Accelerating development in UAV network digital twins with a flexible simulation framework

Unmanned aerial vehicles (UAVs) enhance coverage and provide flexible
deployment in 5G and next-generation wireless networks. The performance of
such wireless networks can be improved by developing new navigation and
wireless adaptation approaches in digital twins (DTs). However, challenges
such as complex propagation conditions and hardware complexities in
real-world scenarios introduce a realism gap with the DTs. Moreover, while
using real-time full-stack protocols in DTs enables subsequent deployment
and testing in a real-world environment, development in DTs requires high
computational complexity and involves a long development time. In this
paper, we develop a measurement-calibrated Matlab-based simulation
framework to accelerate the development cycle to replicate performance in
a full-stack UAV wireless network DT. In particular, we use the
DT from the NSF AERPAW platform and compare its reports with those
generated by our developed simulation framework in wireless networks with
similar settings. In both environments, we observe comparable results in
terms of RSRP measurement, hence motivating iterative use of the developed
simulation environment with the DT.