High Altitude Platform Station Research Articles

Investigating high altitude platform stations communication in Tanzania under heavy rain conditions

AbstractHigh altitude platform station (HAPS) is one of the promising solutions to many of the developing and less developed countries. To a great extent, HAPS is relatively cost‐effective and can be easily moved on demand while observing the required quality of service. For tropical countries, rain attenuation is the main factor that affects HAPS performance. This study investigated HAPS performance in Tanzania under heavy rain conditions. Rain rate, rain attenuation, and carrier‐to‐noise ratio were used to quantify the system's performance. In this study, the rain rate exceeds by 0.01% of an average, was obtained using the Chebil model. Based on Tanzania Meteorological Agency data, the registered a high amount of rainfall for the five selected regions: Dar es Salaam, Kagera, Tanga, Unguja, and Pemba. By using ITU‐R model, rain attenuation for the downlink was predicted, assuming horizontal polarisation, for 31.0–31.3 GHz. Finally, the HAPS link budget was analysed with a platform altitude of 22 km at frequency of 31.0–31.3 GHz for different elevation angles. Results showed that the performance of the system was promising in the given rainfall scenarios.

Time-Efficient Neural-Network-Based Dynamic Area Optimization Algorithm for High-Altitude Platform Station Mobile Communications

Time-Efficient Neural-Network-Based Dynamic Area Optimization Algorithm for High-Altitude Platform Station Mobile Communications

Reliability and availability analysis of high-altitude platform stations through semi-Markov modeling

In the development and deployment of both tethered and autonomous High Altitude Platform Station (HAPS), flight modules such as hexacopter and octocopter with 6 or 8 rotors are most often used. The primary focus of this article is to compute the reliability of tethered HAPS by analyzing the effectiveness of their redundant rotor systems. To measure the performance of such systems, it is convenient to consider mathematical models as k-out-of-n models. Although Markov models have extensively been reported to analyze the reliability of repairable k-out-of-n models, this work introduces an alternative and more thorough methodology. In this work, a semi-Markov model (SMM) is proposed to calculate the probability of rotors being operational after the failure of some rotors in order to analyze system reliability. We emphasize that an SMM model is more appropriate as it provides a more accurate assessment of the probability of system failure over time through non-exponential sojourn time. Further, the efficacy of the proposed SMM is studied through the evaluation of steady-state availability, mean time to failure and reliability. Overall, the findings of this study enhance our comprehension of the reliability of repairable systems and extend the existing knowledge base of HAPS reliability analysis.

Implementing 6G via Non-Terrestrial Networks (NTN): Considerations for High Altitude Platform Stations (HAPS)

Implementing 6G via Non-Terrestrial Networks (NTN): Considerations for High Altitude Platform Stations (HAPS)

Fair resource optimization for cooperative non-terrestrial vehicular networks

Non-terrestrial networks aim to extend wireless communications capabilities beyond traditional terrestrial infrastructure by utilizing various platforms such as satellites, high-altitude platform stations (HAPS), and unmanned aerial vehicles to provide global or localized coverage. However, improving data rates in non-terrestrial cooperative communications (NTCC) networks presents unique challenges, necessitating innovative solutions. This paper presents a novel approach to enhance the request–response ratio (RRR) of NTCC in time asynchrony. By leveraging the advantages of HAPS, such as wide coverage, high altitude, and flexible deployment, we aim to optimize the performance of NTCC networks. We formulate an optimization problem considering the simultaneous connection between the HAPS and ground users, power distribution, and decoding order. The joint optimization problem is formulated as non-convex-non-linear and is also NP-hard, making it very challenging to obtain a globally optimal solution. To reduce the complexity of the problem and make it more tractable, we decouple it into subproblems and achieve an efficient solution in two steps. In the first step, we use the Gale–Shapley algorithm to solve the many-to-many two-sided matching problem of HAPS user terminal association, given the fixed decoding and power allocation. Then, we solve the decoding order and power allocation problem using the Dinkeback-like algorithm, given the optimal association in the second step. Our proposed method iteratively updates the preference lists, mitigating interference among HAPS and enhancing overall system performance. Through extensive simulations, we demonstrate that implementing our proposed schemes achieves high RRR compared to benchmark schemes. Additionally, when temporal asynchrony is employed alongside our approach, there is an increase in the overall performance obtained from the process.

