Communication RSSI prediction and validation framework for advanced air mobility

Abstract

This paper proposes a communication signal strength prediction and validation framework for the use of advanced air mobility. Advanced air mobility, including urban air mobility and unmanned aerial vehicles, requires a scalable, safe, and seamless communication infrastructure different from conventional aircraft. This paper proposes a hybrid regression-based prediction method that combines synthetic data generated from a ray-tracing model and real flight test data in the urban airspace and uses k-fold cross-validation to evaluate the predicted signal strength. The results show that the proposed framework provides reliable performance indices, effectively mitigating the insufficiency of flight data. This research will enable evaluating the communication infrastructure and identifying high-risk areas for advanced air mobility stakeholders.