Towards Robust and Efficient Communications for Urban Air Mobility

For the realization of the future urban air mobility, reliable information exchange based on robust and efficient communication between all airspace participants will be one of the key factors to ensure safe operations. Especially in dense urban scenarios, the direct and fast information exchange between drones based on Drone-to-Drone communications is a promising technology for enabling reliable collision avoidance systems. However, to mitigate collisions and to increase overall reliability, unmanned aircraft still lack a redundant, higher-level safety net to coordinate and monitor traffic, as is common in today's civil aviation. In addition, direct and fast information exchange based on ad hoc communication is needed to cope with the very short reaction times required to avoid collisions and to cope with the the high traffic densities. Therefore, we are developing a \ac{d2d} communication and surveillance system, called DroneCAST, which is specifically tailored to the requirements of a future urban airspace and will be part of a multi-link approach. In this work we discuss challenges and expected safety-critical applications that will have to rely on communications for \ac{uam} and present our communication concept and necessary steps towards DroneCAST. As a first step towards an implementation, we equipped two drones with hardware prototypes of the experimental communication system and performed several flights around the model city to evaluate the performance of the hardware and to demonstrate different applications that will rely on robust and efficient communications

Communication Links for Unmanned Aircraft Systems in Very Low Level Airspace

Communication links are inevitably needed by operators as well as by unmanned aircraft system traffic management to command, monitor and coordinate unmanned aircraft in very low level airspace. This is especially true, since a great number of unmanned aircraft is projected for this airspace in the near future. However, a common standard for communication links for unmanned aircraft systems does not exist at the moment. This work describes the current state of the research and addresses basic research questions concerning the demands imposed by unmanned aircraft system traffic management and operators, the role of autonomy, throughput requirements, communication network architectures and the possibility of re-using existing mobile and vehicular communications systems

Reliability Analysis of Cooperative Traffic Conflict Detection in Drone Ad-Hoc Networks

The growing density of drone traffic due to the increasing popularity of drones will cause frequently occurring traffic conflicts. This creates the need for reliable traffic conflict detection methods to minimize the number of mid-air collisions. A method to cooperatively detect traffic conflicts is the periodic exchange of beacon messages among neighboring drones. By receiving beacon messages containing status information, each drone becomes aware of arising traffic conflicts. Hence, conflict detection reliability inherently depends on successfully receiving beacon messages. However, a mapping from the beacon message reception probability to the conflict detection reliability does not exist yet. Therefore, we present at first a mathematical model which allows us to compute the beacon message reception probability in drone ad-hoc networks which use the slotted Aloha medium access control protocol. Subsequently, we introduce two novel metrics namely conflict detection probability and detection distance. These novel metrics are required since existing metrics have been found unsuitable for the analysis of the conflict detection reliability. The novel metrics allow statements about the reliability by taking the probability of receiving beacon messages from conflicting drones as well as the conflict scenario into account. Our results show that the conflict detection reliability strongly depends on the choice of physical and medium access control parameters, especially the number of information bits per complex symbol and the number of beacon message broadcasts per second. Moreover, we show the existence of an optimum choice of these parameters which maximize the conflict detection reliability in a specific scenario

Reliability Analysis of Cooperative Traffic Conflict Detection in Drone Ad-Hoc Networks

The growing density of drone traffic due to the increasing popularity of drones will cause frequently occurring traffic conflicts. This creates the need for reliable traffic conflict detection methods to minimize the number of mid-air collisions. A method to cooperatively detect traffic conflicts is the periodic exchange of beacon messages among neighboring drones. By receiving beacon messages containing status information, each drone becomes aware of arising traffic conflicts. Hence, conflict detection reliability inherently depends on successfully receiving beacon messages. However, a mapping from the beacon message reception probability to the conflict detection reliability does not exist yet. Therefore, we present at first a mathematical model which allows us to compute the beacon message reception probability in drone ad-hoc networks which use the slotted Aloha medium access control protocol. Subsequently, we introduce two novel metrics namely conflict detection probability and detection distance. These novel metrics are required since existing metrics have been found unsuitable for the analysis of the conflict detection reliability. The novel metrics allow statements about the reliability by taking the probability of receiving beacon messages from conflicting drones as well as the conflict scenario into account. Our results show that the conflict detection reliability strongly depends on the choice of physical and medium access control parameters, especially the number of information bits per complex symbol and the number of beacon message broadcasts per second. Moreover, we show the existence of an optimum choice of these parameters which maximize the conflict detection reliability in a specific scenario

Techniques for Improving the Cooperative Traffic Conflict Detection among Drones

Multiple access interference naturally occurs in ad-hoc networks if the same resources in time-, frequency- or code-domain are used by two or more users concurrently. Unfortunately, it can have a severe impact on the networks' performance. Therefore, mitigation strategies are needed especially with regard to safety-critical applications of ad-hoc networks like the cooperative traffic conflict detection among drones. In our work, we evaluate two techniques which deal with the problem of multiple access interference and increase the network's capacity with respect to this particular application. The first technique is successive interference cancellation whereas the second technique is known as space division multiple access. We evaluate both techniques in a future urban drone scenario considering different conflict scenarios and network parameters, i.e. the communications range of a drone. Our results show, that both techniques are capable of improving the maximum supported drone density without degrading the application’s reliability. Especially, space division multiple access leads to an improvement of up to 157% in one of the investigated conflict scenarios

The Impact of Multipath Propagation on Cooperative Traffic Conflict Detection among Drones

Drone-to-drone communications in urban airspace is likely to be severely influenced by multipath propagation due to numerous reflections off the ground surface, building, or other structures. In this contribution, we have a look at its impact on a specific application, namely the cooperative detection of traffic conflicts through the periodic exchange of beacon messages. Therefore, we propose a theoretical drone-to-drone communications channel model incorporating a ground reflection and Rician fading. Eventually, we show in simulations the influence of the Rician K-factor and the drones' conflict altitude on the probability of detecting traffic conflicts. Especially, low K-factors increase the probability of missing a detection up to 10e7-times compared to free-space propagation

Suitability of LTE for Drone-to-Infrastructure Communications in Very Low Level Airspace

The increasing availability of cheap and powerful drones for various applications is likely to cause a heavy usage of the very low level airspace in metropolitan areas with up to 500 simultaneously airborne drones per square kilometer in the near future. Certainly, the predicted large number of drones presents a major challenge to future UTM and especially to supporting communications systems. A robust and reliable communications system for drone-to-infrastructure communications is inevitably needed to grant all drones access to various services provided by UTM. In previous works, it has already been shown that LTE is capable of providing connectivity to drones flying at low altitudes in principle. However, airborne drones which transmit data to UTM produce severe inter-cell interference since they have a strong line-of-sight connection to multiple LTE base stations. Hence, we investigate further the suitability of the LTE uplink for drone-to-infrastructure communications in very low level airspace by system-level simulations in this work. In particular, the maximum drone density that can be thoroughly monitored and safely coordinated by a UTM system with LTE communication links is identified. Our simulations show that LTE is not suitable for high-density scenarios due to the severe uplink interference. It is concluded that future research has to focus on the mitigation of inter-cell interference so even a large number of drones can get reliable access to all UTM services