Path planning of stratospheric airship in dynamic wind field based on deep reinforcement learning

The path planning of stratospheric airships holds significant potential for high altitude platform station applications. However, current research is confronted with certain limitations. On the one hand, the existing approaches are predominantly manual due to complex scenarios and numerous factors to consider, which are inefficient and lacks the ability to anticipate the dynamic wind field. On the other hand, the path planning approaches employed by other aircrafts rarely account for the dynamic wind field and energy cycle characteristics, rendering them unsuitable for airships. To address these challenges, this paper proposes a novel path planning approach based on deep reinforcement learning. Firstly, according to the characteristics of airship, the state space and the reward function are well-designed. Secondly, heterogeneous data, including dynamic wind field data and airship state features, are fused as state input for the model. Further, the dueling double deep recurrent Q network is used for path planning model. In contrast to the model employing a double deep recurrent Q network and heuristic algorithm, our proposed approach maintains higher energy and higher success rate, empowering airships to adeptly navigate emergencies.

Multiple HAPS-based space-air-ground network with FSO communication: a performance analysis.

Due to the fact that the existing generation of wireless communication cannot possibly keep up with the current traffic explosion and emerging applications, research and development on next-generation (i.e.,sixth generation, 6G) wireless technologies is being carried out worldwide. In this regard, it is anticipated that the space-air-ground (SAG) network with free space optics (FSO) communication can provide the terabits per second throughput necessary to sustain various potential 6G applications. However, FSO communications are susceptible to atmospheric turbulence, pointing errors, and beam scintillation effects. To remedy the severe atmospheric effects, we propose a multiple high-altitude platform station (HAPS)-based SAG network with a HAPS selection scheme. For the proposed system, we have derived the closed-form expressions for outage probability, average symbol error rate (SER), ergodic capacity, and outage capacity over Málaga distribution with pointing errors. Further, the asymptotic expressions for outage probability, average SER, and outage capacity were derived to enhance the comprehension of the system from a practical standpoint. It is observed from the numerical results that the multiple HAPS-based FSO system performs better than the existing HAPS-based FSO systems.

Energy Sustainability in Dense Radio Access Networks via High Altitude Platform Stations

Energy Sustainability in Dense Radio Access Networks via High Altitude Platform Stations

Hybrid FSO/RF Communications in Space–Air–Ground Integrated Networks: A Reduced Overhead Link Selection Policy

Space–air–ground integrated network (SAGIN) is considered an enabler for sixth-generation (6G) networks. By integrating terrestrial and non-terrestrial (satellite, aerial) networks, SAGIN seems to be a quite promising solution to provide reliable connectivity everywhere and all the time. Its availability can be further enhanced if hybrid free space optical (FSO)/radio frequency (RF) links are adopted. In this paper, the performance of a hybrid FSO/RF communication system operating in SAGIN has been analytically evaluated. In the considered system, a high-altitude platform station (HAPS) is used to forward the satellite signal to the ground station. Moreover, the FSO channel model assumed takes into account the turbulence, pointing errors, and path losses, while for the RF links, a relatively new composite fading model has been considered. In this context, a new link selection scheme has been proposed that is designed to reduced the signaling overhead required for the switching operations between the RF and FSO links. The analytical framework that has been developed is based on the Markov chain theory. Capitalizing on this framework, the performance of the system has been investigated using the criteria of outage probability and the average number of link estimations. The numerical results presented reveal that the new selection scheme offers a good compromise between performance and complexity.

FLSTRA: Federated Learning in Stratosphere

We propose a federated learning (FL) in stratosphere (FLSTRA) system,where a high altitude platformstation (HAPS) facilitates a large number of terrestrial clients to collaboratively learn a global model without sharing the training data. FLSTRA overcomes the challenges faced by FL in terrestrial networks, such as slow convergence and high communication delay due to limited client participation and multi-hop communications. HAPS leverages its altitude and size to allow the participation of more clients with line-of-sight (LOS) links and the placement of a powerful server. However, handling many clients at once introduces computing and transmission delays. Thus, we aim to obtain a delay-accuracy trade-off for FLSTRA. Specifically, we first develop a joint client selection and resource allocation algorithm for uplink and downlink to minimize the FL delay subject to the energy and quality-of-service (QoS) constraints. Second, we propose a communication and computation resource-aware (CCRA-FL) algorithmto achieve the target FL accuracy while deriving an upper bound for its convergence rate. The formulated problemis non-convex; thus, we propose an iterative algorithmto solve it. Simulation results demonstrate the effectiveness of the proposed FLSTRA system, compared to terrestrial benchmarks, in terms of FL delay and accuracy.

