Airborne Networks Research Articles

An optimized multi-layer ensemble model for airborne networks intrusion detection

In view of the characteristics of airborne networks, such as the traffic data of 1553B data bus and public networks, numerous redundant and irrelevant data, and fewer but more types of attack behaviors, a highly representative balanced data subset is generated by combining K-means with synthetic minority oversampling technique (SMOTE). A feature selection (FS) method of fast correlation-based filter combined with information gain (IG-FCBF) is proposed to filter the key characteristics with 90 % cumulative importance. Aiming at the problem that it is not easy for a single classifier to accurately classify various types of attacks, as well as the difficulty in obtaining the best prediction results by adjusting default and manual parameters, a multi-layer ensemble model based on Bayesian optimization tree-structured Parzen estimator (BO-TPE) is proposed for airborne networks intrusion detection, combining the advantages of supervised learning, stacking ensemble method and hyperparameter optimization (HPO). The experimental results show the superiority and effectiveness of the model, as well as its universality in Integrated Avionics Systems (IAS) and onboard public networks, which provides a new approach for airborne networks intrusion identification and protection.

Formal verification of timely knowledge propagation in airborne networks

Ensuring timely coordination between autonomous aircraft is a challenging problem in decentralized air traffic management (ATM) applications for urban air mobility (UAM) scenarios. This paper presents an approach for formally guaranteeing timely progress in a Two-Phase Acknowledge distributed knowledge propagation protocol by probabilistically modeling the delays using the theory of the Multicopy Two-Hop Relay protocol and the M/M/1 queue system. The guarantee states a probabilistic upper bound to the time for progress as a function of the probabilities of the total transmission and processing delays following two specific distributions. The proof uses a general library of formal theories, that can be used for the rigorous mechanical verification of autonomous aircraft coordination protocols using the Athena proof checker and assistant.

Directional Antenna-Based Routing Protocol With Low Detection Probability in Airborne Networks

Directional Antenna-Based Routing Protocol With Low Detection Probability in Airborne Networks

A Deep-Learning Approach to a Volumetric Radio Environment Map Construction for UAV-Assisted Networks

Providing global coverage for ubiquitous users is a key requirement of the fifth generation (5G) and beyond wireless technologies. This can be achieved by integrating airborne networks, such as unmanned aerial vehicles (UAVs) and satellite networks, with terrestrial networks. However, the deployment of airborne networks in a three-dimensional (3D) or volumetric space requires a new understanding of the propagation channel and its losses in both the areal and altitude dimensions. Despite significant research on radio environment map (REM) construction, much of it has been limited to two-dimensional (2D) contexts. This neglects the altitude-related characteristics of electromagnetic wave propagation and confines REMs to 2D formats, which limits the comprehensive and continuous visualization of propagation environment variation in spatial dimensions. This paper proposes a volumetric REM (VREM) construction approach to compute 3D propagation losses. The proposed approach addresses the limitations of existing approaches by learning the spatial correlation of wireless propagation channel characteristics and visualizing REM in areal and height/altitude dimensions using deep learning models. Specifically, the approach uses two deep learning-based models: volume-to-volume (Vol2Vol) VREM with 3D-generative adversarial networks and sliced VREM with altitude-aware spider-UNets. In both cases, knowledge of the propagation environment and transmitter locations in 3D space is used to capture the spatial and altitude dependency of the propagation channel’s characteristics. We developed the Addis dataset, a large REM dataset comprising 54,000 samples collected from the urban part of Addis Ababa, Ethiopia, to train the proposed models. Each sample of data comprises a 512-meter by 512-meter areal resolution with different 3D obstacles (buildings and terrain), 15 simulated propagation loss maps at every 3-meter altitude resolution, and 80 different 3D transmitter locations. The results of the training and testing of the proposed models reveal that the constructed VREMs are statistically comparable. In particular, the Vol2Vol approach has a minimum L1 loss of 0.01, which further decreases to 0.0084 as the line-of-sight (LoS) probability increases to 0.95.

