1. Introduction
Advanced air mobility (AAM) is a growing field, with a focus on developing air transportation systems that can be integrated into urban environments to provide faster, more efficient, and more environmentally friendly transportation options. Air mobility refers to the use of aircraft, including helicopters, tilt-rotors, and electric vertical take-off and landing (eVTOL) vehicles, to transport passengers and cargo within urban areas. AAM aims to provide a faster, more efficient, and environmentally friendly mode of transportation, particularly in congested urban areas. AAM technology is still in its early stages, but many companies, including major aerospace companies and start-ups, as well as standards [
1], are investing in the development of eVTOL vehicles and related infrastructure, such as charging stations and landing pads [
2]. The use of AAM is expected to provide benefits such as reducing traffic congestion, improving connectivity and accessibility, and reducing carbon emissions from ground transportation. However, there are also concerns about the safety and noise levels of AAM vehicles and their impact on urban landscapes [
3]. The vehicle mostly considered for AAM operations is an eVTOL aircraft capable of carrying passengers and air cargo with a limited capacity. Like any other flying platform with humans on board and flying over human living areas, AAM vehicles require a highly reliable and intelligent system of communication, navigation, and surveillance (CNS) [
4,
5] to ensure safe operations and to avoid life-threatening accidents. When it comes to autonomous and beyond visual line of sight (BVLOS) flights in future, the reliability and robustness of the communication link between the AAM vehicle and ground control stations is the key factor in safe AAM operations. One of the key challenges for AAM connectivity is the need for secure and reliable communication networks that can handle the massive amounts of data that these vehicles generate [
6] while the AAM vehicle flies through controlled and uncontrolled airspace. When flying through controlled airspace, it should be in communication with air traffic management (ATM) entities on the ground and follow their instructions [
7].
To address these challenges, industry leaders are working to develop advanced communication technologies, such as fifth-generation (5G) networks and satellite-based communication systems, that can support AAM operations [
8]. Telecommunications providers will become a main backbone for eVTOL services due to their network reliability, low latency, and high-bandwidth services to ensure safe and efficient flight management and robust connectivity with other aircraft. Based on the functionalities and performance, the advanced communication system can be divided into edge cloud, core network, AAM-UTM [
9], and telemetry services [
10], as shown in
Figure 1. A control data link will be responsible for the transmission of mission-critical commands to flying vehicles. This includes flight status, telemetry data, and navigation. A payload communication data link can handle the mission and passenger data, including web browsing and vehicle health, for predictive maintenance. On the other hand, BVLOS is the most critical challenge that impacts the safety of vehicles [
11]. To further improve flight operations, there is a need to establish an integrated unmanned aircraft system traffic management (UTM). system that facilitates the processing of dense connected eVTOLs in the whole airspace. This systematic modeling helps to identify the entry of new, diverse eVTOLs into complex communication domains, along with enforcing safety measures to maintain safe and efficient service management, with new vehicle parameters, as shown in
Table 1. Therefore, the AAM data ecosystem will also consist of service assurance and self-optimization, soft defined networks, and a digital twin that provide the necessary features for worldwide deployments [
12].
The eVTOL vehicles will operate in lower altitudes within the coverage domains of ground base stations; the terrestrial cellular communication network 5G seems to be a capable of providing air-to-ground (A2G) connectivity for AAM [
13]. The eVTOLs’ connectivity appears as a bulk of new users require certain features to support regular communications for data transmission along with navigational information required for routing eVTOLs between flying corridors. Advanced terrestrial networks, such as sixth-generation (6G) technology, can take advantage of the latest evolutions in 5G end-to-end slicing, artificial intelligence (AI), and the Internet of Things (IoT) [
14,
15]. Advanced communications technology can find the position of eVTOLs and hopefully support the management of their operations with the help of extended coverage and services [
16]. Sixth-generation communications will play an important role for eVTOL aircraft, providing near-real-time data link connectivity to keep city skies safe while the volume of flying vehicle traffic grows [
17]. This advanced communications technology will be crucial for situational awareness, air-to-air, and air-to-ground communication. In particular, advanced communications technology will help to achieve low-latency and high-throughput connections for in-flight passenger applications [
18].
