Link quality prediction model based on Gaussian process regression - Jian SHU; Manlan LIU; Yaqing SHANG; Yubin CHEN; Linlan LIU (Tongxin xuebao)
Link quality is an important factor of reliable communication and the foundation of upper protocol design for wireless sensor network.Based on this,a link quality prediction model based on Gaussian process regression was proposed.It employed grey correlation algorithm to analyze correlation between link quality parameters and packet receive rate.The mean of the link quality indication and the mean of the signal-to-noise were selected as input parameters so as to reduce the computational complexity.The above parameters and packet receive rate were taken to build Gaussian process regression model with combination of covariance function,so that link quality could be predicted.In the stable and unstable scenarios,the experimental results show that the proposed model has better prediction accuracy than the one of dynamic Bayesian network prediction model.