FALCON: Flight-Aware Link Adaptation for A2G Communications

Abstract

In stationary wireless channels, traditional Adaptive Modulation and Coding (AMC) techniques rely on physical-layer metrics such as the Signal-to-Interference-plus-Noise Ratio (SINR) and the Bit Error Rate (BER) to select an appropriate Modulation and Coding Scheme (MCS). However, Air-to-ground (A2G) UAV communication channels exhibit highly nonstationary behavior due to mobility-induced variations in antenna geometry and propagation conditions, limiting the effectiveness of conventional channel-driven AMC schemes. This paper shows that UAV flight dynamics fundamentally alter MCS feasibility regions, and proposes a mobility-conditioned MCS adaptation framework validated on a real SDR testbed. Frame-level Bit Error Rate (BER) measurements are jointly analyzed with UAV telemetry under different flight conditions. Experimental results have shown that the antenna misalignment caused by yaw is the most prevalent cause of performance degradation for UAV communications. We are inspired by this finding to develop a dual-metric MCS feasibility model that jointly exploits SINR and Error Vector Magnitude (EVM) as well as flight-state-aware operating constraints derived from measured UAV dynamics. Offline evaluation using synchronized communication and UAV flight telemetry traces collected during real SDR-based flight experiments demonstrates that the proposed flight-aware Adaptive Modulation (AM) framework achieves a 93.1% reduction in average BER compared with conventional AM. These results show that the channel quality alone cannot guarantee reliable Adaptive Modulation in dynamic aerial links, and identify UAV flight state (especially orientation) as a complementary adaptation dimension for future aerial communication systems.