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

A Realistic 3D Non-Stationary Channel Model for UAV-to-Vehicle Communications Incorporating Fuselage Posture

Considering the unmanned aerial vehicle (UAV) three-dimensional (3D) posture, a novel 3D non-stationary geometry-based stochastic model (GBSM) is proposed for multiple-input multiple-output (MIMO) UAV-to-vehicle (U2V) channels. It consists of a line-of-sight (LoS) and non-line-of-sight (NLoS) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e. the temporal autocorrelation function (ACF) and spatial cross correlation function (CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture.Comment: 12 pages, 8 figures, CNCO

Map-based Channel Modeling and Generation for U2V mmWave Communication

Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including interpath and intra-path are analyzed in detail. The inter-path parameters are calculated in a deterministic way, while the parameters of intra-path rays are generated in a stochastic way. The statistical properties are obtained by using a Gaussian mixture model (GMM) on the massive ray tracing (RT) data. Then, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. Meanwhile, to reduce the complexity of RT method, the 3D propagation space is reconstructed based on the user-defined digital map. The simulated and analyzed results show that the proposed model and generation method can reproduce non-stationary U2V channels in accord with U2V scenarios. The generated statistical properties are consistent with the theoretical and measured ones as well

Dual-Band Non-Stationary Channel Modeling for the Air-Ground Channel

Multiple air-to-ground (AG) radio propagation channels are experimentally characterized for two frequency bands, C-band and L-band. These characterizations are aimed to support the specification of the control and non-payload communication (CNPC) links being designed for civil unmanned aircraft systems (UAS). The use of UAS is expected to grow dramatically in the coming decades. In the United States, UAS will be monitored and guided in their operation within the national airspace system (NAS) via the CNPC link. The specifications of the CNPC link are being designed by government, industries, academia and standards bodies such as the Radio Technical Commission for Aeronautics (RTCA). Two bands have been allocated for the CNPC applications: from 5030 to 5091 MHz in C-band and a portion of the aeronautical L-band from 960 to 1215 MHz. The project under which this work was conducted is entitled “Unmanned Aircraft Systems Research: The AG Channel, Robust Waveforms, and Aeronautical Network Simulations”, and this is a sub-project of a NASA project entitled “Unmanned Aircraft Systems Integration in the National Airspace System.” Measurements and modeling for radio propagation channels play an essential role in wireless communication system design and performance evaluation; such models estimate attenuation, delay dispersion, and antenna diversity in wireless channels. The AG channel differs significantly from classic cellular, ground-to-satellite, and other terrestrial wireless channels, particularly in terms of antenna heights and velocity. The previous studies about the AG channels are reviewed and the significant gaps are indicated. NASA Glenn Research Center has conducted an AG channel measurement campaign for multiple ground station local environments, including over sea, over freshwater, desert, suburban, near urban, hilly and mountainous settings. In this campaign, over 316 million power delay profiles (PDPs) or channel impulse responses (CIRs), over 82 flight tracks, have been collected. The measurement equipment was a dual-band single-input multiple-output (SIMO) wideband channel sounding system with bandwidth of 50 MHz in C-band and 5 MHz in L-band. Given the dynamic nature of the AG environments, the channels are statistically non-stationary, meaning that the channel’s statistical parameters change over time/space. We have estimated, via two distinct methods, that the stationarity distance is approximately 15 m—this is the distance over which the channel characteristics can be assumed to be wide sense stationary. The AG channel attenuation is considered as a combination of large scale path loss, small scale fading, and airframe shadowing. The large scale path loss is modeled by both the log-distance model and two-ray models. The theoretical flat earth and curved earth two-ray models are presented, along with their limitations, boundaries and some enhancements. Numerous propagation effects in the AG channels are discussed, and this includes earth spherical divergence, atmospheric refraction, atmospheric gas and hydrometeor attenuations, and ducting. The small scale fading is described by the Ricean distribution, which for unit-energy normalizations are completely characterized by Ricean K-factors; these K-factors are approximately 28.7 dB in C-band and 13.1 dB in L-band. The line-of-sight (LOS) signal can be obstructed by the airplane itself in some specific maneuvers, and this is termed airframe shadowing. For the specific flights and NASA aircraft used in our measurements, the shadowing duration was found to be on average 30 seconds, and the shadowing loss can be as large as 40 dB. The statistics, models and simulation algorithm for the airframe shadowing are provided. The wideband characteristics of the AG channel are quantified using root-mean-square delay spread (RMS-DS), and illustrated by sequences of PDPs. Tapped delay line (TDL) models are also provided. Doppler effects for over water channels are also addressed. Given the sparsity of the diffuse multipath components (MPCs) in the AG channels and generally short lifetime of these MPCs, the CIRs are modeled by the two-ray model plus intermittent 3rd, 4th or 5th “rays.” Models for intermittent ray probability of occurrence, duration, relative power, phase, and excess delay are provided. The channels at C-band and L-band were found to be essentially uncorrelated; this conclusion holds for the specific antenna locations used in our experiments (the aircraft underside), but is not expected to change for arbitrary antenna locations. For the aircraft antenna locations employed, intra-band signals are highly correlated, and this is as expected for channels with a dominant LOS component; analytical correlation computations show interesting two-ray effects that also appear in measurements. Multiple aircraft antennas and carefully selected locations are recommended for mitigating airframe shadowing for the CNPC link. Future work for AG channel modeling includes characterization of L-band delay dispersion and L-band TDL models, estimation of building and/or tree shadowing for small UAS that fly at very low altitudes, evaluation of multiple ground site(s) antenna diversity, and AG channel modeling via geometric techniques, e.g., ray-tracing

Classification and comparison of massive MIMO propagation channel models

Considering great benefits brought by massive multiple-input multiple-output (MIMO) technologies in Internet of things (IoT), it is of vital importance to analyze new massive MIMO channel characteristics and develop corresponding channel models. In the literature, various massive MIMO channel models have been proposed and classified with different but confusing methods, i.e., physical vs. analytical method and deterministic vs. stochastic method. To have a better understanding and usage of massive MIMO channel models, this work summarizes different classification methods and presents an up-to-date unified classification framework, i.e., artificial intelligence (AI)-based predictive channel models and classical non-predictive channel models, which further clarify and combine the deterministic vs. stochastic and physical vs. analytical methods. Furthermore, massive MIMO channel measurement campaigns are reviewed to summarize new massive MIMO channel characteristics. Recent advances in massive MIMO channel modeling are surveyed. In addition, typical non-predictive massive MIMO channel models are elaborated and compared, i.e., deterministic models and stochastic models, which include correlation-based stochastic model (CBSM), geometry-based stochastic model (GBSM), and beam domain channel model (BDCM). Finally, future challenges in massive MIMO channel modeling are given

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