摘要
在认知无线网络(CRN)中,合理优化的资源分配可以提高网络的吞吐量。匈牙利算法因其在解决目标分配问题上不但避免程序陷入无限循环而且能够求得全局最优解而成为主流算法之一,但其存在时间复杂度较高且保持不变的问题。因此,文中提出一种改进的匈牙利信道分配算法。这种算法基于成本的方式进行子信道分配,根据带宽足迹(F)的差值来更新迭代中的子信道数量,从第二次迭代起利用本地成本信息降低算法的复杂度。最后仿真表明所提出的算法有效性。
The network throughput in cognitive wireless network（ CRN） depends on the rational allocation of channel resources. Hungary algorithm not only avoids the program into an infinite loop but also gets the global optimal solution in solving the problem of target assignment,Hungary algorithm becomes one of the mainstream algorithms,but it has the problem of a high degree of time complexity and remains the same. Therefore,an improved Hungary channel allocation algorithm is proposed. This algorithm is based on the cost of the sub channel allocation. The number of sub channels in the iteration is updated according to the difference of the bandwidth footprint（ F）. The complexity of the algorithm is reduced by using the local cost information from the second iteration. Finally,the simulation results show the effectiveness of the proposed algorithm.
出处
《信息技术》
2017年第11期72-75,共4页
Information Technology
基金
云南省科技厅面上项目(KKS0201403016)
