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 FOR FIFTH GENERATION CELLULAR NETWORKS AND WIRELESS SENSOR NETWORKS

In view of exponential growth in data traffic demand, the wireless communications industry has aimed to increase the capacity of existing networks by 1000 times over the next 20 years. A combination of extreme cell densification, more bandwidth, and higher spectral efficiency is needed to support the data traffic requirements for fifth generation (5G) cellular communications. In this research, the potential improvements achieved by using three major 5G enabling technologies (i.e., small cells, millimeter-wave spectrum, and massive MIMO) in rural and urban environments are investigated. This work develops SPM and KA-based ray models to investigate the impact of geometrical parameters on terrain-based multiuser MIMO channel characteristic. Moreover, a new directional 3D channel model is developed for urban millimeter-wave (mmW) small cells. Path-loss, spatial correlation, coverage distance, and coherence length are studied in urban areas. Exploiting physical optics (PO) and geometric optics (GO) solutions, closed form expressions are derived for spatial correlation. Achievable spatial diversity is evaluated using horizontal and vertical linear arrays as well as planar 2D arrays. In another study, a versatile near-ground field prediction model is proposed to facilitate accurate wireless sensor network (WSN) simulations. Monte Carlo simulations are used to investigate the effects of antenna height, frequency of operation, polarization, and terrain dielectric and roughness properties on WSNs performance

Caching-Aided Collaborative D2D Operation for Predictive Data Dissemination in Industrial IoT

Industrial automation deployments constitute challenging environments where moving IoT machines may produce high-definition video and other heavy sensor data during surveying and inspection operations. Transporting massive contents to the edge network infrastructure and then eventually to the remote human operator requires reliable and high-rate radio links supported by intelligent data caching and delivery mechanisms. In this work, we address the challenges of contents dissemination in characteristic factory automation scenarios by proposing to engage moving industrial machines as device-to-device (D2D) caching helpers. With the goal to improve reliability of high-rate millimeter-wave (mmWave) data connections, we introduce the alternative contents dissemination modes and then construct a novel mobility-aware methodology that helps develop predictive mode selection strategies based on the anticipated radio link conditions. We also conduct a thorough system-level evaluation of representative data dissemination strategies to confirm the benefits of predictive solutions that employ D2D-enabled collaborative caching at the wireless edge to lower contents delivery latency and improve data acquisition reliability

The COST IRACON Geometry-based Stochastic Channel Model for Vehicle-to-Vehicle Communication in Intersections

Vehicle-to-vehicle (V2V) wireless communications can improve traffic safety at road intersections and enable congestion avoidance. However, detailed knowledge about the wireless propagation channel is needed for the development and realistic assessment of V2V communication systems. We present a novel geometry-based stochastic MIMO channel model with support for frequencies in the band of 5.2-6.2 GHz. The model is based on extensive high-resolution measurements at different road intersections in the city of Berlin, Germany. We extend existing models, by including the effects of various obstructions, higher order interactions, and by introducing an angular gain function for the scatterers. Scatterer locations have been identified and mapped to measured multi-path trajectories using a measurement-based ray tracing method and a subsequent RANSAC algorithm. The developed model is parameterized, and using the measured propagation paths that have been mapped to scatterer locations, model parameters are estimated. The time variant power fading of individual multi-path components is found to be best modeled by a Gamma process with an exponential autocorrelation. The path coherence distance is estimated to be in the range of 0-2 m. The model is also validated against measurement data, showing that the developed model accurately captures the behavior of the measured channel gain, Doppler spread, and delay spread. This is also the case for intersections that have not been used when estimating model parameters.Comment: Submitted to IEEE Transactions on Vehicular Technolog

Reconfigurable antennas and radio wave propagation at millimeter-wave frequencies

