Khawaja Wahab, Ozdemir Ozgur, Guvenc Ismail
W. Khawaja is with the Mirpur University of Science & Technology, Pakistan.
IEEE Antennas Wirel Propag Lett. 2021 Aug;20(8):1364-1368. doi: 10.1109/lawp.2021.3078268. Epub 2021 May 7.
Ground-to-air (GA) communication using unmanned aerial vehicles (UAVs) has gained popularity in recent years and is expected to be part of 5G networks and beyond. However, the GA links are susceptible to frequent blockages at millimeter wave (mmWave) frequencies. During a link blockage, the channel information cannot be obtained reliably. In this work, we provide a novel method of channel prediction during the GA link blockage at 28 GHz. In our approach, the multipath components (MPCs) along a UAV flight trajectory are arranged into independent path bins based on the minimum Euclidean distance among the channel parameters of the MPCs. After the arrangement, the channel parameters of the MPCs in individual path bins are forecasted during the blockage. An autoregressive model is used for forecasting. The results obtained from ray tracing simulations indicate a close match between the actual and the predicted mmWave channel.
近年来，使用无人机（UAV）进行地对空（GA）通信越来越受欢迎，并且有望成为5G网络及以后网络的一部分。然而，GA链路在毫米波（mmWave）频率下容易受到频繁阻塞的影响。在链路阻塞期间，无法可靠地获取信道信息。在这项工作中，我们提供了一种在28GHz的GA链路阻塞期间进行信道预测的新方法。在我们的方法中，沿着无人机飞行轨迹的多径分量（MPC）基于MPC信道参数之间的最小欧几里得距离被排列到独立的路径仓中。排列之后，在阻塞期间预测各个路径仓中MPC的信道参数。使用自回归模型进行预测。从射线追踪模拟获得的结果表明，实际毫米波信道与预测的毫米波信道之间匹配度很高。
