Mobility State Detection of Cellular-Connected UAVs Based on Handover Count Statistics

Estimating the speed of aerial user equipment (UE) is critically important to provide reliable mobility management for cellular-connected unmanned aerial vehicles (UAVs) since this can enhance the quality of service. The 3GPP standard uses the number of handovers made by a UE during a predefined time period to estimate the speed and the mobility state efficiently. In this article, we introduce an approximation to the probability mass function of handover count (HOC) as a function of a cellular-connected UAV's height and velocity, HOC measurement time window, and different ground base station (GBS) densities. Afterward, we derive the Cramer-Rao lower bound (CRLB) for the speed estimate of a UAV and also provide a simple biased estimator for its speed based on the GBS density and HOC measurement period. We show that for a low handover parameter, the biased estimator turns into a minimum variance unbiased estimator (MVUE). Using this estimator, we study the problem of detecting the mobility state of a UAV as low, medium, or high mobility as per the 3GPP specifications. Using our proposed MVUE, we also characterize the accuracy improvement in speed estimation and mobility state detection as the GBS density and the HOC measurement window increase.