The communication networks of future air mobility systems must be highly reliable, secure, and able to handle large amounts of data in real time. These networks will need to support a variety of applications, including remote sensing, situational awareness, navigation, and communication between vehicles and ground-based control systems [
19]. One of the key requirements for the air mobility communication network is low latency, which means that data must be transmitted quickly and efficiently. This is especially important for autonomous vehicles that need to make quick decisions based on real-time data. The network must also be able to handle a large number of devices, including sensors and other types of devices that will be used to support the operation of air mobility vehicles. In this regard, this paper introduces new air mobility challenges and proposes frameworks of aerospace integration-based connected systems that could be compatible with existing and future infrastructure, rather than rebuilding the underlying digital chain. This can be more realistic for separate economic sectors to come together and less challenging from a technical perspective. This will help to facilitate the entry of new diverse vehicles into an already complex communications environment, along with establishing robust safety features to meet evolving standards.
Finally, the network must be able to handle the unique requirements of air mobility, such as high-altitude communications, the need to operate in remote and challenging environments, and the ability to switch seamlessly between different types of communication technologies. Overall, the future of air mobility will depend heavily on the development of robust and reliable communication networks that can support the safe and efficient operation of these vehicles. As new technologies emerge, it will be important to continue to innovate and improve these networks to meet the evolving needs of the industry.
4. Aeronautical Communications Architecture
There are several existing aircraft communication systems that are used in the aviation industry today. These systems enable communication between the cockpit and air traffic control, as well as between aircraft and ground-based maintenance and operations personnel. A legacy ATM encompasses all systems that assist aircraft to depart from an aerodrome, transit airspace, and land at a destination aerodrome. However, ATM systems lack the scalability and interfaces to support the unique needs of AAM operations, specifically AAM vehicle operations. On the other hand, UTM handles traffic management for AAM vehicles, but also complements legacy ATM systems, allowing for the exchange of data between AAM vehicles and manned-aircraft-supporting platforms. Regarding the AAM ecosystem, there are several basic data sources that UTM will need to integrate to ensure the safe and efficient movement of the AAM vehicle. The data could originate from 6G radio access networks, AAM vehicle service providers, AAM vehicle fleets, weather forecasting, surveillance systems, etc. This information is further processed through artificial intelligence (AI) to determine the exact AAM vehicle location and relevant traffic managements for that airspace. AAM communications infrastructure is designed to provide services to predefined sets of users with well-known capacity and key performance indicator (KPI) requirements. Although 5G lays down the basic functionalities at the base station for AAM vehicle connectivity, it is sometimes impossible, or prohibitively expensive, to provide full support to AAM vehicle domains. The forthcoming communications infrastructure can overcome these physical constraints using newly designed technologies and features that provide extended coverage domains over the ground and the sea and throughout the sky to seamlessly integrate AAM vehicles into the network infrastructure. Early alignment between infrastructure and technology in the AAM industry is essential to the growth of this emerging industry. The industry and public attention are largely focused on the vehicles and their operations. However, attention is shifting towards maintenance and support services for AAM vehicles as a crucial component in enabling safe, efficient, and environmentally sustainable AAM transport. The AAM service will consist of several autonomous systems (delivery AAM vehicles, flying taxis, etc.) in the future that can be remotely commanded to perform assigned missions. Requesting a certain service from a AAM platform will be enabled via centralized register that offers such services and identifies them to local providers. To this end, services can be classified as separated vertical slices, probably with their own network core entities and near-user application servers. Although some AAM vehicles may support multiservice types and could have differed registers within the database, some will be only associated with one type of service or even be owned/operated by one service provider. The assignment scheme of services will be subject to the requested service type, enforced policies, available computational and radio resources, and performance metrics. A data-driven decision-making approach can be enabled via deep learning data analysis across all the monitored constraints, developing a more automated approach for service planning and management, both at strategic and tactical levels. On the other hand, future 6G networks need to be more focused on using reinforcement learning to understand and learn how to interact with AAM vehicles considering requested services and connectivity factors. In