Reliability analysis of energy management subsystem in a high altitude platform station using hierarchical stochastic models and machine learning

Reliability analysis of energy management subsystem in a high altitude platform station using hierarchical stochastic models and machine learning

Handoff-Aware Distributed Computing in High Altitude Platform Station (HAPS)–Assisted Vehicular Networks

Distributed computing enables Internet of vehicle (IoV) services by collaboratively utilizing the computing resources from the network edge and the vehicles. However, the computing interruption issue caused by frequent edge network handoffs, and a severe shortage of computing resources are two problems in providing IoV services. High altitude platform station (HAPS) computing can be a promising addition to existing distributed computing frameworks because of its wide coverage and strong computational capabilities. In this regard, this paper proposes an adaptive scheme in a new distributed computing framework that involves HAPS computing to deal with the two problems of the IoV. Based on the diverse demands of vehicles, network dynamics, and the time-sensitivity of handoffs, the proposed scheme flexibly divides each task into three parts and assigns them to the vehicle, roadside units (RSUs), and a HAPS to perform synchronous computing. The scheme also constrains the computing of tasks at RSUs such that they are completed before handoffs to avoid the risk of computing interruptions. On this basis, we formulate a delay minimization problem that considers task-splitting ratio, transmit power, bandwidth allocation, and computing resource allocation. To solve the problem, variable replacement and successive convex approximation–based method are proposed. The simulation results show that this scheme not only avoids the negative effects caused by handoffs in a flexible manner, it also takes delay performance into account and maintains the delay stability.

Free Space Optical Communication: An Enabling Backhaul Technology for 6G Non-Terrestrial Networks

The deployment of non-terrestrial networks (NTNs) is envisioned to achieve global coverage for 6G and beyond. In addition to space nodes, aerial NTN nodes such as high-altitude platform stations (HAPSs) and rotary-wing unmanned aerial vehicles (UAVs) could be deployed, based on the intended coverage and operational altitude requirements. NTN nodes have the potential to support both wireless access and backhauling. While the onboard base station provides wireless access for the end users, the backhauling link connects the airborne/space-borne base station to the core network. With its high data transmission capability comparable to fiber optics and its ability to operate in the interference-free optical spectrum, free space optical (FSO) communication is ideally suited to backhauling requirements in NTNs. In this paper, we present a comprehensive tutorial on airborne FSO backhauling. We first delve into the fundamentals of FSO signal transmission and discuss aspects such as geometrical loss, atmospheric attenuation, turbulence-induced fading, and pointing errors, all of which are critical for determining received signal levels and related link budget calculations. Then, we discuss the requirements of airborne backhaul system architectures, based on use cases. While single-layer backhaul systems are sufficient for providing coverage in rural areas, multi-layer designs are typically required to establish connectivity in urban areas, where line of sight (LoS) links are harder to maintain. We review physical layer design principles for FSO-based airborne links, discussing both intensity modulation/direct detection (IM/DD) and coherent modulation/coherent demodulation (CM/CD). Another critical design criteria for airborne backhauling is self-sustainability, which is further discussed in our paper. We conclude the paper by discussing current challenges and future research directions. In this context, we discuss reconfigurable intelligent surfaces (RIS) and spatial division multiplexing (SDM), for improved performance and an extended transmission range. We emphasize the importance of advanced handover techniques and scalability issues for practical implementation. We also highlight the growing role of artificial intelligence/machine learning (AI/ML) and their potential applications in the design and optimization of future FSO-based NTNs.

Multimode High-Altitude Platform Stations for Next-Generation Wireless Networks: Selection Mechanism, Benefits, and Potential Challenges

Multimode High-Altitude Platform Stations for Next-Generation Wireless Networks: Selection Mechanism, Benefits, and Potential Challenges

Physical Layer Security of HAPS-Based Space–Air–Ground-Integrated Network With Hybrid FSO/RF Communication

In this paper, we study the physical layer security performance of a downlink space-air-ground integrated network (SAGIN), where a satellite communicates with the ground user/destination via a high-altitude platform station (HAPS)- based relay in the presence of an eavesdropper. In particular, we propose to use hybrid free space optical (FSO)/radio frequency (RF) transmission to enhance the security of the considered system. Herein, the FSO and RF links are assumed to experience Gamma-Gamma and Shadowed-Rician distributions, respectively. Specifically, we derive exact and asymptotic expressions of secrecy outage probability for the considered SAGIN by employing intensity modulation/direct detection. We provide the numerical and simulation results to validate our analysis.

