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To ensure reliable and effective mobility management for aerial userequipment (UE), estimating the speed of cellular-connected unmanned aerialvehicles (UAVs) carries critical importance since this can help to improve thequality of service of the cellular network. The 3GPP LTE standard uses thenumber of handovers made by a UE during a predefined time period to estimatethe speed and the mobility state efficiently. In this paper, we introduce anapproximation to the probability mass function of handover count (HOC) as afunction of a cellular-connected UAV's height and velocity, HOC measurementtime window, and different ground base station (GBS) densities. Afterward, wederive the Cramer-Rao lower bound (CRLB) for the speed estimate of a UAV, andalso provide a simple biased estimator for the UAV's speed which depends on theGBS density and HOC measurement period. Interestingly, for a lowtime-to-trigger (TTT) parameter, the biased estimator turns into a minimumvariance unbiased estimator (MVUE). By exploiting this speed estimator, westudy the problem of detecting the mobility state of a UAV as low, medium, orhigh mobility as per the LTE specifications. Using CRLBs and our proposed MVUE,we characterize the accuracy improvement in speed estimation and mobility statedetection as the GBS density and the HOC measurement window increase. Ouranalysis also shows that the accuracy of the proposed estimator does not varysignificantly with respect to the TTT parameter.

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