Characterization of Received Signal Strength Perturbations Using Allan Variance

The received signal strength (RSS) of wireless signals conveys important information that has been widely used in wireless communications, localization, and tracking. Traditional RSS-based research and applications model the RSS signal using a deterministic component plus a white noise term. This paper investigates the assumption of white noise to have a further understanding of the RSS signal and proposes a methodology based on the Allan variance (AVAR) to characterize it. Using AVAR, we model the RSS unknown perturbations as correlated random terms. These terms can account for both colored noise or other effects such as shadowing or small-scale fading. Our results confirm that AVAR can be used to obtain a flexible model of the RSS perturbations, as expressed by colored noise components . The study is complemented by introducing two straightforward applications of the proposed methodology: the modeling and simulation of RSS noise using Wiener processes, and RSS localization using the extended Kalman filter.