Integrated sensing and communication-assisted beam rendezvous in airborne networks

This paper investigates the feasibility of the integrated sensing and communication (ISAC) technology in the future airborne network (AN), a large heterogeneous network of various aircraft to realize situation awareness and sharing. In order to achieve better transmissions with few overheads, an effective beam rendezvous scheme is fundamental. However, due to the nodes’ oblivious movements in AN, the conventional beam training methods may lead to significant overheads and latencies. Motivated by this, we develop a novel fast beam prediction scheme for communication in AN with sensing assistance to improve the sum-rates while satisfying the sensing requirements simultaneously. This paper introduces our vision of the ISAC-enabled AN and provides the signal models in the considered AN based on ISAC technology. Then, we propose a 3D beam prediction scheme that helps both sides to formulate the aligned beams utilizing the angular prediction results, without the heavy beam training processes to reduce the overheads. Numerical results demonstrate that the proposed scheme can achieve high-data-rate transmission while guaranteeing the sensing performance with lower complexity and link overheads.

Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS

Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS

Optimal deployment strategy of airships for near‐space communication system using multiobjective advanced evolutionary algorithm

SummaryThis paper presents a near‐space communication system (NSCS) using advanced deployment strategies to gain high throughput. The airships are deployed according to the user's location, assuming robust backbone network characteristics such as signal path loss, fading factor, routing efficiency, and safety issues among bi‐connected airships. Due to the independent flying nature of airships, it is very attractive to deploy them as aerial base stations and construct airborne networks to provide service for on‐ground users. However, it is quite challenging to optimally deploy multiple airships for on‐demand coverage while maintaining the connectivity among airships. A balance between the network parameters, i.e., capacity and coverage area, should be maintained for optimal deployment of the airships. We have derived the maximum throughput of NSCS, including system parameters, as a multiobjective optimization problem subjected to efficient routing protocol and safety constraints. A decomposition‐based advanced multiobjective evolutionary algorithm (AMOEA/D) is adopted to solve the deployment optimization problem. The proposed algorithm is motivated by the non‐dominated solutions that maintain population diversity over the variable space. Two designed test problems, that is, the L‐shaped hotspot problem and nine hotspot problems, are also investigated. Numerical results show that the proposed method improves the system performance compared with benchmark external archive‐guided MOEA/D (EGA‐MOEA/D) and non‐dominated sorted genetic algorithms (NSGA‐II) by 10.46% and 3.84%, respectively.

Oceania’s 5G Multi-Tier Fixed Wireless Access Link’s Long-Term Resilience and Feasibility Analysis

Information and communications technologies play a vital role in achieving the Sustainable Development Goals (SDGs) and bridging the gap between developed and developing countries. However, various socioeconomic factors adversely impact the deployment of digital infrastructure, such as 5G networks, in the countries of Oceania. The high-speed broadband fifth-generation cellular network (5G) will improve the quality of service for growing mobile users and the massive Internet of Things (IoT). It will also provide ultra-low-latency services required by smart city applications. This study investigates the planning process for a 5G radio access network incorporating sub-6 GHz macro-remote radio units (MRRUs) and mmWave micro-remote radio units (mRRUs). We carefully define an optimization problem for 5G network planning, considering the characteristics of urban macro-cells (UMa) and urban micro-cells (UMi) with appropriate channel models and link budgets. We determine the minimum number of MRRUs and mRRUs that can be installed in each area while meeting coverage and user traffic requirements. This will ensure adequate broadband low-latency network coverage with micro-cells instead of macro-cells. This study evaluates the technical feasibility analysis of combining terrestrial and airborne networks to provide 5G coverage in Oceania, with a special emphasis on Fiji.

A constructive airborne‐ground matrix algorithm for modern telecommunication systems

AbstractConventional Mobile Communication Systems (MCS) reliably transfer critical messages from authorised remote information sources like military bases and ground control stations in the war field. As tactical advancement grows rapidly, the challenges of transmitting tactical messages via conventional satellite methods increase the processing overhead related to cost, Line of Sight (LOS) communication, packet loss, delay, and retransmission requests. Modern mobile communication systems use Airborne Node Networks (ANN) between satellites and Mobile Ground Nodes (MGNs) as they provide many advantages in mobile communication systems. Hence airborne network reduces the burden of satellites as they are only used as relay stations. The mobility problem caused by ANN and MGNs is solved by proposing a novel constructive airborne‐ground matrix algorithm known as the Who‐To‐Whom (WTW) matrix. With the help of this matrix acting as a reference index, it determines which nodes relate to whom at every time interval T in the tactical environment. This WTW matrix holds precise status/information about connectivity among all stakeholders in the operating environment by carefully and effectively accounting for frequent location changes. The methodology of the proposed matrix is that it contains the physical parameters of the nodes and their behaviour in the tactical environment. The WTW matrix construction algorithm discusses how the reference matrix is constructed in every aerial node to monitor the mobile ground nodes by leading them to safety and providing aerial guidance as they move along the tactical environment. The performance metrics are measured with other existing schemes, and the merits and demerits of the proposed WTW matrix are identified and discussed in detail.

