UAV ground-to-air channel prediction during blockages using six dimensional channel data

Citation Author(s):
Wahab Ali Gulzar
ECE Dept., North Carolina State University, Raleigh, NC
ECE Dept., North Carolina State University, Raleigh, NC
ECE Dept., North Carolina State University, Raleigh, NC
Submitted by:
Wahab Ali Gulza...
Last updated:
Sun, 05/22/2022 - 11:24
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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.


1- In this work, we have obtained ray tracing channel data of UAV ground-to-air propagation scenario using Wirless InSite software. The channel data is captured at 28 GHz. 

2- Six dimensional channel data is used for channel prediction during blockages. The six dimensional channel data for channel prediciton is received power, delay, angle of arrival (azimuth, elevation), and angle of departure (azimuth and elevation). The phase data is not considered for channel prediction.

3- A Markov chain model based on the minimum Euclidean distance among the channel parameters is used for first sorting the channel data with respect to receiver positions. The sorted channel data can provide information related to trajectory of the UAV flight in the given environment. Then, an autoregressive model is used on the sorted channel data for prediction during blockages.


Note: The folder contains the ray tracing channel data, sample matlab code for data processing, and plotting. The provided matlab code is for received power of multipath components. The same code can be applied for viewing other channel parameters.    

The details of the setup are further provided in the following paper:

W. Khawaja, O. Ozdemir and I. Guvenc, "Channel Prediction for mmWave Ground-to-Air Propagation Under Blockage," in IEEE Antennas and Wireless Propagation Letters, vol. 20, no. 8, pp. 1364-1368, Aug. 2021, doi: 10.1109/LAWP.2021.3078268.

Funding Agency: 
Funded by NASA under the award NNX17AJ94A


Feel free to ask any questions regarding the data and code at

Submitted by Wahab Ali Gulza... on Sun, 05/22/2022 - 10:08