  Future intelligent systems will consist of a massive number of battery-less
sensors, where quick and accurate aggregation of sensor data will be of
paramount importance. Over-the-air computation (AirComp) is a promising
technology wherein sensors concurrently transmit their measurements over the
wireless channel, and a reader receives the noisy version of a function of
measurements due to the superposition property. A key challenge in AirComp is
the accurate power alignment of individual transmissions, addressed previously
by using conventional precoding methods. In this paper, we investigate a
UAVenabled backscatter communication framework, wherein UAV acts both as a
power emitter and reader. The mobility of the reader is leveraged to replace
the complicated precoding at sensors, where UAV first collects sum channel
gains in the first flyover, and then, use these to estimate the actual
aggregated sensor data in the second flyover. Our results demonstrate
improvements of up to 10 dB in MSE compared to that of a benchmark case where
UAV is incognizant of sum channel gains.
