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A measurement setup including millimeter-wave and ultra wideband transceivers mounted on both a customized UAV and a ground station and a measurement procedure for full 3D wireless propagation analysis is described in this work. The custom-made developed system represents a flexible solution for the characterization of wireless channels and especia...
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Context 1
... UAV represents the backbone of the air station and consists of a quadcopter drone specifically designed by [25] and customized for wireless channel measurement (Fig. 2). The drone frame is mainly made of carbon fiber, in order to limit the weight to 4 kg at most -measurement equipment included. A metal landing skid is present on the bottom side to let the UAV safely rest on ground, whereas the UAV control units -e.g. the telemetry and remote-control boards and the GPS receiver -are placed on the ...
Citations
... GHz 2.408-2.44 GHz [78], [89], [90], [93], [95], [100], [107], [116] [55], [87], [91], [92], [98], [101], [105], [118], [113], [116], [ [23], [52], [98] [98], [99], [110][111][112], [115] 24-29.5 GHz [99], [102] 60.48 GHz 60.48 GHz 128/250 MHz 128/250 MHz [22], [61] [48] [63], [82], [85], [86], [88] [63], [82], [85], [86], [88] Therefore, the frequency selection for UAV channel sounder system should be associated with specific application scenarios at the aforementioned and some other potential frequency bands. Wireless channel characteristics have been proved to change along with different frequency bands [128]- [130], [132]. ...
... Generally, the UAV channel measurements under most frequency bands are still insufficient. In addition, it can be found that UAV channel measurements at millimeter wave (mmWave) bands [98], [99], [110]- [112] are still in their early infancy compared with those at sub-6 GHz bands. ...
... Another option for the UAV channel sounder includes the portable signal generator (as an aerial transmitter) [34] and the portable spectrum analyzer or network scanner (as an aerial receiver) [82], [110], [112]. The portable signal generator is a suitable instrument as the aerial transmitter, which can generate some built-in waveforms as well as load customized sounding signals. ...
Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications, where a stable communication link is vital for safe flight control and robust data transmission. To develop a reliable UAV communication system, it is necessary to deeply understand the UAV channel characteristics and establish accurate channel models. Channel sounding is the most effective way to obtain realistic channel characteristics and validate the theoretical channel model. However, the studies on UAV channel sounding are still insufficient in terms of system design and data processing due to the complexity of developing a UAV channel sounder. Different from the terrestrial channel sounders, the implementation of a UAV channel sounder is tortured by the limited battery life and payload capacity of the UAV platform. The sounding scheme and data post-processing also need to be specially designed for highly dynamic UAV channels. So far, most existing survey studies on UAV channels focus on modeling methodology and model presentation. To fill this gap, this paper provides a comprehensive survey on the design of the UAV channel sounder, in terms of the hardware scheme, sounding signal, time synchronization, calibration, and data postprocessing. Current issues and potential research topics behind existing sounding technologies and measurement campaigns are analyzed. Moreover, future challenges and open issues are also discussed.
... In [18], UAVs are used to measure the Reference Signal Received Power (RSRP) of a single eNodeB in LTE band 20 to carry out spatial analysis of the fading effect. In [19], UAVs are used to characterize 3-D wireless propagation of 27 and 38 GHz frequency millimeter waves(mmWaves). A UAV-based channel measurement system with spectrum analyzer was created in [20] that can be used to carry out interference studies and link budget calculation. ...
This paper presents a measurement methodology
for obtaining a high-resolution beam pattern of 5G active
antenna systems (AASs) using Unmanned Aerial Vehicles
(UAVs). Beam pattern measurements are typically conducted
in an anechoic chamber by placing the active antenna at the
center and radiation pattern is measured at various angles.
This approach is limited by the spatial constraints of the
chamber and is time-consuming for obtaining high-resolution
measurements. To address this problem, UAVs equipped with
measurement sensors are proposed to fly around the antenna
and do the measurement campaign. The beam pattern measurement
campaign problem is formulated into a UAV path planning
problem. Horizontal circular arcs at various elevation angles are
defined on a sphere centered at the antenna and connected at
their ends alternatively to define a reference path and transcribe
it into a reference trajectory for the UAV. A chattering-free
super-twisting controller is designed to accurately track this
trajectory against unknown matched disturbances and model
uncertainties. The proposed methodology is validated by an
indoor experiment with a horn antenna set up to operate in
the frequency range of a 5G AAS and create a stationary beam.
