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. 2018 Oct 21;18(10):3571.
doi: 10.3390/s18103571.

Flying Ad Hoc Networks: A New Domain for Network Communications

Antonio Guillen-Perez, Maria-Dolores Cano  1
Affiliations

Flying Ad Hoc Networks: A New Domain for Network Communications

Antonio Guillen-Perez et al. Sensors (Basel). .

Abstract

The advent of flying ad hoc networks (FANETs) has opened an opportunity to create new added-value services. Even though it is clear that these networks share common features with its predecessors, e.g., with mobile ad hoc networks and with vehicular ad hoc networks, there are several unique characteristics that make FANETs different. These distinctive features impose a series of guidelines to be considered for its successful deployment. Particularly, the use of FANETs for telecommunication services presents demanding challenges in terms of quality of service, energy efficiency, scalability, and adaptability. The proper use of models in research activities will undoubtedly assist to solve those challenges. Therefore, in this paper, we review mobility, positioning, and propagation models proposed for FANETs in the related scientific literature. A common limitation that affects these three topics is the lack of studies evaluating the influence that the unmanned aerial vehicles (UAV) may have in the on-board/embedded communication devices, usually just assuming isotropic or omnidirectional radiation patterns. For this reason, we also investigate in this work the radiation pattern of an 802.11 n/ac (WiFi) device embedded in a UAV working on both the 2.4 and 5 GHz bands. Our findings show that the impact of the UAV is not negligible, representing up to a 10 dB drop for some angles of the communication links.

Keywords: WiFi; drone; flying ad hoc network (FANET); mobility models; positioning algorithms; propagation models; radiation pattern; unmanned aerial vehicle (UAV).

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Conflict of interest statement

The authors declare no conflicts of interest

Figures

Figure 1
Figure 1
An example of communication links in a FANET using the 5 GHz band for U2U communication and the 2.4 GHz band for U2G coverage.
Figure 2
Figure 2
Pure randomized mobility trajectories: (a) Random Walk mobility model where each node selects a random direction [0, 2π) and speed S [Smin, Smax] that is maintained for a predefined time interval t or a constant distance d (500 × 500 m, t = 5 s); (b) Random Waypoint (Tpause = 3 s); (c) Random Direction, as in RWP but the node searches the edge point of the simulation area; and (d) Manhattan Grid with example of an urban scenario with 16 horizontal and 16 vertical streets.
Figure 3
Figure 3
Time-Dependent mobility trajectories: (a) Boundless Simulation Area, (b) Gauss-Markov, and (c) Smooth Turn.
Figure 4
Figure 4
Path-Planned mobility trajectories: (a) Semi-Random circular mobility model; (b) Paparazzi autopilot UAV Movements (Stay-At, Eight, Way-Point, Scan, and Oval); and (c) PPRZM state machine.
Figure 5
Figure 5
Column mobility models: (a) Example of a single step in PSMM; (b) Trajectory simulation using RPGM.
Figure 6
Figure 6
Column mobility models: (a) Example of a single step in CLMN where each node has its reference point and reference points are placed on a reference line that moves a distance d and rotates an angle θ; (b) Trajectory simulation of three nodes using CLMN where reference points randomly move through the simulation area and each node moves randomly around its reference point.
Figure 7
Figure 7
Column mobility models: (a) Example of a single step in Nomadic Community (NC) with five nodes where the nodes have a maximum distance rmax to move away from the reference point and the reference point moves through the simulation area a random distance d following a randomized model; (b) Trajectory simulation of three nodes using NC.
Figure 8
Figure 8
Column mobility models: (a) Example of a single step in PRS with a target node (black) moving a distance d and it is pursued by five purser nodes (white); (b) Trajectory simulation of a target node and three pursuer nodes using PRS.
Figure 9
Figure 9
UAV and WiTi device.
Figure 10
Figure 10
Experimental testbed elements (DUT ≡ Device Under Test ≡ UAV + WiTi device).
Figure 11
Figure 11
Planes under study.
Figure 12
Figure 12
Example of a measurement of the complete radiation pattern and example of possible areas of interest for each communication link, which are highlighted in green for the U2U link and yellow for the U2G link: (a) X Plane, (b) Y Plane, and (c) Z Plane.
Figure 13
Figure 13
The best antenna configurations of the WiTi as seen from above: 2.4 GHz band for the U2G link with APA-M25 antennas in horizontal position with 90° between them and 5 GHz band for the U2U link with ARS-NT5B antennas in vertical position.
Figure 14
Figure 14
Radiation pattern of the isolated WiTi using the antennas configuration shown in Figure 13 in the U2G link working in 2.4 GHz: (a) X Plane, (b) Y Plane, and (c) Z Plane.
Figure 15
Figure 15
Radiation pattern of the isolated WiTi using the antennas configuration shown in Figure 13 in the U2U link working in 5 GHz: (a) X Plane, (b) Y Plane, and (c) Z Plane.
Figure 16
Figure 16
Influence of the UAV on the radiation pattern in: (a) 2.4 GHz band and X Plane, (b) 2.4 GHz band and Y Plane, (c) 5 GHz band and X Plane, and (d) 5 GHz and Y Plane.
Figure 16
Figure 16
Influence of the UAV on the radiation pattern in: (a) 2.4 GHz band and X Plane, (b) 2.4 GHz band and Y Plane, (c) 5 GHz band and X Plane, and (d) 5 GHz and Y Plane.
Figure 17
Figure 17
Radiation pattern of the WiTi on-board the UAV for the antennas configuration shown in Figure 13 in the U2G link working in 2.4 GHz: (a) X Plane, (b) Y Plane, and (c) Z Plane.
Figure 18
Figure 18
Radiation pattern of the WiTi on-board the UAV for the antennas configuration shown in Figure 13 in the U2U link working in 5 GHz: (a) X Plane, (b) Y Plane, and (c) Z Plane.
See this image and copyright information in PMC

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