Adaptive Spectrum Management in UAV-Aided Ad-Hoc Wireless Networks in Single-area Theater

Unmanned aerial vehicle (UAV)-aided wireless ad- hoc networks have become an important component of today's battleground. This paper considers the dynamic spectrum management problem in a single-theater UAV-aided ad-hoc wireless network. We propose spectrum management and rate allocation algorithms in a multi-rate, multi-channel UAV-aided ad hoc wireless network that uses link adaptation. We also evaluate the impact of the quality of the channel state prediction on the throughput of the system. Two different metrics of prediction quality are considered: (i) Look-ahead, defined as the number of future time slots over which CSI is available at the decision time for the current time slot, and (ii) prediction error, which is the probability that the estimate for a future channel state is different from the actual one. We use simulations together with performance bounds to the offline version of the problem to evaluate the performance with varying prediction quality. Our results can provide meaningful guidelines in deciding what level of system resource consumption (bandwidth, time, power, and additional complexity) is justified in UAV-aided ad hoc networks for channel quality estimation and link adaptation. Our results suggest that it may be possible to reap most of the potential UAV-aided predictive scheduling benefits with a small look-ahead, and imperfect channel state estimates.