A universal software radio peripheral is mounted on a UAV and
programmed to measure the received signal strength indicator
in real time and a high-resolution beam pattern is satisfactorily
captured.
... Due to high flexibility and low cost, unmanned aerial vehicles (UAVs) have been widely used in various civil and military fields, such as aerial base stations, emergency communication, and post-disaster relief, etc. [1][2][3][4]. A deep understanding of channel knowledge in the UAV communication environment is of great significance for the reliable UAV-related communication [5][6][7][8][9][10][11]. Channel measurement is an important method to obtain channel knowledge in real communication scenarios [12][13][14][15][16][17]. However, it can only obtain the channel knowledge at a specific location, and is not suitable for the large-scale propagation environment. ...
With the fast development of unmanned aerial vehicles (UAVs), reliable UAV communication is becoming increasingly vital. The channel knowledge map (CKM) is a crucial bridge connecting the environment and the propagation channel that may visually depict channel characteristics. This paper presents a comprehensive scheme based on a UAV-assisted channel measurement system for constructing the CKM in real-world scenarios. Firstly, a three-dimensional (3D) CKM construction scheme for real-world scenarios is provided, which involves channel knowledge extraction, mapping, and completion. Secondly, an algorithm of channel knowledge extraction and completion is proposed. The sparse channel knowledge is extracted based on the sliding correlation and constant false alarm rate (CFAR) approaches. The 3D Kriging interpolation is used to complete the sparse channel knowledge. Finally, a UAV-assisted channel measurement system is developed and CKM measurement campaigns are conducted in campus and farmland scenarios. The path loss (PL) and root mean square delay spread (RMS-DS) are measured at different heights to determine CKMs. The measured and analyzed results show that the proposed construction scheme can effectively and accurately construct the CKMs in real-world scenarios.
... In [9] the authors investigated short range UAV communication in the 3.1 − 4.8 GHz bands. A similar analysis was carried out in [10] for an urban environment, where building reflections were taken into consideration. The works [11] and [12] explored the performance of UAVs connecting to 5G macrocells and small cells, respectively, in urban environments. ...
Unmanned Aerial Vehicles (UAVs) are a disruptive technology that is transforming a range of industries. Because they operate in the sky, UAVs are able to take advantage of strong Line-of-Sight (LoS) channels for radio propagation, allowing them to communicate over much larger distances than equivalent hardware located at ground level. This has attracted the attention of organisations such as the Irish Defence Forces (DF), with whom we are developing a UAV-based radio relay system as part of the MISTRAL project. This relay system will support digital Very High Frequency (VHF) band communication between ground personnel, while they are deployed on missions. In this paper we report on the initial set of experimental measurements which were carried out to verify the feasibility of VHF signal relaying via UAV. In our experiments, a UAV carrying a lightweight Software-Defined Radio (SDR) receiver is positioned at a height of 500 meters above ground, while two 5W transmitters travel in vehicles on the ground. The SDR receiver measures the received signal power, while the Global Positioning System (GPS) coordinates of the vehicles are logged. This is combined to measure the signal pathloss over distance. Our results show that the signal is received successfully at distances of over 50 kilometers away. While the signals still appear to suffer from a degree of obstacle blockage and multipath effects, these communication ranges are a substantial improvement over the ground communication baseline, and validate the use of UAVs to support wide area emergency communication.
... The quadcopter market has recently gained a lot of prominence and has found a range of applications in domestic as well as in commercial areas [1]. Drones can carry out various high-frequency measurements [2] including far-field, near-field measurements, mobile network testing, interference hunting, direction finding, imaging, etc. [3]. In a recent study, unmanned aerial vehicles (UAVs) have been employed to conduct measurements and characterize the radiation patterns of low-frequency antennas in the presence of interfering sources [4]. ...