Figure 5, the proposed AAM framework shows interaction with the communication network for safe AAM vehicle landing at an airport and later movement to a gate. For example, in the context of a vehicle-assisted communications network, the whole communication systemwill be administrated by a data management platform to achieve the dynamic and flexible allocation of computational and radio resources with minimized power consumption to facilitate the handover process [
17]. AAM vehicles will need to communicate with air traffic control (ATC) to receive clearances, flight plans, and other information necessary for safe operation in airspace. Communication with ATC will be critical to avoid conflicts with other aircraft and ensure that AAM vehicles are operating in accordance with existing regulations. AAM vehicles may need to communicate with each other to avoid collisions and ensure safe separation in airspace. Vehicle-to-vehicle communication can enable real-time sharing of information such as position and speed to enable the safe and efficient operation of AAM vehicles. AAM vehiclesmay need to communicate with ground-based infrastructure, such as landing pads or vertiports, to receive information on available space and conditions for landing. Infrastructure communication can also enable the remote control of ground-based infrastructure to facilitate the efficient movement of AAM vehicles. In the event of an emergency, AAM vehicles will need to communicate with ground-based personnel, including emergency responders, to receive assistance and coordinate rescue efforts. Emergency communication systems will need to be reliable and efficient to enable rapid response and ensure the safety of passengers and crew.
5. Future Communications Infrastructure
Fifth-generation networks leveraged the concept of networking into the new automated slices of private networks that provide dedicated services to specific sites. Sixth-generation networkswill further leverage their infrastructure into chains of separated reconfigurable and self-automated private networks that interconnect with each other through clouds [
8]. This network will be built on top of a blockchain with back-end elementsin the form of Tactile Internet. Tailoring to AAM, AAM vehicle management could be performed in two modes; “Localized” and “Centralized”.
In Localized Mode, the AAM vehicle connectivity and service management will be provisioned by the local geonetwork base station and core functionalities in collaboration with UTM entities. This mode is likely to occur when an AAM vehicle is flying within the local network boundaries. This interaction between AAM vehicles and local networks will reduce the end-to-end time delays incurred when processing the service assignment and access though large scale-networks, similar to edge computing models in 5G. Therefore, the AAM vehicle’s association with the local geonetwork will be terminated when the AAM vehicle conducts handover and registers with a neighboring subnetwork.
In Centralized Mode, the AAM vehicle connectivity is provided by the local network resources (e.g., base station, external connectivity to application server, etc.), while service provisioning is performed by core network entities. This mode assumes that the core network will be able to instantiate a logical overlaid networkthat overwrites all local network policies for AAM vehicle slices of service. This mode is triggered when a fleet of associated AAM vehicles swarm multiple local networks at the same time, or during emergencies when governing authorities take control over the entire airspace.
In the near future, AAM communications networks will tremendously evolve, driven by a sharp increase in connected machines, data demands, supported services, and the advent of 6G [
54]. Designing a compatible network infrastructure that supports traffic demands in a cost-effective fashion will be always subject to network generation.A main challenge in providing connectivity to low-flying AAM vehicles through future 6G networks arises from increased interference. Dense network infrastructure and concurrent transmissions to ground-based users and AAM vehicles are the main sources for higher noise levels, especially on the downlink. In addition, AAM vehicles could also overload the network with massive data streams with limited channel bandwidth. One of the solutions may be much tighter frequency reuse and wider channel deployment. Therefore, it is necessary to define the equivalent of hexagonal cellular domain shapes for the AAM vehicle’s air layer or what could be the air coverage domains for ground base stations. The speed performance of the 6G network is expected to be 100 times faster than 5G, with enhanced reliability and wider network coverage; for more features and comparison between different technology, see
Table 3. In addition, seamless mobility will be required for the system operation; thus, the handover prediction for dual connectivity in AAM vehicles is an important technique to ensure seamless communication between the aircraft and different base stations, which is essential for the safe and efficient operation of the AAM. In dual connectivity, the aircraft is connected to two base stations simultaneously, which provides redundancy and improves the reliability of communication link. One of the key challenges of handover is the need for real-time prediction, since AAM operations require immediate and reliable communication links [
55].
