High-altitude platforms (HAPs) are emerging as persistent middle-layer infrastructures for space-air-ground integrated networks (SAGINs), offering a favorable compromise among coverage, latency, endurance, and deployment flexibility. Their role, however, is evolving beyond communication relaying toward the joint provision of sensing, storage, communication, computing, and intelligence (S^2C^2I). This survey presents a unified HAP-centric perspective on S^2C^2I integration. We first review HAP fundamentals, platform categories, and their principal roles in SAGINs, including wide-area access, relaying, backhaul, edge service, low-altitude aerial coordination, and cross-layer orchestration. We then develop an integrated architecture spanning multi-plane connectivity, payload functional splits, and a cloud-edge-HAP space continuum with hierarchical data, control, computing, and storage loops. The enabling technologies are systematically examined, covering heterogeneous RF, millimeter-wave, terahertz, free-space optical, and hybrid links; sensing payloads and integrated sensing and communication; onboard computing; storage and caching; and AI-based orchestration. We further synthesize standardization progress, open software and datasets, testbeds, field evidence, and a four-level evaluation methodology ranging from component validation to mission-level effectiveness. An emergency-response case study demonstrates that joint S^2C^2I orchestration substantially improves conjunctive service availability while reducing feeder-link traffic. Finally, we identify research opportunities in agentic AI, trustworthy autonomy, goal-oriented semantic operation and digital twins, and sustainable, certifiable, and open HAP-native systems. The resulting synthesis provides a coherent roadmap from platform design to network-wide deployment.
Free-space optical (FSO) communication has emerged as a promising technology, but its performance is highly dependent on line-of-sight (LOS) conditions. To address this limitation, we propose a multistage optical intelligent reflecting surface (OIRS)-assisted FSO communication system, which utilizes multiple OIRS nodes to dynamically reflect and redirect optical signals toward the receiver, even in the absence of direct LOS paths. In this work, we first establish a generalized geometric misalignment loss (GML) model for multistage OIRS systems under both two-dimensional (2D) and three-dimensional (3D) deployment scenarios. Building on the 3D GML model, we construct a comprehensive statistical channel model by incorporating Gamma-Gamma (GG) atmospheric turbulence and attenuation losses. Furthermore, we propose a multi-OIRS-assisted unmanned aerial vehicle (UAV)-based non-terrestrial network (NTN) system and analyze its performance. We derive semi closed-form expressions for the outage probability (OP), average bit error rate (BER), channel capacity, and moments of the signal-to-noise ratio (SNR). Additionally, we present asymptotic expressions for OP and BER in the high-SNR regime and determine the diversity order of the system.
Shunyuan Shang, Emna Zedini, A. Kammoun et al.· IEEE Transactions on Wireles...· 0 citations
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.