Legal Issues Pertaining to High Altitude Platform Station Implementation in Indonesia as an Archipelagic State

Information is a necessity for the interests of government, the economy, social culture, as well as defense and security in the era of industrial revolution 4.0. Since 1976, the Indonesian government has been working on developing a satellite communication system starting with the Palapa A1 Satellite, followed by its subsequent generations. However, this system has limitations, particularly in providing coverage to rural areas in Indonesia. To address this issue, the government has started the procurement of the Wahana Dirgantara Super or High-Altitude Platform Station (HAPS) in Indonesia. HAPS are stations positioned at altitudes of 20 to 50 km above the Earth's surface. Given Indonesia's geographical location, HAPS is seen as the most suitable solution as it utilizes non-ground terrestrial technology to improve information and communication technology coverage in rural areas. However, the location on which the HAPS is positioned might trigger new issues, particularly with regard to state sovereignty and disruption of flight traffic. The operation of HAPS also needs further consideration so that the protection of personal data in Indonesia will not be disrupted. This article employs normative juridical research as a methodology. The research collected and analyzed primary sources in the form of law, regulation, and policy at the national and regional levels, as well as secondary sources that are available in textbooks, journal articles, and website content. This article aims to explain the development of HAPS regulations based on international law and national law and to examine the legal issues related to the procurement of HAPS in Indonesia . At the end, this article suggests that it is necessary to regulate HAPS in Indonesia with reference to aviation safety, security, and liability issues as well as maintaining state sovereignty and ensuring personal data protection.

Sustaining Dynamic Traffic in Dense Urban Areas with High Altitude Platform Stations (HAPS)

Sustaining Dynamic Traffic in Dense Urban Areas with High Altitude Platform Stations (HAPS)

Trajectory Optimization for FSO Based U-IoT Backhaul Networks

Considering many advancements in aerial platform technology, aerial backhaul networks (ABNs) are expected to play a big role in 6th generation (6G) mobile systems. Considering the significant demand in capacity of Internet of Things (IoT) networks, ABNs using free space optical (FSO) signals are receiving attention as an alternative to using traditional radio frequency (RF) signals. However, FSO based ABNs face the challenge of needing to avoid obstacles (e.g., clouds) in the vertical channel to maintain line-of-sight (LoS) between the ground terminals (GTs) and the unmanned aerial vehicle (UAV) based high-altitude platform stations (HAPSs). Therefore, in this paper, a trajectory optimized FSO based UAV-IoT (U-IoT) backhaul network (TOFU) scheme that minimizes the end-to-end outage probability is proposed. Considering moving clouds and obstacles, the TOFU scheme identifies the changing LoS area and applies gradient descent based on optimized control of the HAP and relay UAVs to minimize the end-to-end outage probability. Simulation experiments were conducted to include various cloud properties and orientations, where the results show that the TOFU scheme can provide significant improvements in the end-to-end outage probability and throughput compared to other benchmarked schemes.

Resource-Efficient HAPS-RIS Enabled Beyond-Cell Communications

In the future, urban regions will encounter a massive number of capacity-hungry devices. Relying solely on terrestrial networks for serving all UEs will be a cost-ineffective approach. Consequently, with the anticipated supply and demand mismatch, several UEs will be unsupported. To offer service to the left-out UEs, we employ an energy-efficient and cost-effective beyond-cell communications approach, which uses reconfigurable intelligent surfaces (RIS) on a high-altitude platform station (HAPS). Particularly, unsupported UEs will be connected to a dedicated control station (CS) through RIS-mounted HAPS. A novel resource-efficient optimization problem is formulated that maximizes the number of connected UEs, while minimizing the total power consumed by the CS and RIS. Since the resulting problem is a mixed-integer nonlinear program (MINLP), a low-complexity two-stage algorithm is developed. Numerical results demonstrate that the proposed algorithm outperforms the benchmark approach in terms of the percentage of connected UEs and the resource-efficiency (RE). Also, the results show that the number of connected UEs is more sensitive to transmit power at the CS than the HAPS size.

Design and Evaluation on Onboard Antenna Pointing Control System for a Wireless Relay System Using Fixed-Wing UAV

Among several usages of unmanned aerial vehicles (UAV), wireless relay systems for high altitudes using fixed-wing UAVs, or high-altitude platform stations (HAPS), are some of the most promising applications. To realize the systems by making the most of advantages of the long flight duration and endurance of fixed-wing airplanes, this paper proposes an antenna pointing control system using mechanical gimbals onboard a fixed-wing UAV continuously turning midair and describes results of the blocking analysis of the antenna driving angles of the gimbal directed to a ground station, the design of the antenna pointing control system, and the evaluation of its performance. It is confirmed by the evaluation that, though the antenna pointing control accuracy is greatly influenced by the noisy antenna pointing direction command, its accuracy is greatly improved by using the highly accurate RF sensor to detect antenna pointing direction.