AirBeam: Experimental Demonstration of Distributed Beamforming by a Swarm of UAVs

Abstract

We propose AirBeam, the first complete algorithmic framework and systems implementation of distributed air-to-ground beamforming on a fleet of UAVs. AirBeam synchronizes software defined radios (SDRs) mounted on each UAV and assigns beamforming weights to ensure high levels of directivity. We show through an exhaustive set of the experimental studies on UAVs why this problem is difficult given the continuous hovering-related fluctuations, the need to ensure timely feedback from the ground receiver due to the channel coherence time, and the size, weight, power and cost (SWaP-C) constraints for UAVs. AirBeam addresses these challenges through: (i) a channel state estimation method using Gold sequences that is used for setting the suitable beamforming weights, (ii) adaptively starting transmission to synchronize the action of the distributed radios, (iii) a channel state feedback process that exploits statistical knowledge of hovering characteristics. Finally, AirBeam provides insights from a systems integration viewpoint, with reconfigurable B210 SDRs mounted on a fleet of DJI M100 UAVs, using GnuRadio running on an embedded computing host.