摘要
现有基于链路质量指示(LQI)的估计方法未能有效解决LQI参数波动较大的问题,并且所使用的LQI与收包率(PRR)的映射关系模型没有考虑实际物理意义。为此,通过推理LQI和PRR的理论关系,建立更具实际物理意义的双曲正切模型,并提出一种链路质量估计方法。通过指数加权卡尔曼滤波获得更为稳定的LQI估计值,再利用双曲正切模型对链路质量进行定量估计。实验结果表明,该方法能够更真实地反映链路质量,与LETX、K-CCI方法相比,其估计误差在不同质量链路下降低了11.21%~52.26%。
The existing estimation methods based on Link Quality Indicator(LQI)fail to effectively solve the problem of large fluctuation of LQI parameters.Besides,the mapping relationship model between LQI and Packet Receiving Rate(PRR)does not consider the actual physical meaning.Therefore,by inferring the theoretical relationship between LQI and PRR,this paper establishes a hyperbolic tangent model with more actual physical meaning,and proposes a link quality estimation method.On the basis of exponentially weighted Kalman filtering,a more stable LQI estimation is obtained,and then the link quality is quantitatively estimated by the hyperbolic tangent model.Experimental results show that the proposed method can reflect the link quality rather factually.Compared with the LETX and K-CCI method,the estimation error of this method is reduced by 11.21%~52.26%in different quality links.
作者
夏宇
刘伟
罗嵘
胡顺仁
XIA Yu;LIU Wei;LUO Rong;HU Shunren(School of Electrical and Electronic Engineering,Chongqing University of Technology,Chongqing 400054,China;Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2020年第5期216-223,共8页
Computer Engineering
基金
国家自然科学基金(61601069)
重庆市基础科学与前沿技术研究项目(cstc2017jcyjAX0254)
重庆市教委科学技术研究项目(KJ1600935)。
关键词
无线传感器网络
链路质量估计
链路质量指示
指数加权卡尔曼滤波
推理模型
双曲正切模型
wireless sensor network
link quality estimation
Link Quality Indicator(LQI)
exponentially weighted Kalman filtering
inference model
hyperbolic tangent model
