High Altitude Platform Research Articles

Evaluation of landing procedures for a high-altitude platform with skid-type landing gear based on pilot-in-the-loop simulations

AbstractIn the context of the project HAP, the German Aerospace Center (DLR) is currently developing a solar-powered high-altitude platform. The underlying vehicle is a fixed-wing aircraft that is supposed to be stationed in the stratosphere for 30 days. Due to, among others, low achievable rates of descent, the use of skids as landing gear and its high susceptibility to wind, landing this aircraft is a very challenging task. Hence, it requires a landing procedure specifically tailored to the aircraft’s particularities. Furthermore, this procedure needs to be easy to follow by pilots especially in adverse atmospheric conditions. This paper deals with a pilot-in-the-loop simulation campaign conducted to assess a landing procedure developed for the high-altitude platform in earlier works. Within this campaign, the pilots are supposed to land the aircraft following this developed procedure in atmospheric turbulence conditions. In addition, they also land the aircraft following a second procedure, which is based on a conventional landing. In doing so, the altitude at which a flare is performed and/or the propellers are shut down is varied. Finally, the novel procedure’s overall feasibility from a piloting point of view and its potential to reduce the risks during landing are assessed. The results show that the procedure proves to reduce the risk of inadvertent ground contact of the aircraft payload compartment, which is associated with serious damage to aircraft structure and payload. However, since the novel procedure is challenging for the pilots, some improvements to the procedure are proposed.

Developed Internet of Vehicles Architecture: Communication, Big Data and Route Determination Perspectives

Internet of vehicles (IoV) has become an important research topic due to its direct effect on intelligent transportation systems (ITS) development. There are many challenges in the IoV environment, such as communication, big data and best route assigning. In this paper, an effective IoV architecture is proposed. This architecture has four main objectives. The first objective is to utilize a powerful communication scheme in which three tiers of coverage tools — Internet, satellite, high-altitude platform (HAP) — are utilized. Therefore, the vehicles maintain a continuous connection to the IoV environment everywhere. The second objective is to apply filtering and prioritization mechanisms to reduce the detrimental effects of IoV big data. The third objective is to assign the best route for a vehicle after determining its real-time priority. The fourth objective is to analyze the IoV data. The proposed architecture performance is measured using a simulation environment that is created by the NS-3 package. The simulation results proved that the proposed IoV architecture has a positive impact on the IoV environment according to the performance metrics: energy, success rate of route assignment, filtering effect, data loss, delay, usage of coverage tools and throughput.

Utility optimization for computation offloading and splitting in time-varying HAP and LEO satellite integrated MEC networks

To provide ubiquitous and low-latency communication and computation services for remote and disaster areas, high altitude platform (HAP) and low earth orbit (LEO) satellite integrated multi-access edge computing (HLS-MEC) networks have emerged as a promising solution. However, most current studies directly assume that the number of connected satellites is fixed and neglect the modeling of the time-varying multi-satellite computing process. Motivated by this, we establish an M/G/K(t) queuing model to illustrate task computation on satellites. To evaluate the efficiency and quality of computation offloading and splitting, we develop a utility model. This model is defined as a difference between a value function that assesses the trade-offs of task offloading, considering latency reductions and energy savings, and a cost function that quantifies expenses related to latency and energy consumption. After formulating the utility maximization problem, we propose the deep reinforcement learning-based offloading and splitting (DBOS) scheme that can overcome the time-varying uncertainties and high dynamics in the HLS-MEC network. Specifically, the DBOS scheme can learn the best computation offloading and splitting policy to maximize the utility by sensing the number of connected satellites, the distance between the HAP and satellites, the available computing resources, and the task arrival rate. Finally, we evaluate and validate the computational complexity and convergence property of the DBOS scheme. Numerical results show that the DBOS scheme outperforms the other three benchmarks and maximizes the utility under time-varying dynamics.

MDM‐Incorporated Quad Donut Modes OCDMA‐FSO Scheme for Secure High‐Altitude Platforms‐To‐Satellite Scenarios