Quantum Key Distribution for V2I communications with software‐defined networking

AbstractThe evolution of Connected and Autonomous Vehicles (CAVs) promises improvements in our travel experience and the potential to enhance road safety and reduce environmental impact. This will be utilising highly diverse traffic environments that enable several advanced mobility applications. A secure, efficient, reliable, and resilient communications infrastructure is required to support developments in these CAV systems. Next generation of telecommunication networks will seamlessly integrate terrestrial, satellite, and airborne networks into a single wireless system satisfying the requirements of trustworthy future transport systems. Given the increasing importance of CAVs, coupled with their attractiveness as a cyber‐attack for threat agents (e.g., disruption of transportation systems by nation states), security is paramount. Future communications systems offer an opportunity to integrate Quantum Key Distribution (QKD) into vehicular environments, protecting against advances in quantum computation that render many of the classical algorithms that underpin Public Key Infrastructure obsolete. This paper proposes a method for the integration of QKD in V2I networks to enable secure data communication. Quantum Key Distribution is used in the end‐to‐end path of vehicle‐to‐infrastructure (V2I) networks. Furthermore, an overarching Software‐Defined Network, with integrated QKD, is introduced. We have investigated the security performance of QKD in a V2I network over an urban environment.

Ultra-Reliable Device-Centric Uplink Communications in Airborne Networks: A Spatiotemporal Analysis

This paper proposes an ultra-reliable device-centric uplink (URDC-UL) communication scheme for airborne networks. In particular, base stations (BSs) are mounted on unmanned aerial vehicles (UAVs) that travel to schedule UL transmissions and collect data from devices. To attain an ultra-reliable unified device-centric performance, the UL connection is established when the UAV-BS is hovering at the nearest possible distance from the scheduled device. The performance of the proposed URDC-UL scheme is benchmarked against a stationary UAV-centric uplink (SUC-UL) scheme where the devices are scheduled to communicate to UAV-BSs that are continuously hovering at static locations. Utilizing stochastic geometry and queueing theory, novel spatiotemporal mathematical models are developed, which account for the UAV-BS spatial densities, mobility, altitude, antenna directivity, ground-to-air channel, and temporal traffic, among other factors. The results demonstrate the sensitivity of the URDC-UL scheme to the ratio between hovering and traveling time. In particular, the hovering to traveling time ratio should be carefully adjusted to maximize the harvested performance gains for the URDC-UL scheme in terms of link reliability, transmission rate, energy efficiency, and delay. Exploiting the URDC-UL scheme allows IoT devices to minimize transmission power while maintaining unified reliable transmission. This preserves the device's battery and addresses a critical IoT design challenge.

Intelligent Terahertz Medium Access Control (MAC) for Highly Dynamic Airborne Networks

The Terahertz (THz) link provides over 100 Gbps of data transmission rate. However, it is extremely vulnerable to obstacles and requires very narrow (highly directional) beams for highly focused energy radiation. The main task of THz medium access control (MAC) protocol is not channel access collision avoidance; instead, it is to coordinate all the one-hop neighbors for scheduled, antenna-aligned line-of-sight communications. This study aims to build an intelligent MAC scheme for highly mobile Terahertz airborne networks (TANs). Our TAN MAC design has three features as follows: (1) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Spatio-temporal TAN state learning:</i> We will build a predictive network state estimation model through deep learning and generative adversarial network (GAN). Based on the predicted node/link status, all the one-hop neighbors can prepare well for the antenna alignment and THz channel scheduling. (2) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Accurate, two-level MAC operation control:</i> we propose to use nested deep reinforcement learning (DRL) with outer/inner policy loops for high-/low-level action determination: The outer loop determines the high-level, coarse actions (such as antenna codebook selection); the inner loop determines the low-level, fine actions (such as individual beam control) under the selected high-level action. (3) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TAN-specific, comprehensive MAC behavior control:</i> Based on the above deep neighbor adaptation (DNA) model, we design a complete TAN MAC protocol that considers the routing context and dynamic network topology. Our simulations demonstrate the smooth, high-rate THz communications in MAC layer with resilient RF links under high node mobility.

