The Impact of Weather Condition on Radio-Based Distance Estimation: A Case Study in GSM Networks With Mobile Measurements

Abstract

Distance estimation based on the received signal strength (RSS) of wireless radio has been extensively studied; however, the estimation accuracy is susceptible to radio propagation conditions, particularly during periods of precipitation. This study performed experiments on the 1.8-GHz band of Global System for Mobile Communications (GSM) networks at Yuan Ze University, Taoyuan, Taiwan, sensing actual radio power signals using mobile phones and recording transmission conditions during various weather events. The aim was to compare RSS performance under dry and wet weather conditions and study the dynamics of distance estimation from theoretical and empirical perspectives. Traditional rain attenuation models have largely discounted the impact of precipitation on GSM signals due to the relatively low frequency band; however, on-site experimental results demonstrated that dynamic weather significantly degrades accuracy in distance estimation. This study employed a typical rain attenuation model and a radio propagation model to evaluate errors in distance estimation under various rain conditions, i.e., heavy rain, extremely heavy rain, torrential rain, and extremely torrential rain, in accordance with the standards set out by the Central Weather Bureau, Taiwan. This study also investigated the RSS attenuation under various wind speeds. The Cramer–Rao lower bound (CRLB) was used as a benchmark for comparison.