Joint Trajectory, Power, and Blocklength Optimization for Energy-Efficient UAV-Aided Short-Packet Visible Light Communications

Abstract

Next-generation wireless communication requires ultra-low latency, high data rate, and superior energy efficiency (EE). UAV-aided short-packet visible light communication (VLC) emerges as a promising paradigm to meet these requirements. This paper investigates the joint optimization of UAV trajectory, transmit power, and blocklength to maximize the EE of a UAV-aided short-packet VLC system. We establish the UAV motion and short-packet VLC transmission models, and formulate an EE maximization problem subject to practical constraints. To tackle the resulting fractional and non-convex optimization problem, we adopt the Dinkelbach iterative framework and decompose the problem into three subproblems: the trajectory optimization subproblem, power allocation subproblem, and blocklength optimization subproblem. Each subproblem is transformed into a convex form via cyclic maximization and successive convex approximation. Based on this, we propose a Dinkelbach-based iteration (DBI) algorithm and a low-complexity fixed power (FP) algorithm. Theoretical analysis shows that both algorithms are convergent and computationally efficient. Numerical results demonstrate that the proposed DBI algorithm achieves the best EE performance, while the FP algorithm obtains comparable performance with significantly reduced complexity. Both proposed algorithms consistently outperform existing benchmarks.