Generative AI Agent Empowered Power Allocation for HAP Propulsion and Communication Systems
2026-04-10 • Networking and Internet Architecture
Networking and Internet ArchitectureInformation Theory
AI summaryⓘ
The authors study how flying communication platforms at high altitudes can best use their limited power for both flying and sending data. They created an AI-based tool to better understand how the aircraft’s shape and propellers affect energy use when flying. Using this, they designed a method to improve the quality and energy efficiency of the communication signals. Their tests show their power model and method work well together. This helps balance flying energy and communication quality more accurately than before.
High Altitude Platform (HAP)6G CommunicationPropulsion PowerBeamformingAerodynamicsEnergy EfficiencyQuality of Service (QoS)Artificial Intelligence (AI)Power AllocationWireless Communication
Authors
Xiaoyu Xing, Dingyi Lu, Peng Yang, Zehui Xiong, Xianbin Cao, Tony Q. S. Quek
Abstract
High altitude platforms (HAPs) are emerging as a key enabler for 6G coverage, yet limited energy must be split between propulsion and communications. Most prior HAP studies ignore propulsion power or rely on surrogates that miss hull-propeller interference, leading to misestimated communication power budgets and degraded beamforming. More importantly, HAP power allocation is intrinsically a multi-system, multidisciplinary problem in which aerodynamics, propulsion-system efficiency, and communication-system performance (quality of service (QoS) and energy efficiency (EE)) are tightly coupled.To address these challenges, this paper designs an interactive generative artificial intelligence (AI)-empowered HAP power allocation agent.By interacting with the AI agent, we develop an accurate propulsion power consumption model that takes into account the aerodynamic interference between the HAP's hull and the propeller. Assisted by the AI agent, we further formulate a HAP beamforming problem to improve user QoS and enhance the EE of the HAP communication system.This paper also proposes a QoS-enhanced energy-efficient (Q3E) beamforming algorithm to solve the formulated problem.Simulation results demonstrate the accuracy of the propulsion-power model and the effectiveness of the Q3E algorithm.