Mobility State Estimation: Performance and Tradeoff Considerations

Estimating mobile user speed is a problematic issue which has significant impacts to radio resource management and also to the mobility management of 3GPP Long Term Evolution (LTE)/LTE-Advanced (LTE-A) networks. This paper presents two algorithms that can estimate the speed of mobile user equipments (UE), with low computational requirement, and without modification of neither current user equipment nor 3GPP standard protocol. The proposed methods rely on uplink (UL) sounding reference signal (SRS) power measurements performed at the eNodeB (eNB) and remain efficient with large sampling period (e.g., 40ms or beyond). We also present an online algorithm for mobile user speed estimation. Extensive performance evaluation of the proposed algorithm is carried out using field traces from realistic environment. Results show that the classification of UE's speed required by LTE can be achieved with high accuracy. In addition, the online solution is proven to have minimal impact to the central processing unit (CPU) and the memory of eNB modem. In particular, we show that the proposed algorithm can allow for the first speed estimation to be obtained in 10 seconds with an average speed overestimation error of 7 kmph. After the first speed acquisition, subsequent speed estimations can be obtained much faster (e.g., each second) with limited implementation cost and still provide high accuracy.