Satellite-enabled wireless power transfer (WPT) may be a transformative solution for charging Internet of Things (IoT) devices in off-grid scenarios where traditional technologies struggle to efficiently meet urgent energy demands. In this article, we review the advantages and limitations of microwave-based long-distance charging for satellite-enabled WPT. We then introduce our vision of coordinated space-based WPT, where multiple satellites jointly serve networks of ground devices. Potential use cases are presented highlighting application requirements. We evaluate the average received power at the target locations using two coordination schemes and perform a statistical characterization of the power spillover on undesired locations. We also shed light on the performance of inter-satellite laser WPT for different operating distances and transmit-receive apertures of the peer satellites. Moreover, we explore the integration of metasurfaces on satellite apertures and ground networks to boost energy conversion efficiency, scalability, and beam management. Finally, we outline relevant challenges and research directions towards implementing our vision.
O. M. Rosabal, Amirhossein Azarbahram, Mateen Ashraf et al.· 0 citations
Space-Air-Ground Integrated Networks (SAGINs) can extend connectivity, but their communication, computing, and platform operations create tightly coupled energy demands. Solar-powered High-Altitude Platforms (HAPs) offer a promising middle layer by combining persistent regional coverage, renewable-energy harvesting, and onboard computing. However, realizing this potential requires more than optimizing individual links or processors, as radio transmission, task execution, backhaul use, and battery preservation share a common energy budget. Therefore, we introduce a HAP-native Agentic AI framework. It continuously perceives communication, computing, energy, mobility, and mission states; invokes quantitative tools for prediction and verification; and coordinates executable actions through a closed control loop. Then, a multi-timescale design separates fast radio control from task orchestration and long-term energy planning. Furthermore, a disaster-recovery case study illustrates how the framework responds to backhaul congestion, traffic surges, and declining solar generation, improving energy efficiency, task completion, and latency over other baselines. We finally identify trustworthy control, collaborative multi-HAP orchestration, and digital-twin-assisted lifelong adaptation as key steps toward deployable, sustainable, and resilient SAGIN intelligence.