基于认知无线电技术的动态频谱分配方案研究

随着物联网的发展,人们能够更加方便快捷地利用智能终端,随时随地接入到无线网络中进行业务数据传输.然而,激增的移动用户数量和业务的带宽需求,使得无线频谱资源日益稀缺,现有固定式频谱分配方案面临巨大挑战.面向物联网发展,如何满足用户的高移动性和呈爆炸式增长的业务传输需求成为物联网研究的重点.认知无线电技术,一方面允许用户终端自适应感知所处环境的频谱资源空闲信息,为用户营造一个无缝的接入环境,保证用户的高移动性;另一方面通过动态频谱分配有效地解决了频谱资源稀缺和现有授权频谱资源利用率低的问题,为用户的海量数据传输提供保证.作者基于认知无线电技术,提出了一个用户终端和网络端共同参与决策的两级动态频谱分配框架结构,并提出了两级动态频谱分配方案.该方案设计包含:空闲频谱资源排序选择算法和集中式的联合优化匹配算法.通过用户终端和网络端的协同工作,文中所提出的两级动态频谱分配方案能够有效满足用户的高移动性和业务传输服务质量需求,实现空闲频谱资源利用率和频谱间切换概率的联合优化,为移动用户的海量数据传输提供保证.仿真实验结果表明,与传统图匹配方法相比较,该方案能够平均提高全网服务质量有效吞吐量70%,平均降低频谱间切换概率56%.

Research on Dynamic Spectrum Allocation Using Cognitive Radio Technologies

With the fast development of wireless communication technologies and the amazing increasing of user numbers in Internet of Things,the limited spectrum resources have become more and more scarce.However,today’s spectrum resources are regulated by a fixed assignment policy and they are in inefficient usage.How to satisfy users’ high mobility and mass date transmission requirements are new challenges.Cognitive Radio is one of these technologies that can offer users a seamless accessing environment,and solves the current spectrum inefficiency problems.It represents a great potential for the development of Internet of Things.In this paper,using Cognitive Radio technologies,we propose a cognitive radio users and networks cooperative spectrum allocation framework,then propose a dynamic spectrum allocation solution.This solution consists of two algorithms: One is a Spectrum Ranking Selecting algorithm(SRS) implemented at cognitive radio users,to meet their QoS and mobility requirements;and the other is a Joint Optimization Matching algorithm(JOM) implemented at the networks,by achieving the co-optimization between spectrum utilization and handoff rate to satisfy the mass data transmission requirement.With the cooperation between cognitive radio users and networks,our solution can construct an efficient dynamic spectrum allocation.Simulation results show that,compared with the traditional mapping algorithm,our solution can significantly improve the performance of networks in terms of throughput by 70% and spectrum handoff rate by 56%.