📝 SummarXiv

Abstract

A pinching-antenna systems (PASS)-enabled unmanned aerial vehicle (UAV) delivery framework is proposed, which exploits the capability of PASS to establish a strong line-of-sight link and reduce free-space pathloss.Aiming at minimizing the communication energy consumption in one cycle, a double-layer optimization (DLO) algorithm is developed by jointly optimizing the UAV delivery sequence and the pinching antenna (PA) activation vector. More specifically, at the outer layer, a hierarchical alternating optimization (HAO) scheme is proposed to tackle the NP-hard problem of delivery sequence planning, where a genetic algorithm performs global exploration to generate candidate solutions at the top-level, while a dynamic programming performs local refinement to obtain elite solutions at the lower-level. With determined UAV trajectory, at the inner layer, focus is placed on addressing the highly coupled mixed-integer nonlinear programming problem of PA activation vector optimization, where a pair of algorithms are proposed: 1) Branch-and-Bound (BnB) algorithm for finding global optimum; 2) incremental search and local refinement (ISLR) algorithm for reducing computational complexity. Simulation results indicate that: i) The proposed HAO-based delivery sequence planning scheme can effectively reduce the total flight distance, thereby decreasing flight time and communication energy consumption; ii) Both the proposed BnB and ISLR algorithms can achieve energy-efficient PA activation, with the former exhibiting better performance and the latter having lower complexity; iii) PASS outperforms the conventional multi-antenna systems, especially with higher communication rate requirements.