UAVs need to communicate along three dimensions (3D) with other aerial vehicles, ranging from above to below, and often need to connect to ground stations. However, wireless transmission in 3D space significantly dissipates power, often hindering the range required for these types of links. Directional transmission is one way to efficiently use available wireless channels to achieve the desired range. While multiple-input multiple-output (MIMO) systems can digitally steer the beam through channel matrix manipulation without needing directional awareness, the power resources required for operating multiple radios on a UAV are often logistically challenging. An alternative approach to streamline resources is the use of phased arrays to achieve directionality in the analog domain, but this requires beam sweeping and results in search-time delay. The complexity and search time can increase with the dynamic mobility pattern of the UAVs in aerial networks. However, if the direction of the receiver is known at the transmitter, the search time can be significantly reduced. In this work, multi-antenna channels between two UAVs in A2A links are analyzed, and based on these findings, an efficient machine learning-based method for estimating the direction of a transmitting node using channel estimates of 4 antennas (2 × 2 MIMO) is proposed. The performance of the proposed method is validated and verified through in-field drone-to-drone measurements. Findings indicate that the proposed method can estimate the direction of the transmitter in the A2A link with 86% accuracy. Further, the proposed direction estimation method is deployable for UAV-based massive MIMO systems to select the directional beam without the need to sweep or search for optimal communication performance.
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Beam Focusing by Scattering from an Array of Scatterers on a Drone
Beamforming by scattering from an array of scatterers carried by a drone is explored. By positioning the vertical heights of the scatterers on the drone, beam focusing can be achieved in a desired direction. Various horizontal layouts of the scatterers on the drone can be used, with a “double-cross” layout used here for the case of 9 scatterers. The formation of a null in the pattern in a desired direction is also possible using optimization of the scatterer positions.
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- Award ID(s):
- 1553063
- NSF-PAR ID:
- 10219783
- Date Published:
- Journal Name:
- 2021 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)
- Page Range / eLocation ID:
- 140 to 141
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.23919/USNC-URSINRSM51531.2021.9336436
