An Experimental mmWave Channel Model for UAV-to-UAV Communications

Unmanned Aerial Vehicle (UAV) networks can provide a resilient communication infrastructure to enhance terrestrial networks in case of traffic spikes or disaster scenarios. However, to be able to do so, they need to be based on high-bandwidth wireless technologies for both radio access and backhaul. With this respect, the millimeter wave (mmWave) spectrum represents an enticing solution, since it provides large chunks of untapped spectrum that can enable ultra-high data-rates for aerial platforms. Aerial mmWave channels, however, experience characteristics that are significantly different from terrestrial deployments in the same frequency bands. As of today, mmWave aerial channels have not been extensively studied and modeled. Specifically, the combination of UAV micro-mobility (because of imprecisions in the control loop, and external factors including wind) and the highly directional mmWave transmissions require ad hoc models to accurately capture the performance of UAV deployments. To fill this gap, we propose an empirical propagation loss model for UAV-to-UAV communications at 60 GHz, based on an extensive aerial measurement campaign conducted with the Facebook Terragraph channel sounders. We compare it with 3GPP channel models and make the measurement dataset publicly available.Comment: 7 pages, 7 figures, 3 tables. Please cite it as M. Polese, L. Bertizzolo, L. Bonati, A. Gosain, T. Melodia, An Experimental mmWave Channel Model for UAV-to-UAV Communications, in Proc. of ACM Workshop on Millimeter-Wave Networks and Sensing Systems (mmNets), London, UK, Sept. 202

Channel Model and Performance Analysis of Millimetre-wave UAV Air-to-Ground Link under UAV Wobbling

Fifth-generation (5G) and beyond mobile communication networks are expected to meet an explosion of data traffic usage and a fast-varying environment. The millimetre-wave communications and unmanned aerial vehicles (UAVs) communications are two important methods to tackle these challenges. To thoroughly investigate millimetre-wave UAV communications, it is essential to have a good understanding of electromagnetic wave propagation in the millimetre-wave band between the UAV-carried aerial base station or the mobile relay node and ground nodes, which is known as the UAV air-to-ground (A2G) channel model. To support the millimetre-wave UAV A2G network design, it is vital to have a deep cognition of the network performance evaluation parameters of the UAV A2G link, e.g., throughput and energy efficiency. This thesis discusses three problems related to millimetre-wave UAV A2G communications. In this study, the effect of the inevitable UAV wobbling on the millimetre-wave UAV A2G channel is first investigated. The wobbling process of a hovering UAV, which is affected by wind gusts and the high vibration frequency of its propellers and rotors, is modelled. The analytical temporal autocorrelation function (ACF) for the millimetre-wave UAV A2G link is derived. With the derived temporal ACF equation, the Doppler power spectrum density for the millimetre-wave UAV A2G link is investigated. The numerical results show that the temporal ACF decreases quickly with time and the impact of the Doppler effect caused by UAV wobbling is significant on bit error probability (BEP) for the millimetre-wave A2G link. Then, the problem of throughput for the millimetre-wave UAV A2G link under UAV wobbling is investigated. Two types of detectors at the receiver to demodulate the received signal and get the instantaneous BEP of a millimetre-wave UAV A2G link under UAV wobbling are introduced. Based on the designed detectors, an adaptive modulation scheme maximising the average transmission rate under UAV wobbling by optimizing the data transmission time subject to the maximum tolerable BEP is proposed. The numerical results show that the proposed adaptive modulation maximises the temporally averaged transmission rate of the millimetre-wave UAV A2G link compared with other transmission policies under UAV wobbling. After proposing the adaptive modulation, the power control to minimise the power consumption is investigated considering the limited on-board energy of a UAV. A power control policy that minimises the transmission power while maintaining both the BEP under the threshold and the maximised average transmission rate is proposed for the millimetre-wave UAV A2G link under UAV wobbling. The energy efficiency of the UAV A2G link is evaluated to show how effective this power control policy is. The numerical results show that the power control policy reduces the power consumption by up to 50% for wobbling millimetre-wave UAV A2G links and the energy efficiency of the system under power control is higher than that of the adaptive modulation scheme without the power control policy. In summary, the thesis studies the channel characteristics and evaluates the performance of the millimetre-wave UAV A2G link under wobbling to support the future millimetre-wave UAV communication network deployment. A key observation is that even for weak UAV wobbling, the temporal ACF of the UAV A2G link deteriorates quickly, making the link difficult to establish a reliable communication link. To keep the reliable A2G link and achieve high throughput, the adaptive modulation scheme of the millimetre-wave UAV A2G link under wobbling is proposed. The power control policy for the adaptive modulation of the millimetre-wave UAV A2G link could save power by over 50% and support the green UAV A2G link

Characterization of UAV-based Wireless Channels With Diverse Antenna Configurations

In the next wave of swarm-based applications, unmanned aerial vehicles (UAVs) need to communicate with peer drones in any direction of a three-dimensional (3D) space. On a given drone and across drones, various antenna positions and orientations are possible. We know that, in free space, high levels of signal loss are expected if the transmitting and receiving antennas are cross polarized. However, increasing the reflective and scattering objects in the channel between a transmitter and receiver can cause the received polarization to become completely independent from the transmitted polarization, making the cross-polarization of antennas insignificant. Usually, these effects are studied in the context of cellular and terrestrial networks and have not been analyzed when those objects are the actual bodies of the communicating drones that can take different relative directions or move at various elevations. In this work, we show that the body of the drone can affect the received power across various antenna orientations and positions and act as a local scatterer that increases channel depolarization, reducing the cross-polarization discrimination (XPD). In addition to communicating with other UAVs in a swarm, UAVs can also serve users on the ground. For example, at ultra-low altitudes, an unmanned aerial vehicle (UAV) can act as a personal base station where it communicates only with one or two users on the ground. The communication device used by a user can be in their pocket, held by hand, or attached to their bodies. In these scenarios, the wireless channel can go through different fading levels, depending on the UAV’s location, user orientation, the location of the UE near the user’s body, and the frequency of the transmitted signal. The extent to which these factors can affect Air-to-Ground channels at ultra-low altitudes is studied in this work. We answer questions regarding how the human body and different use-cases of holding a communication device on the ground can affect the quality of the wireless channel and the optimal UAV hovering location. Furthermore, we demonstrate how the observed effects can be leveraged to our advantage and increase the physical layer security of UAV-assisted networks relying on the human-induced effects. Finally, in situations where a UAV swarm needs to communicate with a target that is far or surrounded by undesired receivers, beamforming can be an attractive solution. With beamforming, the transmitted signal becomes shaped towards a certain direction confining its spatial signature and increasing the received signal-to-noise-ratio (SNR) at the receiver. However, phase synchronization across the swarm is difficult to achieve and there will always exist some degree of phase incoherency across the transmitted signals from the distributed UAVs. Phase differences between the distributed nodes would result in signals arriving at different times and their phases might not align with each other resulting in reductions in beamforming gain. Hence, a method to increase phase coherency at the receiver with limited channel overhead is desired. To this end, we propose a UAV rotation-based method through which the UAV, relying on its heterogeneous body structure, can alter the phase of the incoming signals and increase the beamformed signal level

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios