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Using Unmanned Aircraft Systemsfor Mobile Network Verifications
Marjo Heikkila, Marjut Koskela, Tero Kippola,Mahmut Kocak, Juha Erkkila
Centria University of Applied SciencesYlivieska, Finland
Email: [email protected]
Jouni TervonenUniversity of Oulu
Kerttu Saalasti InstituteNivala, Finland
Email: [email protected]
Abstract—This study presents the usage of unmannedaircraft for site survey and antenna pattern measurementsin-situ in mobile networks. The site survey is one partof the verification and optimization process of the networkoperator. Mobile network operators’ responsibility is to en-sure the broadly available, reliable network series that areessential for customer experience. Technically that meansmobile network coverage of the desired area without holesand with good capacity. The operator performs networkplanning in order to optimize coverage and capacity. It isessential to know the antenna pattern to plan and design aneffective and efficient mobile network. Antenna manufac-turers provide antenna radiation patterns measured in thestandard anechoic chamber. Understanding how real siteimplementation differs from the laboratory measurementsis also crucial. This study focuses on developing in-situantenna measurements for the antenna patterns recordedin the laboratory. The evaluation of antenna radiationpatterns in a real environment will provide additionalinformation about what kind of effect the antenna sitemast, installation, and antenna performance parameterswill have on the theoretical radiation pattern.
I. INTRODUCTION
This paper illustrates the development of the practi-cal 3D measurement method for mobile networks. Thecomplexity of future networks will increase becausethey consist of many different technologies and frequen-cies. When the complexity of networks increases, thecritical verification of the network performance in-situalso becomes increasingly challenging. The increasingdemand for high reliability and availability of networksmeans that a network must be verified with testing. Thefield testing with smart-phone and measurement softwareis one method of producing practical knowledge ofmobile technologies. This method usually provides onlya 2D view of the network performance. Field testing istypically conducted with a car. Future mobile technolo-gies will utilize 3D beamforming. In 3D beamforming,the beam can be steered horizontally and vertically.In addition to steering the beam, the tilt and azimuthcan also be changed dynamically by using adaptiveantennas. With all these adjustments, network throughputcan be improved. When these antenna features are stud-ied, it is also necessary to study network performance
in both horizontal and vertical dimensions. Using anUnmanned Aircraft System (UAS) in testing providesnew possibilities to perform network measurements, itenables actual on-site 3D beamforming measurementsand allows to perform measurements automatically. AnUnmanned Aerial Vehicle (UAV) enables measurementsto be taken from different elevation angles. UAV alsomakes it possible to measure in rough terrain or areaswithout roads; compared to traditional field testing, onecan operate a UAV where humans or cars cannot go.
UASs are becoming popular for professional use be-cause of the easily operated and cost-efficient aerialtechnology. A battery-powered UAV equipped with aGlobal Positioning System (GPS) and suitable measure-ment equipment is capable of gathering data from theair. They are commonly used for aerial photography andsurveys. This study focuses on how UASs can be usedin an efficient way for mobile network site surveys andnetwork verification.
The Section I introduces a developed measurementmethod, which can increase the effectivity of verifyingfuture mobile networks. The related work is described inSectionII. The measurement environment and equipmentare presented in Section III. The measurement setup isshown in Section IV. Section V describes the measure-ments and methods. The results are shown in Section VI.The conclusions are drawn, and future work is discussedin Section VII.
II. RELATED WORK
Traditionally, the antenna characterization measure-ments, i.e., the evaluations of the antenna radiation pat-terns, are performed either indoors in anechoic chambersor in specific outdoor antenna measurement ranges. