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

Channel Modeling and Characteristics for 6G Wireless Communications

[EN] Channel models are vital for theoretical analysis, performance evaluation, and system deployment of the communication systems between the transmitter and receivers. For sixth-generation (6G) wireless networks, channel modeling and characteristics analysis should combine different technologies and disciplines, such as high-mobil-ity, multiple mobilities, the uncertainty of motion trajectory, and the non-stationary nature of time/frequency/space domains. In this article, we begin with an overview of the salient characteristics in the modeling of 6G wireless channels. Then, we discuss the advancement of channel modeling and characteristics analysis for next-generation communication systems. Finally, we outline the research challenges of channel models and characteristics in 6G wireless communications.This research was supported by the National Key R&D Program of China under grant 2018YFB1801101; the National Nature Science Foundation of China (No. 61771248 and 61971167); the Jiangsu Province Research Scheme of Nature Science for Higher Education Institution (No. 14KJA510001); and the Open Research Fund of the National Mobile Communications Research Laboratory, Southeast University (No. 2020D14).Jiang, H.; Mukherjee, M.; Zhou, J.; Lloret, J. (2021). Channel Modeling and Characteristics for 6G Wireless Communications. IEEE Network. 35(1):296-303. https://doi.org/10.1109/MNET.011.200034829630335

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

A three dimensional MIMO channel model for unmanned Aerial vehicle in urban environments

Increasing the availability of Unmanned Aerial Vehicles (UAV's) platforms leads to a variety of applications for aerial exploration, surveillance, and transport. Many of these applications rely on the communication between the UAV and the ground receiver which is subjected to high mobility that may lead to restrictions on link connectivity and throughput. In order to design high throughput and efficient communication schemes for these scenarios, a deep understanding of the communication channel behavior is required, especially taking into account measurement data from flight experiments. Channel propagation in urban environments involves diffraction effects which modify the Line-of-Sight (LoS) contribution of the total received signal, especially when the receiver is located on the ground. This process leads to scenarios where Multiple-Input Multiple-Output (MIMO) signal processing can take advantage from this situation. In this context, the goal of this paper is to study the diffraction effects of the LoS component through spatial correlation metrics of the signal. To accomplish this, we propose the use of a geometric stochastic technique to model the channel behavior which lies between High Altitude Platforms (HAP) and terrestrial link communications.Fil: Mendoza, Horacio Aurelio. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Corral Briones, Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Estudios Avanzados en Ingeniería y Tecnología. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Estudios Avanzados en Ingeniería y Tecnología; Argentin

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