认知无线车载自组织网络中的联合路由调度

发布时间：2018-05-20 20:04

本文选题：认知无线电 + 车载自组织网络　；参考：《计算机研究与发展》2017年11期

【摘要】：通过将认知无线电(cognitive radio,CR)技术应用到车载自组织网络(vehicular ad hoc networks,VANETs)(也称车联网)中,认知无线车载自组织网络(CR-VANETs)可以缓解频谱资源稀缺问题,有效提高车对车通信的频谱资源利用率.由于车辆的高速移动性以及认知无线电频谱资源的动态特性,使得传统的认知无线电网络或车载自组织网络中的路由协议无法直接应用到CR-VANETs中.目前,针对CR-VANETs的路由研究相对较少,如何最大效率地利用有限的频谱资源,同时降低跳数过多带来的频谱资源浪费,仍然是一个有待解决的问题.为此,提出了一种CR-VANETs中联合路由调度方案,结合了有限频谱资源调度研究与最小化路由跳数的优化目标.首先,建立了CR-VANETs中的网络模型和基于车对车通信的频谱感知模型,预测车辆间有效接触时间和频谱可用概率.其次,通过这些参数定义出通信链路消耗,并由此得出权衡链路质量的权重因子.通过分析优化目标,将其转化为有限频谱资源约束下的最小化路由跳数问题,并证明该问题为NP难问题.然后,针对这个联合路由调度问题提出一种混合启发式算法,结合了粒子群优化算法的快速收敛性和遗传算法的种群多样性,对有限频谱资源进行调度,同时优化路由跳数.最后仿真实验结果表明,与现有的CR-VANETs路由研究比较,有着更优的路由跳数并使其保持在一个相对稳定的值.
[Abstract]:By applying cognitive radio (CR) technology to vehicle-borne ad hoc networks (VANETs), cognitive wireless vehicle-borne ad hoc networks (CR-VANETs) can alleviate the scarcity of spectrum resources and improve the efficiency of vehicle-to-vehicle communication. Due to the high-speed mobility of vehicles and the dynamic characteristics of cognitive radio spectrum resources, the routing protocols in traditional cognitive radio networks or vehicle-mounted ad hoc networks can not be directly applied to CR-VANETs. At present, there are few researches on CR-VANETs routing. How to make the most efficient use of limited spectrum resources and reduce the waste of spectrum resources caused by excessive hops is still a problem to be solved. In this paper, a joint routing scheduling scheme in CR-VANETs is proposed, which combines the research of finite spectrum resource scheduling and the optimization goal of minimizing the number of routing hops. Firstly, the network model in CR-VANETs and the spectrum sensing model based on vehicle-to-vehicle communication are established to predict the effective contact time and spectrum availability between vehicles. Secondly, the communication link consumption is defined by these parameters, and the weight factor to weigh the link quality is obtained. By analyzing the optimization objective, it is transformed into the minimized routing hops problem under the constraint of finite spectrum resources, and it is proved that the problem is NP-hard. Then, a hybrid heuristic algorithm is proposed for the joint routing scheduling problem. Combining the fast convergence of particle swarm optimization algorithm and the diversity of genetic algorithm, the finite spectrum resources are scheduled and the number of routing hops is optimized. Finally, the simulation results show that compared with the existing CR-VANETs routing research, it has better routing hops and keeps it at a relatively stable value.
【作者单位】：武汉大学计算机学院;武汉理工大学计算机科学与技术学院;
【基金】：国家自然科学基金项目(61772386) 广东省省级科技计划项目(2015B010131007)~~
【分类号】：TN925

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