Finite-Alphabet-Aware Trajectory and Precoder Optimization for UAV Relaying

Abstract

Unmanned aerial vehicles (UAVs) have become key enablers in relay-assisted wireless communications thanks to their flexibility and line-of-sight channel advantage. However, most existing trajectory optimization frameworks assume ideal Gaussian inputs, overlooking the fact that practical wireless systems rely on structured, finite-alphabet constellations. This mismatch can lead to suboptimal, and sometimes misleading, design choices. In this paper, we challenge that convention by introducing a finite-alphabet-aware framework for joint trajectory and precoder optimization in UAV-assisted relay systems. We formulate a non-convex design problem that directly accounts for discrete signal structures and propose an efficient solution based on alternating optimization and successive convex approximation. Simulation results reveal that strategies optimized under Gaussian assumptions can waste energy and degrade throughput in real deployments. In contrast, our approach adapts both the UAV's trajectory and transmission strategy to the underlying modulation format, delivering consistent performance gains under practical system constraints. This work takes a key step toward aligning UAV communication design with the realities of modern wireless systems: discrete signals, power limits, and intelligent mobility.