6. Air-to-Ground Connectivity
One of the key parameters that could affect the implementation of AAM is the airborne communication system. The AAM vehicle will have to communicate with the ground station continuously to maintain an uninterrupted flow of data and UTM messages. Therefore, the AAM radio system will employ reconfigurable components that can perform ubiquitous connectivity with the ground mobile network without being restricted to specified technology [
58]. The airborne system will employ an AI functionality that provisions the platform and allows communication with mobile networks [
59]. The AAM vehicle will be registered with the 5G base stations using the same procedures for any connected machine, while requests to the ground network will be tagged with the AAM slice type to ease the recognition of the requested service. The airborne communication system will be extremely power-efficient to maintain functionality during longer flight times and to reduce the burden on the AAM power system. From an airborne communication perspective, the AAM will employ multiradio interfaces or become agnostic to base station technology. This means that mobile networks will be obligated to connect any AAM vehicles within their coverage area, regardless of the vehicle’s service provider or home mobile network. Although the final framework for enabling AAM communications will be decided by market holders, such decisions will influence the techniques and protocols used to operate AAM services. Air-to-ground communication systems are essential for ensuring safe and efficient communication between aircraft and ground stations. The information given in
Table 4 includes communication systems, frequency ranges, and applications. Very-high-frequency (VHF) radios are the most widely used communication system in aviation. VHF radios operate in the frequency range of 118 MHz to 136 MHz, and are used for voice communication between pilots and air traffic control [
45]. The Aircraft Communications Addressing and Reporting System (ACARS) is a digital communication system that enables pilots and ground personnel to exchange messages, including weather updates, flight plans, and maintenance information. ACARS can use VHF, HF, or satellite communication systems to transmit data.
AAM Connectivity Performance Analysis
The performance of AAM connectivity can be affected by several factors, such as the frequency spectrum used for communication, the type of data transmission protocol used, the location and number of communication nodes, the quality of service (QoS) requirements, and the presence of other wireless systems in the same frequency band. Since current and future networks are densely overlaid with base stations, AAM vehicles will be always connected to mobile networks, provided that those future networks will employ new generations of base stations with magnificent coverage capabilities. QoS communications system parameters refer to the configuration settings that determine how data are transmitted and received over a network to ensure a certain level of service quality. These parameters are critical to providing reliable and efficient communication services. The main QoS requirement parameters are shown in
Table 5. For example, bandwidth determines the amount of data that can be transmitted over the network per unit of time, and latency refers to the delay between sending and receiving data for real-time communication applications. Thus, QoS systems can implement error correction techniques to detect and correct errors in transmitted data.
This dense network will support connectivity across cells while maintaining uninterrupted service for AAM vehicles. Handover is carried out when the signal received from base station falls below the threshold level and there is another base station within the visible range. For such air-to-ground connectivity, the priority will be always given to AAM vehicles flying in urban domains to avoid unnecessary handovers to neighboring rural domains. This type of procedure could be predefined on AAM vehicle platforms and enforced by terrestrial mobile networks. One of the main challenges for delivering video or data content is the real-time throughput for AAM connectivity and quality of service (QoS) parameters, including bandwidth, delay, packet loss, and jitter. In general, radio signal strength is the value measured by the AAM vehicle platform to establish connectivity with the nearest base station along its flight trajectory.
These equations can be customized and modified based on the specific QoS requirements of AAM communication systems.
For AAM flying vehicles, handover and mobility management are critical components of the communication system. As the vehicle moves through the airspace, it needs to seamlessly switch between communication links to ensure uninterrupted connectivity.