Resource allocation for dataflow applications in FANETs using anypath routing

Management of network resources in advanced IoT applications is a challenging topic due to their distributed nature from the Edge to the Cloud, and the heavy demand of real-time data from many sources to take action in the deployment. FANETs (Flying Ad-hoc Networks) are a clear example of heterogeneous multi-modal use cases, which require strict quality in the network communications, as well as the coordination of the computing capabilities, in order to operate correctly the final service. In this paper, we present a Virtual Network Embedding (VNE) framework designed for the allocation of dataflow applications, composed of nano-services that produce or consume data, in a wireless infrastructure, such as an airborne network. To address the problem, an anypath-based heuristic algorithm that considers the quality demand of the communication between nano-services is proposed, coined as Quality-Revenue Paired Anypath Dataflow VNE (QRPAD-VNE). We also provide a simulation environment for the evaluation of its performance according to the virtual network (VN) request load in the system. Finally, we show the suitability of a multi-parameter framework in conjunction with anypath routing in order to have better performance results that guarantee minimum quality in the wireless communications.

Modeling air-to-air communication networks in the North Atlantic region

The North Atlantic is one of the world’s airspaces accommodating a very high aircraft density while at the same time no radio coverage or radar surveillance is available. Beside satellite communication, one approach to enable data communication between aircraft and ground in the North Atlantic region is to establish ad-hoc networks build up by direct data links between the aircraft that are acting as communication nodes. In this paper we, therefore, present a modeling approach to model air traffic and ad-hoc networks in the North Atlantic region using up-to-date flight plans and trajectory modeling techniques and to assess the connectivity provided by such networks. Assuming an applicable set of ground stations that provide data transfer to and from this airborne network, we assess the connectivity by time-series analysis and in total for a set of different fractions of all aircraft assumed to be equipped with the necessary systems as well as for a variation of the air-to-air communication range. In addition, we present average link durations, average amounts of hops to reach ground and numbers of connected aircraft for the different scenarios and identify general relations between the different factors and metrics. We will show, that communication range and equipage fraction significantly influence the connectivity of such networks.

Oblivious neighbor discovery algorithms in airborne networks with directional multi-antenna

Neighbor discovery problem is of essential importance in airborne network (AN) to support the capabilities of real-time situation awareness and sharing among aircraft. With the exploding demand for high-data-rate transmission and communication security, it is a predictable trend that adopt the multi-antenna in AN. However, due to the uncertainty of AN (e.g., oblivious relative positions, asynchronous clock, heterogeneous multi-antenna configurations, and anonymous information, the neighbor discovery algorithm must be carefully designed, with the aim at achieving faster beam rendezvous within a bounded latency. In this paper, the oblivious multi-antenna neighbor discovery problem is investigated, with the multi-antenna neighbor discovery algorithms (MAND) proposed based on the Chinese Remainder Theorem (CRT). Through the theoretical analysis, we derive the conditions for successful neighbor discovery within a bounded latency, as well as the worst case discovery latency bound with multi-antenna. The simulation results show that our algorithms can approximate the better average performance of the randomized mechanism in oblivious scenarios, besides achieving complete neighbor discovery within a bounded latency.

Can drones save lives and money? An economic evaluation of airborne delivery of automated external defibrillators.

Out-of-hospital cardiac arrest is one of the most frequent causes of death in Europe. Emergency medical services often struggle to reach the patient in time, particularly in rural areas. To improve outcome, early defibrillation is required which significantly increases neurologically intact survival. Consequently, many countries place Automated External Defibrillators (AED) in accessible public locations. However, these stationary devices are frequently not available out of hours or too far away in emergencies. An innovative approach to mustering AED is the use of unmanned aerial systems (UAS), which deliver the device to the scene. This paper evaluates the economic implications of stationary AED versus airborne delivery using scenario-based cost analysis. As an example, we focus on the rural district of Vorpommern-Greifswald in Germany. Formulae are developed to calculate the cost of stationary and airborne AED networks. Scenarios include different catchment areas, delivery times and unit costs. UAS-based delivery of AEDs is more cost-efficient than maintaining traditional stationary networks. The results show that equipping cardiac arrest hot spots in the district of Vorpommern-Greifswald with airborne AEDs with a response time < 4min is an effective method to decrease the time to the first defibrillation The district of Vorpommern-Greifswald would require 45 airborne AEDs resulting in annual costs of at least 1,451,160 €. In rural areas, implementing an UAS-based AED system is both more effective and cost-efficient than the conventional stationary solution. When regarding urban areas and hot spots of OHCA, complementing the airborne network with stationary AEDs is advisable.

