Joint Beamforming and User Association Design for Integrated HAPS-Terrestrial Networks

Located in the stratospheric layer of Earth's atmosphere, the high altitude platform station (HAPS) is a promising network infrastructure, which can bring significant advantages to sixth-generation (6G) and beyond wireless communications systems by forming vertical heterogeneous networks (vHetNets). However, if not dealt with properly, integrated networks suffer from several performance challenges compared to standalone networks. In harmonized integrated networks, where different tiers share the same frequency spectrum, interference is an important challenge to be addressed. This work focuses on an integrated HAPS-terrestrial network, serving users in an overlapped urban geographic area, and formulates a fairness optimization problem, aiming to maximize the minimum spectral efficiency (SE) of the network. Due to the highly nonconvex nature of the formulated problem, we develop a rapid converging iterative algorithm that designs the massive multiple-input multiple-output (mMIMO) beamforming weights and the user association scheme such that the propagated inter- and intra-tier interference is managed. Simulation results demonstrate the proposed algorithm's superiority over standalone terrestrial networks and scenario where only the beamforming weights are optimized.Comment: 8 pages singlecolumn, 5 figures, under review in IEEE Communications Letter

Data Center-Enabled High Altitude Platforms: A Green Computing Alternative

Information technology organizations and companies are seeking greener alternatives to traditional terrestrial data centers to mitigate global warming and reduce carbon emissions. Currently, terrestrial data centers consume a significant amount of energy, estimated at about 1.5% of worldwide electricity use. Furthermore, the increasing demand for data-intensive applications is expected to raise energy consumption, making it crucial to consider sustainable computing paradigms. In this study, we propose a data center-enabled High Altitude Platform (HAP) system, where a flying data center supports the operation of terrestrial data centers. We conduct a detailed analytical study to assess the energy benefits and communication requirements of this approach. Our findings demonstrate that a data center-enabled HAP is more energy-efficient than a traditional terrestrial data center, owing to the naturally low temperature in the stratosphere and the ability to harvest solar energy. Adopting a data center-HAP can save up to 14% of energy requirements while overcoming the offloading outage problem and the associated delay resulting from server distribution. Our study highlights the potential of a data center-enabled HAP system as a sustainable computing solution to meet the growing energy demands and reduce carbon footprint

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial