Becker, Dennis

Fiebig, Uwe-Carsten

Schalk, Lukas Marcel

English

Institute of Transport Research:Publications

Wideband Channel Measurements and FirstFindings for Low Altitude Drone-to-Drone Links inan Urban ScenarioDennis Becker, Uwe-Carsten Fiebig and Lukas SchalkInstitute of Communications and NavigationGerman Aerospace Center (DLR)Oberpfaffenhofen-Wessling, Germanydennis.becker@dlr.deAbstract—In order to prevent collisions between unmannedaerial vehicles (UAVs), Drone-to-Drone (D2D) communication isa promising technology for enabling reliable collision avoidancesystems. For a high reliable communication system accuratechannel models, specifically designed for UAVs in typical en-vironments, are needed. Especially, the urban environment forsmall sized UAVs in very low level (VLL) airspace is chal-lenging due to rich multipath propagation and non line-of-sight (NLOS) conditions. In order to model the real worldpropagation behavior, channel measurements with small UAVsin different urban scenarios are mandatory. So far, no widebandchannel model based on measurements for D2D communicationhas been proposed. Therefore we conducted channel measure-ments with our MEDAV RUSK-DLR channel sounder witha 100 MHz bandwidth sounding signal at 5.2 GHz and twoflying hexacopters. A key feature in our D2D wideband channelmeasurement campaign was the use of optical fibers. In thispaper, we present the scenarios of our campaign and show firstfindings. By applying a geometrical signal path simulation weidentify multipath component (MPC) sources. The measurementsreveal that the D2D MPC scenario is clearly three-dimensional.Index Terms—Unmanned Aerial Vehicle, Air-to-Air, Propa-gation, Drone-to-Drone Communication, Channel Measurement,SimulationI. INTRODUCTIONIn the near future, the number of UAVs in VLL airspace isexpected to increase significantly due to manifold applicationslike inspection of critical infrastructure, parcel delivery or airtaxis. In the longterm we foresee a UAV-to-person ratio ofaround one, resulting in densities of hundreds of airborneUAVs per square kilometer in cities during rush hours. Fora safe integration of UAVs into urban airspace, high reliablecollision avoidance systems are mandatory. We are convincedthat D2D communication is a promising approach for sharinginformation on UAV trajectories in a reliable manner andwith very low latency. We expect that D2D communicationchannels for UAVs exhibit rich multipath characteristics inthree dimensions and, thus, may be even more challengingthan vehicular channels. Channel measurements are inevitablein order to derive accurate channel models for D2D commu-nication links.A propagation measurement campaign with small 1 sizedUAVs is a big challenge since we have strong limitations onthe payload in terms of size, weight and power consump-tion. Thus sophisticated wideband D2D channel measurementsare difficult to achieve as long as transmitter and receiverequipment is carried by UAVs. Consequently, only large-scale parameters have been investigated so far for the D2Dchannel with small sized UAVs with IEEE802.11 radios [1]and IEEE802.15.4 radios [2]–[4].Another challenge is to fly UAVs in urban scenarios indifferent heights and close to buildings. These scenarios are ofgreat interest, but to our knowledge they have not yet been thesubject of a propagation measurement campaign. Therefore,other methods have been applied so far to gain a first under-standing about the D2D channel: [5] describes the propagationcharacteristics of the air-to-air (A2A) channel in an urbanenvironment with a ray-tracing simulation considering large-scale parameters.To overcome the payload limitations of small UAVs, weproposed a measurement setup that extends the operation ofchannel sounding equipment by exploiting analog optical linksto send the channel sounding signal to the drone. [6]. Withour MEDAV RUSK-DLR channel sounding equipment and theproposed extension we conducted D2D channel measurementsat 5.2 GHz with 100 MHz bandwidth for urban scenarios. Theused frequency band has been chosen since the future controland non payload communication (CNPC) link is planned tooperate in the C-band (5.03 GHz to 5.091 GHz) [8].The objective of this paper is to give an overview aboutall scenarios of our D2D channel measurement campaign.Furthermore we will present first findings of one of theassessed scenarios where two hexacopters fly between build-ings at different heights. In order to understand where themany multipath signals originate from, we also derive thegeometrical signal paths of all major MPCs based on the exacttrajectories of the involved UAVs and the three-dimensional1The classification small is typically used for UAVs, which weigh less than25 kilogram [7].Fig. 1. Overview of the measurement