A Multipath Local Route Repair Scheme for Bidirectional Traffic in an Airborne Network of Multibeam FDD Nodes

A directional airborne network consisting of nodes equipped with multibeam antennas is considered. These nodes use the frequency division duplex mode of communication. This allows formation of multiple routes between a pair of source and destination nodes, where every forward and reverse route completely overlaps. Each of these routes supports the bidirectional traffic. These routes are formed using the bidirectional ad hoc on-demand multipath distance vector (BAOMDV) routing protocol. In this article, we propose a local route repair scheme, called BAOMDV-LR, when these routes break due to node mobility. The proposed route repair scheme preserves the overlapping and link-disjoint (or node-disjoint) characteristics of the routes, while reducing the need for expensive route rediscovery. The proposed scheme significantly improves the overall network performance for bidirectional traffic (in terms of packet delivery ratio, end-to-end delay, and routing overhead) as compared to the BAOMDV and other existing routing schemes, especially at higher node speeds and data rates.

Review of Protocol Stack Development of Flying Ad-hoc Networks for Disaster Monitoring Applications.

When disasters such as floods or earthquakes occur, we may not have a support of regular infrastructure based networks. This proves fatal because people who are trapped can not be easily located by search and rescue team. In such cases, airborne network consisting of miniaturized drones can be extremely beneficial in providing quick and effective coverage of the affected area, in an on-demand manner providing instant insights to rescue teams. While the challenges offered by such networks are plenty, the ongoing research and development shows promise to make such a technology more reliable and effective. In this paper, we discuss various disaster events in which network of drones can play a vital role in offering support to rescue operations. Mainly, the article discusses the protocols proposed by researchers for various layers of protocol stack including physical layer, data link layer, network layer, transport layer, application layer along with clustering protocols, time synchronization protocols and localization protocols. Finally, a brief summary of software simulation platforms and testbeds, along with future trends of Flying Ad-hoc networks have been provided.

Heuristic-driven strategy for boosting aerial photography with multi-UAV-aided Internet-of-Things platforms

Unmanned Aerial Vehicles (UAVs) are gaining much attractiveness due to the emerging 5G, Internet of things applications and the advances in artificial intelligence. Their application fields encompass both civil and military domains. UAVs can ubiquitously supply many Internet-of-things-driven services; as such, they can be configured into airborne networks to provide flexible aerial views, which is essential for photography and videography-based applications like 3D mapping and real-time monitoring. However, many research challenges need to be tackled to facilitate the deployment of such promising applications. This paper addresses a non-convex NP-hard problem of deploying a fleet of UAVs equipped with rotating gimbal-mounted cameras over large-scaled terrains. The problem is heuristically solved in two phases. Firstly, we introduce a fast parallel multi-verse swarm optimization algorithm. A hybrid multi-objective heuristic coalescing two relevant concepts of stochastic optimization: (1) Improved Multi-Objective Particle Swarm Optimization; (2) Improved Multi-Objective Multi-verse Optimization. This heuristic holds several algorithmic tweaks, such as Pareto-based population splitting, Taguchi-based parameters tuning, adaptive mutation, and is used to derive the most near-optimal hovering coordinates of UAVs under two customized objective functions. Secondly, we adopt an efficient gimbal-based rotation and synchronization strategy allowing the UAVs to rotate their cameras resourcefully in four cardinal directions to boost the aerial photographing coverage with few maneuvers. The claimed performance is rigorously endorsed with intensive simulations and comparative analyses (e.g., analysis of variances, Wilcoxon test, performance index) against twenty multi-objective bio-inspired heuristics. The results show that our approach has the upper hand in terms of efficiency and accuracy.

Application prospect of time-sensitive network in airborne communication network

TSN (Time Sensitive Network) is a real-time Network communication technology being promoted by the international industry. It has the characteristics of more flexibility and high real-time performance. This paper firstly introduces the background of airborne network and real-time network. Then, TSN and the mainstream airborne communication network technology are compared and analyzed from the aspects of synchronization mechanism, scheduling strategy, redundancy and reliability mechanism. Finally, the prospect of TSN in the field of civil aviation is analyzed in general, which makes the application route of TSN in the airborne communication network more clear.