Real-Time Detection and Prediction-Aided Dynamic Location Area Design for High-Mobility Users Based on LEO Satellites

In multi-beam low-Earth-orbit (LEO) satellite communication networks, high-mobility aerial users, such as unmanned aerial vehicles (UAVs), high-speed aircraft, and near-space vehicles, may traverse multiple satellite beams within a short period of time. When the precise position of a target user is not continuously available to the network, the network needs to determine the set of beams in which the user is likely to be located when a paging request arrives. The corresponding communication satellites then transmit paging messages within these candidate beams to reach the target user. If the selected beam set does not cover the user's actual position, the paging attempt fails; however, excessively enlarging the paging region or frequently updating the user's location information introduces additional signaling and management overhead. Therefore, the key problem is to construct an accurate and adaptive paging region under the joint mobility of the user and LEO satellite beams. To address this problem, this paper proposes a network-side sensing- and prediction-aided dynamic location-area management method for high-mobility users. First, based on a three-stage motion model of high-mobility users, LEO satellite ephemeris information, and beam coverage parameters, the coverage performance during the whole flight process of high-mobility users is analyzed. Second, a high-mobility user state prediction mechanism integrating a three-stage motion model and square-root cubature Kalman filtering (TSM-SRCKF) is proposed. This mechanism can adaptively adjust the weights of different motion models according to the current motion state of the high-mobility user and suppress the influence of abnormal measurements during the measurement update process, thereby obtaining more reliable position prediction results and error covariance information. Finally, a TSM-SRCKF-aided dynamic location-area management method is proposed. Simulation results show that the root-mean-square error of the high-mobility user position under the proposed mechanism is only 23.3% of that of the comparison mechanism. Compared with the traditional velocity-based dynamic location area design method, the proposed method improves the paging success probability by about 60.1% and reduces the cumulative total management overhead by about 73%.