无线认知网络中一种分布式最大频谱分配算法

A Distributed Maximum Spectrum Allocation Algorithm for Wireless Cognitive Networks

无线认知网络被认为是下一代无线网络的核心架构之一。该网络能解决日益增长的频谱使用需求和低下的频谱使用率之间的矛盾。通过伺机接入临时可用频谱资源,其频谱利用率能得到大幅的提高。由于频谱资源分配是影响频谱资源利用率的关键,因此如何对频谱资源进行高效的分配一直是无线认知网络的重要研究领域之一。我们证明了在异构频谱使用概率条件下的最优频谱分配是NP难的问题。为了有效解决该问题,本文提出了一种基于分布式最大加权独立集的频谱分配算法——DMWIS。该算法的时间复杂度为O(V2/2)。通过大量的仿真实验,验证了在90%以上的不同随机网络环境下算法能在3轮内收敛,并且该算法一般能获得最优解90%的性能。

Wireless cognitive network is regarded as one of the fundamental architectures of next generation wireless network.It can solve the key problem of increasing demand for spectrum and low spectrum utilization.By opportunistically accessing the temporal available spectrum,the spectrum utility can be increased tremendously.As the spectrum utility is mainly determined by the spectrum allocation scheme,how to efficiently allocate the spectrum is always one of the fundamental aspects of wireless cognitive research domain.We have proved that the optimal spectrum allocation problem under heterogeneous spectrum availability is NP hard.To solve the spectrum allocation problem efficiently,a new spectrum access approach was proposed which is based on the distributed maximum weighted independent set algorithm——DMWIS.The time complexity of this algorithm is O（V2/2）.By detailed simulation,the algorithm can be finished within 3 rounds under 90% of the random network scenarios.The performance of this algorithm can reach 90% performance of optimal algorithm.