For the last decades we have been witnessing the evolution of wireless radio networks. Since new devices appear and the mobile traffic, as well as the number of users, grows rapidly, there is a great demand in high capacity communications with better coverage, high transmission quality, and more efficient use of the radio spectrum. In this thesis, reconfigurable antennas at micro- and millimeter-wave frequencies and peculiar properties of radio wave propagation at mm-wave frequencies are studied. Reconfigurable antennas can improve radio link performance. Recently, many different concepts have been developed in the reconfigurable antenna design to control the antenna bandwidth, resonant frequency, polarization, and radiation properties. In the first part of the thesis, we investigate mechanically tunable antennas operating at microwave frequencies with the ability to change the shape of the conductor element and, consequently, to control the radiation properties of the antenna. Also in the first part, we study conformal antenna arraysfor 60 GHz applications based on cylindrical structures. Beam switching technology is implemented by realizing several antenna arrays around the cylinder with a switching network.Scanning angles of +34˚/-32˚ are achieved. Moreover, it is vital to study radio wave propagation peculiarities at mm-wave frequencies in indoor and outdoor environments to be able to deploy wireless networks effectively. The propagation part of the thesis focuses on several aspects. First, we investigate how the estimation of optimum antenna configurations in indoor environment can be done usingrealistic propagation models at 60 GHz. Ray tracing simulations are performed and realistic human blockage models are considered. Second, we present the results from a measurement campaign where reflection and scattering properties of two different built surfaces are studied in the millimeter-wave E-band (71-76 and 81-86 GHz). Next, we present a geometry based channel model for a street canyon scenario, using angular-domain measurement results to calculate realistic power angular spectra in the azimuth and elevation planes. Then, we evaluate propagation effects on the radio channel on the rooftop of the buildings bymeasurements and simulations. We have used unmanned aerial vehicles and photogrammetrytechnique to create a highly accurate 3D model of the environment. Based on a comparison of the measured and simulated power delay profiles, we show that the highly accurate 3D modelsare beneficial in radio wave propagation planning at mm-wave frequencies instead of using simple geometrical models

Map-Aware Models for Indoor Wireless Localization Systems: An Experimental Study

The accuracy of indoor wireless localization systems can be substantially enhanced by map-awareness, i.e., by the knowledge of the map of the environment in which localization signals are acquired. In fact, this knowledge can be exploited to cancel out, at least to some extent, the signal degradation due to propagation through physical obstructions, i.e., to the so called non-line-of-sight bias. This result can be achieved by developing novel localization techniques that rely on proper map-aware statistical modelling of the measurements they process. In this manuscript a unified statistical model for the measurements acquired in map-aware localization systems based on time-of-arrival and received signal strength techniques is developed and its experimental validation is illustrated. Finally, the accuracy of the proposed map-aware model is assessed and compared with that offered by its map-unaware counterparts. Our numerical results show that, when the quality of acquired measurements is poor, map-aware modelling can enhance localization accuracy by up to 110% in certain scenarios.Comment: 13 pages, 11 figures, 1 table. IEEE Transactions on Wireless Communications, 201

Evaluation of mmWave 5G Performance by Advanced Ray Tracing Techniques

Technological progress leads to the emergence of new concepts, which can change people’s everyday lives and accelerate the transformation of many industries. Among the more recent of these revolutionary concepts are big data analysis, artificial intelligence, augmented/virtual reality, quantum computing, and autonomous vehicles. However, this list would be incomplete without referring to fifth-generation (5G) technology, which is driven by several trends. First, the exponential growth of the worldwide monthly smartphone traffic up to 50 petabytes during the next three years will require the development of mobile networks supporting high datasharing capabilities, excellent spectral efficiency, and gigabits per second of throughput. Another trend is Industry 4.0/5.0 (also called the smart factory), which refers to advanced levels of automation requiring millions of distributed sensors/devices connected into a scalable and smart network. Finally, the automation of critical industrial processes, as well as communication between autonomous vehicles, will require 99.999% reliability and under 1 ms latency as they also become the drivers for the emergence of 5G. Besides traditional sub-6 GHz microwave spectrum, the 5G communication encompasses the novel millimeter-wave bands to mitigate spectrum scarcity and provide large bandwidth of up to several GHz. However, there are challenges to be overcome with the millimeter-wave band. The band suffers from higher pathloss, more atmospheric attenuation, and higher diffraction losses than microwave signals. Because the millimeter-wave band has such a small wavelength (< 1 cm), it is now feasible to implement compact antenna arrays. This enables the use of beamforming and multi-input and multi-output techniques. In this thesis, advanced ray tracing methodology is developed and utilized to simulate the propagation mechanisms and their effect on the system-level metrics. The main novelty of this work is in the introduction of typical millimeter-wave 5G technologies into channel modelling and propagation specifics into the system-level simulation, as well as the adaptation of the ray tracing methods to support extensive simulations with multiple antennas