setup.layout of the scenario.II. MEASUREMENT CAMPAIGN DESCRIPTIONWith our proposed channel sounding setup in [6] we con-duct D2D channel measurements with different scenarios atour site in Oberpfaffenhofen Germany, which provides anurban scenario with tall buildings standing close by. For thecampaign we identified different environments and scenariosdescribed further in II-A. The overall goal of this campaignis to characterize the specific large-scale and small-scalecharacteristics for the D2D communication channel betweensmall UAVs in an urban environment and to identify and locatepossible MPCs in the three-dimensional layout.We have already carried out several test flights with twohexacopters and recorded preliminary measurement data inorder to evaluate our hardware setup and the flight behaviorof our UAVs. In this work we use these measurements toinvestigate first MPC sources.A. Planned ScenariosWe conduct measurements at three different environmentsat our site that allow for different scenarios with line of sight(LOS) and NLOS conditions at different heights, speedsand trajectories. Figure 2 illustrates the environments A, Band C with the planned flight paths for the drones. We areconsidering following scenarios.A1 - Horizontal Flight with LOS Condition: In thisscenario at environment A, one drone flies horizontally online path AP1 at constant height, while the other dronehovers at fixed position at point path AP2. Thereby thedrones are always in LOS. With this scenario, we tested ourhardware setup and evaluated the flight behavior of the dronewhen flying at relatively low height between a narrow urbancanyon with a width of approximately 7 m, which is the mostchallenging flight mission in our our campaign.A2 - Horizontal Flight with NLOS Condition: In thisscenario at environment A, one drone flies horizontally online path AP1 at constant height, while the other drone flieshorizontally on line path AP3. Thereby the drones are alwaysin NLOS condition as the view is obstructed by the buildingin between.A3 - Collision Course at Corner: For Scenario A3 onedrone flies path AP1, while the other drone flies at path AP4.Thereby the drones fly towards and away from each otherwith changing LOS conditions.A4 - Balcony: For Scenario A4 one drone is placed on abalcony of building B103 at point AP6, while the other droneflies at path AP5 over the building and along path AP4.B1 - Horizontal Flight with LOS Condition: In thisscenario at environment B, one drone flies horizontally atpath BP3, while the other drone hovers at point BP2. Thebuilding close by offers an interesting surface due to bigwindow shutters for sun protection.B2 - Vertical Flight in Courtyard: In this scenario atenvironment B, one drone flies horizontally at path BP3,while the other drone flies vertically at point BP1 down andup in an inner courtyard.C1 - Horizontal Fast Flight with Changing Environment:For Scenario C1 one drone flies path CP1 horizontally,while the other drone hovers at points CP2 and CP3. Thisenvironment allows for higher velocities of the drones due tomuch more open space.B. Measurement SetupOur measurement setup consists of seven basic compo-nents shown in figure 1. We are using two custom-build DJIS900 hexacopters that are connected to our MEDAV RUSK-DLR channel sounder [9] via 600 m long optical fibers. Byguiding the sounding signal trough optical fibers we extendthe operation of our channel sounder and enable widebandchannel measurements between flying drones. In [6] we pro-posed a channel sounding setup and explain our equipmentin more detail. Table I summarizes important parameters. Weare transmitting an OFDM-like multitone signal at 5.2 GHzwith 100 MHz bandwidth and 30 dBm power over omni-directional linear polarized dipole antennas. The receiving andtransmitting antennas are vertically aligned and placed at thebottom of the drones. In order to precisely navigate the drones,a RTK system, consisting of a static basestation on the groundand receivers on the drones, was used. Our flight trials revealedthat a single GNSS solution on the drones is insufficient forautonoumusly flying waypoint missions safely at lower heightsbetween the buildings. For an accurate position tracking of thedrones we use two Leica TCRP1201 total stations that allow usto track them with position uncertainties of a few centimetersdepending on the speed of the drones. The Leica stations aretracking prisms attached on the bottom of the drones, wherethey can be seen from the Leica stations at ground during the(a) Environment A(b) Environment B(c) Environment CFig. 2. Three environments for several measurement scenarios with plannedflight paths for the drones.flight. The Leica stations must be placed carefully in order toensure LOS condition for the whole