ABSTRACTThe next generation of communication networks is envisioned to be driven by high‐altitude platform (HAP)‐to‐satellite systems. License‐free narrow beam free space optics (FSO) can provide uninterrupted connectivity in satellite‐enabled Internet of Things scenarios. This work proposes a HAP‐to‐satellite hybrid mode division multiplexing–optical code division multiple access (MDM‐OCDMA) scheme employing zero cross‐correlation (ZCC) and multidiagonal (MD) codes. In high‐speed satellite communications, a 12 × 10‐Gbps hybrid MDM‐OCDMA scheme carrying four donut modes (0, 1, 2, and 3) enables high channel capacity, sufficient spectral efficiency, and data security under severe link conditions. Based on simulations, the hybrid MDM‐OCDMA scheme using the ZCC code achieves a greater FSO link distance of 420 m compared with when using the MD code at a 10e‐9 error correction limit under clear air and weak turbulent scenario. The reliable transmission distance of 250 m is achievable with the 120‐Gbps proposed system, assuming pointing errors of 2 mrad, 1‐dB receiver, and 2.5‐dB transmitter losses. The results also show that the system can sustain an additional loss of 1.5–2 dB over 250 m for all donut modes. Additionally, the system using ZCC code contributes to low power consumption over MD and variable weight ZCC code and thus requires a minimum received power of −4.02 dBm. It also offers high optical signal to noise of 42–52 dB, −11.58 to −22.20 dB of gain, 11.58–22.20 dB of noise figure, and −48.11 to −58.73 dBm of signal power at output over 200–700 m range up to 2 dB of additional loss. Comparative analysis indicates that the proposed system is more efficient, less complex, adequately distance‐friendly (=420 m), and capable of higher data rates (=120 Gbps) compared with other works. This makes it a promising solution for future high‐speed satellite communications considering the impact of link losses and atmospheric conditions.

Regulatory and spectrum policy challenges for combined airspace and non-terrestrial networks

The recent advancements in the aviation and space industries facilitate new types of users in the sky, e.g., electrical vertical take-off and landing (eVTOL) aircraft. To unlock the full potential of these innovations, it is crucial to create interconnected three-dimensional networks that integrate airspace and non-terrestrial networks (NTNs) with their terrestrial counterparts, also known as Combined Airspace and Non-Terrestrial Networks (ASN). Combined ASN needs a flexible and adaptive network architecture with multiple, and partly converging technologies, such as air-to-ground, satellite, and high-altitude platforms, with a focus to cover both ground and aerial users. In addition to technical challenges, spectrum policy and regulatory aspects will affect the wireless network design and management schemes in three-dimensional space. Hence, this paper introduces regulatory and spectrum policy challenges posed by the development of combined ASN. This paper investigates a hypothetical urban air mobility use case with an eVTOL aircraft that operates as a flying taxi.

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.

HAC-SAGIN: High-altitude computing enabled space-air-ground integrated networks for 6G

The space–air–ground integrated networks (SAGINs) provide a new paradigm for the evolution of the Internet of Things (IoT) networks by enhancing coverage and deploying computing resources near IoT devices, especially in emergency situations and disaster-hit regions. In the context of the IoT networks, aerial platforms such as unmanned aerial vehicles (UAVs) and high-altitude platforms (HAPs) present in the air layer of SAGINs with access and aerial computing (AC) capabilities have the potential to significantly expand coverage, enhance performance, reduce delay and handle complex computation tasks for IoT devices. Seeking the stated prospect, we propose a high-altitude computing (HAC)-enabled SAGIN leveraging millimeter waves (mmWave) frequency range in which the IoT devices are provided access services by low-earth orbit satellites (LEO-SATs) and HAPs while the HAPs offer AC facility as well. Non-orthogonal multiple access (NOMA) is used as a multiple access scheme with different clustering mechanisms in uplink (UL) and downlink (DL) communication. We aim to establish high-rate data transmission in DL along with minimizing the execution time of IoT devices offloading their data to the HAPs in UL communication. The mmWaves range is targeted to have high-rate data transmissions and NOMA implementation further enhances the bandwidth available for an individual IoT device. For efficient offloading in UL communication, we formulate an optimization problem aiming to minimize the execution time by using the Lagrangian function-based approach. Execution time is minimized by reducing the transmission and computation time, which is attained by the optimization of allocated power and computation resources. Simulation results demonstrate that the proposed HAC-SAGIN is able to establish high-rate transmissions in DL and exhibits a significant decrease in execution time in UL in contrast to the no optimization case. Optimum power assignment improves the achievable rate, leading to reduced transmission time, while optimum core assignment efficiently reduces the computation time. In addition, the offloaded data size-driven NOMA implementation in UL prominently improves the system effective throughput.

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

Design of Anti-Eccentric Load Sensor for Engineering Operation Early Warning Based on Particle Swarm Optimization.

