Abstract:
This project uses a systems approach to study how UAV millimeter wave (mmWave) radio transmitters provide high-throughput links under typical hovering conditions. We use Terragraph channel sounder units to study signal fluctuations and sub-optimal beam selection on a DJI M600 UAV testbed.
We develop and validate the first stochastic UAV-to-Ground mmWave channel model with UAV transmitters using hovering insights and antenna radiation patterns. Our UAV-centric analytical model considers 3-D antenna configuration and beamforming training parameters to add to classical fading in the mmWave channel during hovering.
We focus on lateral displacement, roll, pitch, and yaw, which depend on hardware like real-time kinematic GPS. We use this model to select a near-optimal pair of beams to reduce the hovering effect on the UAV-to-Ground link.
Our work is compatible with mmWave devices because it does not change the wireless standard or require cross-layer information. Our channel model reduces estimation error by 18x and improves the average PHY bit-rate by 10% compared to state-of-the-art channel models and beamforming methods for UAVs.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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