Skip to Main Content
Wireless localization using the received signal strength (RSS) can have tremendous savings over using specialized positioning infrastructures. In this work, we explore improving RSS localization performance in multipath environments by varying the transmitter's signal power and frequency. We first derive and analyze the Cramér-Rao Lower Bound (CRLB) of RSS-based localization based on the frequency dependent path loss propagation model that considers the transmitter's signal power and frequency. The derived CRLB shows the feasibility of improving localization performance by applying frequency and power level selection for RSS-based localization. Using this analysis, we develop two new selection metrics based on the observed standard deviations of RSS as well as residuals. We then show a set of selection methods that attempt to select the combinations of power and frequencies which minimize the localization error in a representative class of localization algorithms. Our simulation results confirm the proposed selection methods can improve the localization accuracy under CRLB. Additionally, using active RFID tags, we experimentally characterize the effect of using multiple signal powers and frequencies on a wide spectrum of RSS-based algorithms. We found that the performance of all the algorithms improves when leveraging on multiple power levels and frequencies, although different algorithms present different sensitivity in terms of localization accuracy under different selection methods.