... More specifically, one long-range rangefinder is adopted for landing and retaining a minimum safety distance from the ground, while the rest are low range and utilized solely for landing. Unlike the other works in the field [102], we focus on protecting the whole system's integrity, and for this reason, we present the design of the aircraft on top of which we developed our novel algorithms. Finally, a set of experiments are conducted to evaluate the optimal tradeoff between the detection speed and accuracy of the obstacles in the aircraft's view and the surface's suitability in an emergency landing. ...
Unmanned aerial vehicles (UAVs) are at the forefront of this century’s technological shift, becoming ubiquitous in research and market areas. However, as a UAV navigates autonomously, there are unanticipated occasions, e.g., collisions with dynamic obstacles or loss of data provided by the global navigation satellite system, where the aircraft has to change its mission plans. In particular, to be protected from possible accidents, the platform’s geofence protection system should adjust the trajectory appropriately when obstacles are detected and select the proper ground surface when emergency landing is prompted. As these processes require fast reaction times, utilizing low latency sensors and algorithms is necessary. This article proposes a complete and low-complexity geofence protection system for recognizing moving objects and assessing the ground surface’s suitability using onboard sensing and processing modules. The proposed system is implemented on a novel fixed-wing UAV, designated as MPU RX-4, which features an unconventional flying wing layout and vertical take-off and landing (VTOL) capabilities. Our system is based on a forward-facing laser imaging, detection, and ranging (LIDAR) sensor and three downward-facing laser range-finders. We take advantage of the high-precision distance measurements and operational speed to identify moving obstacles using the LIDAR module, while the ground’s slope and the existence of any obstacle therein are computed through the range-finders. First, the article describes the UAV design procedure and its aerodynamic performance characteristics, which allowed us to evaluate our approach on a testbed aircraft. Then, the evaluation protocol shows that our system can perform robustly and under real-time constraints reaching an overall latency of only 165.5 ms, sufficient for reliable detection and avoidance of moving obstacles.
With the rapid development and broad applications of unmanned aerial vehicle (UAV)-based wireless stations in the sky, fundamental understanding and characterization of the realistic air-to-ground (A2G) communication link properties are crucial. In this article, a UAV-aided channel sounder with a real-time processing hardware system is developed for highly dynamic and nonstationary A2G channel measurements. In the hardware system, a global positioning system (GPS)-based triggering signal is designed, the equivalent antenna pattern affected by the UAV airframe is considered, and an appropriate sounding signal is selected, to improve the accuracy of measured channel impulse response (CIR). Moreover, real-time hardware processing algorithms for raw channel data, that is, CIR extraction, system response elimination (SRE), power loss recovery (PLR), and adaptive multipath component (MPC) recognition are developed and implemented on a single field-programmable gate array (FPGA) chip. In this way, the required storage size of channel data and the processing time for one slice of CIR is greatly decreased, which can meet the requirement of nonstationary A2G channel measurement with a high sampling rate and long-time measurement. A commercial channel emulator is used to reproduce controllable channels and verify the performance of the developed channel sounder. Finally, the developed channel sounder is applied to carry out A2G measurement campaigns at 3.5 GHz in a campus scenario. The channel characteristics, that is, path loss (PL),
$K$
-factor, and path angle are analyzed. The measured channel characteristics are consistent with existing measurements under a similar scenario. The estimated path angles are also validated by the theoretical results. Thus, the channel sounder can be used to capture the nonstationary A2G channel characteristics for the system design and algorithm optimization of A2G communications.
The incorporation of unmanned aerial vehicles (UAVs) based nodes into upcoming and future wireless communications has recently become a substantial field of research. Consequently, problems related to spectrum utilization optimization and network coexistence have also gathered attention. Radio Environment Maps (REM) have been established as an important tool for spectrum usage analysis, and thus, their construction via UAVs has been explored by a number of influential studies. This paper provides a review of these works, on the basis of which, it describes the relevant challenges and procedures of performing real-time volumetric (i.e. in three-dimensional space) UAV-based measurements for aerial communications, and analysis of the gathered data in the temporal, frequency and spatial domains. These guidelines facilitate the construction of REMs as well as the further investigation for simulation-based spectrum management algorithms.