The accuracy of aerial work platform weighing is essential for safety. However, in practice, the same weight placed at different locations on the platform can yield varying readings, which is a phenomenon known as eccentric load. Measurement errors caused by eccentric loads can lead to missed detections and false alarms in the vehicle safety system, seriously affecting the safety of aerial work. To overcome the influence of eccentric load, the current engineering practice relies on multiple measurements at multiple points and averaging the results to eliminate the eccentric load, which greatly increases the work intensity of workers. To address the aforementioned issues, this paper proposes a three-dimensional force/torque shear force compensation scheme based on bending torque and torsional torque for pressure. The goal is to ensure that the sensor on the aerial work vehicle platform can accurately measure the anti-eccentric load under single-point measurement conditions. A three-box structure anti-eccentric load-weighing sensor for the aerial work platform was designed. Its structure has the advantages of high mechanical strength and no radial effect, ensuring the safety of aerial work, improvement of measurement sensitivity, and enabling of real-time and accurate acquisition of force/torque in three directions. In order to further improve the measurement accuracy of 3D force/torque compensation, a particle swarm optimization algorithm was adopted to optimize the 3D force/torque shear force compensation, thereby improving the safety of engineering operations. Through the verification of a self-made testing platform, the anti-eccentric load sensor designed in this study can ensure that the measurement error of objects at any position on the platform is less than 1.5%, effectively improving the safety of high-altitude platform engineering operations.

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.

Enhanced Non-Orthogonal Multiple Access Performance Using Channel Coding for High-Altitude Platform System (HAPS)

The high-altitude platform system (HAPS) is a promising technology for providing high-speed data transmission and coverage for remote areas. Still, it suffers from unpredictable channel transmission, especially in the Rician channel. To overcome the issue in transmission, we used one channel coding strategy, namely the quasi-cyclic low-density parity-check (QC-LDPC). This study aims to evaluate the performance of power domain non-orthogonal multiple access (PD-NOMA), which allows multiple users to share the same spectrum in a downlink communication system from HAPS to three ground stations. We simulated the system using MATLAB simulation with different power allocation coefficients for every ground station. The simulation results showed that QC-LDPC codes can significantly lower the signal-to-noise ratio (SNR) required to achieve the same bit error rate (BER) as uncoded NOMA, especially in scenarios with uneven power allocation. The average improvement of QC-LDPC over uncoded NOMA was 8.4% in SNR. However, we also observed that NOMA is prone to domino errors, where decoding errors in one ground station can propagate and degrade the performance of the subsequent ground station. Furthermore, we found that power allocation significantly impacts the system performance, while the location and power allocation of the second ground station have a minor effect. Based on these findings, we conclude that QC-LDPC can enhance system performance in scenarios with low received power and that power allocation is a crucial factor for NOMA systems with multiple ground stations.

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)

Air computing: A survey on a new generation computation paradigm

There is an ever-growing race between what novel applications demand from the infrastructure and what the continuous technological breakthroughs bring in. Especially after the proliferation of smart devices and diverse IoT requirements, we observe the dominance of cutting-edge applications with ever-increased user expectations in terms of mobility, pervasiveness, and real-time response. Over the years, to meet the requirements of those applications, cloud computing provides the necessary capacity for computation, while edge computing ensures low latency. However, these two essential solutions would be insufficient for next-generation applications since computational and communicational bottlenecks are inevitable due to the highly dynamic load. On the other hand, inadequate infrastructure considering rural areas and disaster sites makes the utilization of those solutions difficult. Therefore, a 3D networking structure using different air layers including Low Altitude Platforms, High Altitude Platforms, and Low Earth Orbits in a harmonized manner for both urban and rural areas should be applied to satisfy the requirements of the dynamic environment. In this perspective, we put forward a novel, next-generation paradigm called Air Computing that presents a dynamic, responsive, and high-resolution computation environment for all spectrum of applications. In this survey, we define the components of air computing, investigate its architecture in detail, and discuss its essential use cases and the advantages it brings for next-generation application scenarios. We provide a detailed and technical overview of the benefits and challenges of air computing as a novel paradigm and spot the important future research directions.

Outage probability minimization by optimal beamwidth selection for UAV-to-HAP FSO links under pointing inaccuracies

The design of a free-space optical (FSO) link between an unmanned aerial vehicle (UAV) and a high-altitude platform (HAP) in the practical scenario of generalized pointing errors (PE) and beam wandering (BWAN) is addressed. We propose to select appropriately the system parameters such as optical beamwidth at the UAV and its flight altitude so as to minimize the outage probability. First, we characterize the channel statistics by taking into account the joint influence of attenuation loss, weak atmospheric turbulence and generalized PE particularly impaired by BWAN. Second, we formulate the closed-form expressions for outage probability, where we also derive an asymptotic expression at high signal-to-noise ratios (SNR)s. Third, we derive the optimum beamwidth at the UAV leading to the instantaneous minimum outage probability under generalized PE and BWAN. Finally, we address the optimal flight altitude of the UAV to avoid strong turbulence in order to ensure efficient data transmission. Our simulation results validate both the effectiveness and the accuracy of the derived asymptotic outage probability and the adequate choice of beamwidth and flight altitude to minimize the average outage performance. For instance, our results show that at an SNR of 20 dBm, the link availability is increased from 20% (with nominal beamwidth) to more than 70% by adopting the proposed beamwidth optimization.