measurement and to keepthe angular velocity as small as possible, as it is restricted dueto mechanical limits.C. First MeasurementsFor first experiences with our setup we started with mea-surements for the described scenario A1 at two differentheights. Figure 3 illustrates the planned waypoint missions andTABLE ICHANNEL SOUNDING PARAMETERParameter Symbol ValueCenter frequency fc 5.2 GHzBandwidth B 100 MHzTx Power Ptx 30 dBmSignal duration Tp 12.8 µsSignal period Tg 1.024 msMax resolvable doppler frequency fdmax 488 HzADC resolution resadc 8 bitDynamic range αagc 52 dBAntenna Tx omni-dir. V-pol. 0 dBiAntenna Rx omni-dir. V-pol. 0 dBithe tracked positions for the drones as well as for the Leicastation positions. In the first measurement the drones flew bothat about 30 m height above ground level, which is higher thanthe surrounding buildings. In the second measurement theyflew at about 15 m height, which is below the rooftops.For the two scenarios (A1 at height 15 m and 30 m),figures 5a and 6a show the channel impulse responses forboth flights. In both figures the strong LOS signal can beclearly seen. It’s delay increases and decreases constantly asthe moving drone flies towards and away from the hoveringdrone. Furthermore strong reflections from MPCs with longand short life times can be seen. In the following we investigatethese MPCs and describe possible sources.III. GEOMETRICAL SIGNAL PATH SIMULATIONIn order to understand the channel impulse characteristics oftwo measurements explained in II-C, we simulate geometricalsignal paths based on the exact trajectories of the UAVs and thethree-dimensional layout of the scenario A1 with all buildingsclose by (B102, B103, B104, B160). Figure 4 illustrates themodeled environment with the tracked trajectories of bothFig. 3. Flight trial for D2D channel measurement. In this scenario UAV1flies a line mission 65 m in an urban canyon two times back at 15 m height.UAV2 hovers at same height and is always in LOS.Fig. 4. Modeled simulation environment with buildings close by in scenarioA1 and tracked drone positions when flying at 15 m and 30 m height.UAVs and both flights (blue: 15 m and red: 30 m height)in the local Cartesian coordinate system.For every measured position of the UAVs we estimate thedelays and the received signal power relative to the LOS signalfor several signal paths with single and double reflections onthe building and ground surfaces. Then we compare the resultswith the measurements. For the delays we assume speed oflight and calculate the geometrical distances of the reflectedsignal path on the surfaces with the well known two-rayground reflection model and apply it for the vertical surfaces ofthe buildings as well. The double bounce propagation distancesare calculated by mirroring the signal source points at one ofthe two involved surfaces as virtual signal sources. For thereceived signal powers we only assume free space path lossand do not consider losses by different reflection coefficientsas the results shall only help to identify the MPCs. For bettercomparison with the measurements, we quantize the resultswith the same signal period time and delay resolution.In addition we show possible sources for the MPCs notassumed a priori by calculating the MPC regions with samesignal delays and intersecting them with satellite maps. Forthis we simply assume all MPCs located horizontally on anellipse around the transmitter and receiver as foci points likedone in [10].IV. RESULTS AND COMPARISONFig. 5b and 6b show the results of the estimated channelimpulse response over time by simulation. The simulated longlife-time reflections can be found in the measurements, but donot explain all the reflections that are visible. They are namedafter the sources of the reflections, which are the surroundingbuildings (B102, B103, B104 and B160) as well as the groundsurface (GREF). There are single bounce (SREF) and doublebounce (DREF) propagations on the surfaces. The strong LOScomponent can be seen very clearly with a linear increasingand decreasing delay as the receiving drone moves down andup the corridor at constant speed.In both measurements there are two stronger reflections thatwere not estimated by simulation. They are clearly visible infig. 6b at around 460 ns and 510 ns around minute 3, whenthe flying drone is at it’s furthest distance to the hoveringdrone. In order to estimate possible locations for the origins(a) Measured channel impulse response over time with received powerrelative to LOS signal power .