借助分枝定界算法,通过把全部可行的解空间不断分割为越来越小的子集,从而实现了对该多级模型的频谱分配。仿真实验采用与遗传算法比较,通过对二者认知用户接入量和系统网络效益的分析比较,表明该算法对处理多级DSA分配问题的优越性,且所提算法具有较小的计算复杂度,具有较高的应用价值。

Aiming at the problems that there are many cognitive users in the dynamic spectrum assignment issue in cognitive radio,and the traditional optimization algorithms cost amounts of convergence time.A multi-level dynamic spectrum allocation algorithm is presented based on branch and bound theory.This paper first build a model of DSA system with multilevel based on user demand,and then the problem was formulated as a functional optimizing by means of the graph-coloring theory,finally The branch and bound optimization algorithm is introduced to the model,the algorithm put all the practicable solution space constantly dividing into smaller and smaller subsets,by this way the dynamic spectrum allocation is implemented to the model of DSA system with multi-level.The simulation experiment is taken with comparison on the basic genetic algorithms,through the analysis of the amount of the cognitive user access and the system profits,the simulation results show the superiority of the classification model in dealing with the problem of DSA with multi-level.And the algorithm proposed has an relatively small computation complexity,which is of a relatively high application value.