无人机集群网络中一种基于链路质量预测的按需路由算法  

A Link Quality Prediction Based On-Demand Routing Algorithm for UAVs Swarm Network

作　　者：贾旭峰 茹乐[1] 乐波 于云龙[1] 方堃[1] 

机构地区：[1]空军工程大学无人机运用工程系,西安710038 [2]盲信号处理重点实验室,成都610041

出　　处：《空军工程大学学报（自然科学版）》2017年第5期48-54,共7页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：陕西省自然科学基础研究计划(2017JM6071)

摘　　要：无人机集群网络,相较于传统Ad Hoc网络,其节点速度更快,拓扑变化更剧烈。传统路由算法已难以满足无人机集群作战需要。因此,提出一种基于链路质量预测的按需路由算法。通过链路稳定度和节点拥塞度评估当前链路质量,并以此作为选路标准。同时,通过灰色-WNN组合预测模型,对相关参数进行合理预测,并以此估计链路稳定性与节点拥塞程度,进而对链路质量进行提前评估。算法根据得到的链路质量预测值来优化路由发现与路由维护过程,避免无人机的高动态特性对集群网络的不利影响。仿真结果表明,与AODV及其他相关改进算法相比,该算法明显改善了网络性能,减少了路由断裂的次数,大幅降低了节点高速移动时的路由开销与平均时延,使分组投递率得到明显提高。Topology of UAV ad hoc networks is more dynamic due to fast movement of nodes compared with other traditional ones. The performance of traditional routing algorithms is not able to satisfy efficient communication for multi-UAVs carrying out missions, and this paper proposes an on-demand routing algorithm based on link quality prediction. The link quality is chosen as a standard to choose route and calculated by sensing the stability of a link and the congestion level of a link. Meanwhile, relevant parameters are predicted by Grey-WNN prediction model, and then they are used to estimate the stability of a link and the congestion level of a link. After that, the link quality can be evaluated in advance. The process of routing discovery and routing maintenance is optimized according to the predicted link quality, thus avoiding the negative influence on swarm network caused by the high-dynamic characteristics of UAVs. The simulation results show that the algorithm improves the network performance obviously, decreases the number of route fracture, reduces the route overhead and average delay increases the packet delivery ratio when nodes are moving at a high speed.

关 键 词：无人机集群 AD HOC网络 路由算法 链路质量预测 

分 类 号：V416.216[航空宇航科学与技术—航空宇航推进理论与工程]