  Propelled by multi-user MIMO (MU-MIMO) technology, unmanned aerial vehicles
(UAVs) as mobile hotspots have recently emerged as an attractive wireless
communication paradigm. Rate adaptation (RA) becomes indispensable to enhance
UAV communication robustness against UAV mobility-induced channel variances.
However, existing MU-MIMO RA algorithms are mainly designed for ground
communications with relatively stable channel coherence time, which incurs
channel measurement staleness and sub-optimal rate selections when coping with
highly dynamic air-to-ground links. In this paper, we propose SensRate, a new
uplink MU-MIMO RA algorithm dedicated for low-altitude UAVs, which exploits
inherent onboard sensors used for flight control with no extra cost. We propose
a novel channel prediction algorithm that utilizes sensor-estimated flight
states to assist channel direction prediction for each client and estimate
inter-user interference for optimal rates. We provide an implementation of our
design using a commercial UAV and show that it achieves an average throughput
gain of 1.24\times and 1.28\times compared with the bestknown RA algorithm for
2- and 3-antenna APs, respectively
