Wireless signal strength propagation model base on cubic spline interpolation

Abstract

An accurate wireless signal strength propagation model with less parameters was proposed to increase the application efficiency of fingerprint based positioning approaches in wireless networks,and to address the problems of wireless signal attenuation models,e.g.low computation efficiency,build complexity,and difficulty of parameter setting.The proposed model is an empirical model,which changes the attenuation factor n of the classical attenuation model,in terms of a cubic interpolation spline function of distance or received signal strength indicator(RSSI).The proposed model does not introduce any new parameter and is easy to compute.Experimental results indicated that in an indoor corridor environment,by trained with 10% samples,the proposed model estimated the wireless signal strength with an average error less than 0.4 dBm.Employing the calibration data generated by the proposed model,the fingerprint based positioning approach achieved a mean error less than 1.3 m.