(b) Estimated channel impulse response over time by simulation .Fig. 5. Flight scenario A1 at 30 m height.of these reflections, we plotted the regions in yellow of samesignal delays around the receiver in fig. 7 on a satellite-map.For the indicated yellow regions we then identified the redregions as possible MPC sources of the reflections as thereare steel beams on the rooftop of building 160 that intersectwith the yellow regions. Also the steady increasing delay insame manner as the LOS delay shows, that the MPCs mustbe located somewhere in the opposite of the flight direction.When comparing the two different measurements, it can beseen that all reflections at the grounds surface show differentdelays as the height of the drones is different in both cases.Delays of the single bounce propagations on the buildingsurfaces stay nearly the same. Furthermore the flight scenarioA1 at height 30 m shows a reflection from a higher part ofthe roof of building B102 (102 2 SREF) that is not present atheight 15 m. This is simply because this surface is not in LOSfor the signal receiving drone at lower heights. The reflectionsresulting from building B104 are visible if not overlaid bystronger reflections.(a) Measured channel impulse response over time with received powerrelative to LOS signal power .(b) Estimated channel impulse response over time by simulation .Fig. 6. Flight scenario A1 at 15 m height.V. CONCLUSION AND OUTLOOKIn this work we showed first findings of wideband channelmeasurements for low altitude D2D links in an urban sce-nario. We identified most of the MPC sources by comparingthe measurements with simulations of the three-dimensionallayout and recorded flight tracks of the drones. The resultsreveal a rich multipath environment that is clearly three-dimensional. MPCs are identified from reflections on thesurrounding buildings and the grounds surface. Even doublebounce propagations are visible in the measurements andstrong reflections from good reflectors like metallic objects ona rooftop. In the next we will further investigate the D2D com-munication channel with the different measurement scenariosdescribed for our measurement campaign and extend the MPCidentification and localization in the three-dimensional space.ACKNOWLEDGMENTThe authors thank all colleagues at Institute of Communica-tions and Navigation, German Aerospace Center, who helpedto perform several flight trials.Fig. 7. Possible MPC regions of same signal delays at 510 ns and 460 nsaround the receiver RX. Red regions illustrate the assumed origins of thesignal reflections.REFERENCES[1] N. Goddemeier and C. Wietfeld, Investigation of air-to-air channelcharacteristics and a UAV specific extension to the rice model, in Proc.IEEE Globecom Workshops, San Diego, CA, USA, Dec 2015, pp. 15.[2] N. Ahmed, S. S. Kanhere, and S. Jha, On the importance of link char-acterization for aerial wireless sensor networks, IEEE CommunicationsMagazine, vol. 54, no. 5, pp. 5257, May 2016.[3] Jude Allred, Ahmad Bilal Hasan, Saroch Panichsakul, William Pisano,Peter Gray, Jyh Huang, Richard Han, Dale Lawrence, and KamranMohseni. 2007. SensorFlock: an airborne wireless sensor network ofmicro-air vehicles. In Proceedings of the 5th international conference onEmbedded networked sensor systems (SenSys ’07). ACM, New York,NY, USA, 117-129.[4] Apratim Shaw and Kamran Mohseni, A fluid dynamic based coordi-nation of a wireless sensor network of unmanned aerial vehicles: 3-Dsimulation and wireless communication characterization,IEEE SensorsJ., Special Issue on Cognitive Sensor Networks, 722–736, 2011[5] Zhou, L., Yang, Z., Zhao, G., Zhou, S., Wang, C-X. (2019). PropagationCharacteristics of Air-to-Air Channels in Urban Environments. In 2018IEEE Global Communications Conference (GLOBECOM) [8647360](Global Communications Conference (GLOBECOM)).[6] Becker, Dennis and Schalk, Lukas , Enabling Air-to-Air WidebandChannel Measurements between Small Unmanned Aerial Vehicles withOptical Fibers, AIAA/IEEE 38th Digital Avionics Systems Conference,DASC 2019, 9. -12.September, San Diego, USA.[7] Federal Aviation Administration, Operation and Certification of SmallUnmanned Aircraft Systems, accessed: 2019-07-07. [Online]. Available:https://www.faa.gov/uas/media/RIN 2120-AJ60 Clean Signed.pdf[8] B. Kerczewski, Spectrum for UAS control and non-payload communica-tions, in Proc. IEEE Integrated Communs., Navigation and SurveillanceConf. (ICNS), 2013, pp. 121[9] Medav, MEDAV RUSK Channel Sounder,http://www.channelsounder.de/.[10] Rashdan, Ibrahim und Ponte Mueller, Fabian und Jost, Thomas undSand, Stephan (2019), Measurement-based Geometrical Characterizationof the Vehicle-to-Pedestrian Channel, EuCAP2019, 31,March-05. April.2019, Krakow, Poland

Wideband Channel Measurements and First Findings for Low Altitude Drone-to-Drone Links in an Urban Scenario

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Wideband Channel Measurements and First Findings for Low Altitude Drone-to-Drone Links in an Urban Scenario

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