Handover initiation threshold (HIT):
Handover hysteresis (Hys):
Reference signal received power (RSRP):
Effective signal-to-noise ratio (SNR):
HIT refers to the signal strength threshold at which a handover is initiated. Hys refers to the hysteresis value that determines how much the signal strength should differ from HIT to trigger a handover. RSRP is the received signal strength of the reference signal. PRS refers to the received power of the reference signal. NRS is the noise floor of the reference signal. N0 is the noise floor of the receiver. SNReff refers to the effective signal-to-noise ratio of the received signal. Psig is the received power of the signal. Iinterf is the interference power. HM is the handover margin, which is the difference between the current RSRP and the target RSRP for the new cell. AAM vehicles can benefit from using both the received signal strength indicator (RSRP) and the received signal quality (RSRQ) to make handover decisions. RSRQ provides information about the quality of the signal, which can be used to prioritize certain links over others. AAM vehicles will experience some handovers while traveling through these areas, as shown in
Figure 6. The simulation scenario consists of seven cells on the ground covering the areas around the flight trajectory. Each cell has three directional antennas, downtilted 120 degrees, with one main lobe (facing the ground) and two sidelobes (facing the sky). The AAM vehicle connects to the cells through these sidelobes. The figure also shows the connection of the AAM to different cells (Cell ID) throughout its 14 km journey (origin to destination/landing point) for a given speed, and the altitude is shown. The jumps in this figure represent the disconnection from the previous cell and connection to a new cell, known as a handover. At some point, we notice ping-pong handovers, which occur when the AAM vehicle is flying through null spaces of the two sidelobes of a single cell; the system parameters are summarized in
Table 6.
Figure 7 shows the reference signal received power (RSRP), which is a measurement of the received power level in a communications network. The average power is a measurement of the power received from a single reference signal. The RSRP is of detected cells by the AAM vehicle throughout its 14 km journey.The null spaces between sidelobes of each cell are quite visible in this figure, where a sudden drop in RSRP is noticed. In order to mitigate the problem of redundant and ping-pong handovers, a new handover scheme for network infrastructure should be modified for the AAM vehicle.
Figure 8 shows the same for a different route and at 1000 m AGL, and as it is seen, all seven cells are detected during the whole flight path.
Figure 9 depicts the RSRP of the detected ground communication infrastructure at a height of 100 m above ground level (AGL). At low altitudes, the aircraft does not fall with the coverage area of any sidelobe of remote towers, and only detects the propagation of the closest tower.
It should be mentioned that in these simulations, we have not considered the multipath reflections from main beams or strong sidelobes of the serving or neighbor cells at low altitudes. However, at higher altitudes, these multipath reflections are too weak to be considered. In this section, we have simulated flights at altitudes of 500 m AGL and higher. The multihop wireless backhaul networks are a promising solution for providing reliable and cost-effective connectivity in areas where traditional wired backhaul is not feasible. As expected, the received power of a wireless communication signal decreases with increasing distance between the transmitter and the receiver due to the inverse-square law. Additionally, when the transmitter and the receiver are in motion relative to each other, the frequency of the signal can be shifted due to the Doppler effect. This can lead to a loss in signal quality and a decrease in the received signal power, which can further reduce the range of the communication link. To overcome these issues, various techniques can be used, such as increasing the transmitting power, using directional antennas, optimizing the frequency band and modulation scheme used, and employing signal processing techniques to mitigate the effects of fading and Doppler shift, as shown in
Figure 9.
The velocity of the AAM vehicle can also affect the received signal distance, as higher speeds can cause Doppler shift and signal attenuation. Assuming a line-of-sight communication scenario, the following table provides a rough estimate of the signal received distances for different AAM vehicle velocities, assuming a transmitting power of 1 watt and a receiving sensitivity of −100 dBm, as shown in
Figure 10. Finally, a connected eVTOL vehicle is designed to operate seamlessly and safely in complex urban environments, using advanced connectivity and communication technologies to enable efficient and reliable transportation for passengers and cargo.