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.

Impact of visibility limiting conditions on satellite and high-altitude platform quantum key distribution links

Satellite and aerial platforms are critical in the deployment of global quantum communications networks. Currently, there remain significant challenges including operation during daytime and robustness to visibility limiting conditions. In this work we investigate, through simulation, the impact of visibility limiting conditions on low-Earth orbit CubeSat dimensioned satellites, small satellites and high-altitude platform implementations. Three different operational wavelengths were considered: currently used near-infrared (at 850 nm); next-generation short-wave infrared (at 1550 nm); and a candidate longer wavelength (at 2133 nm). We present channel attenuation and consider quantum key distribution (QKD) system performance parameters. Results indicate that the “best wavelength” for an implementation depends on the minimum visibility rated and the single-photon detector technology utilized. In the cases where tolerated meteorological visibility is short, 1550 nm and 2133 nm wavelengths provide better performance. In cases when the visibility is long, the operational wavelength of 850 nm provides better QKD system performance.

Fly-around-the-World Near-Space Picosatellite for Cost-Effective School Space Projects

This research presents the design and development of a near-space picosatellite platform intended to operate at high altitudes between 20–40 km above sea level. These picosatellites function similarly to orbital satellites but float and travel with the wind in the atmosphere instead of orbiting the Earth. The platform utilizes a super-pressure balloon to provide buoyancy, allowing the picosatellite to remain airborne and operational for several days to months, capable of flying around the world multiple times. This study focuses on the cost-effective design of high-altitude platforms, telecommunication systems, and energy consumption for the picosatellite, enabling it to communicate with ground stations from anywhere in the world while consuming low power. The use of common COTS (Commercial Off-The-Shelf) equipment aims to enhance accessibility for educational applications. This research gathered data from our previous studies for over 20 high-altitude platform flights, analyzed the necessary factors for whole system design, and developed a new prototype that has been successfully built and tested.

Intelligent Online Offloading and Resource Allocation for HAP Drones and Satellite Collaborative Networks

High-altitude platform (HAP) drones and satellites collaborate to form a network that provides edge computing services to terrestrial internet of things (IoT) devices, which is considered a promising method. In this network, IoT devices’ tasks can be split into multiple parts and processed by servers at non-terrestrial nodes in different locations, thereby reducing task processing delays. However, splitting tasks and allocating communication and computing resources are important challenges. In this paper, we investigate the task offloading and resource allocation problem in multi-HAP drones and multi-satellite collaborative networks. In particular, we formulate a task splitting and communication and computing resource optimization problem to minimize the total delay of all IoT devices’ tasks. To solve this problem, we first transform and decompose the original problem into two subproblems. We design a task splitting optimization algorithm based on deep reinforcement learning, which can achieve online task offloading decision-making. This algorithm structurally designs the actor network to ensure that output actions are always valid. Furthermore, we utilize convex optimization methods to optimize the resource allocation subproblem. The simulation results show that our algorithm can effectively converge and significantly reduce the total task processing delay when compared with other baseline algorithms.

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.

Distributed HAPS-assisted communications in FSO/RF space-air-ground integrated networks

Space-air-ground integrated (SAGI) communication networks have been envisioned as one of the pillars of the next generation communications (6 G). This type of networks are expected to offer fairness and high quality of services in various scenarios where traditional terrestrial communication systems cannot efficiently support due to inherent limitations, e.g., limited coverage areas. In this paper, a distributed transmission scheme is proposed in a SAGI communication network that utilizes free-space-optical (FSO)/radio frequency (RF) links. More specifically, a set of N high altitude platform systems are cooperatively transmit the received signal to the ground station, using the decode-and-forward relaying protocol. For this system, generic analytical expressions for the outage probability (OP) have been derived that take into consideration the impact of turbulence, pointing errors, and atmospheric attenuation (for the FSO links) as well as the impact of composite fading (for the RF links). Moreover, asymptotic closed-form expressions for the OP are also presented, which are used to extract useful insights for the system under consideration. The numerical evaluated results that are illustrated reveal the impact of various system and channel models parameters on the system’s performance. From these results, it is shown that the proposed scheme outperforms a pure FSO-based relaying scheme, which has been used as a benchmark, under different environmental conditions.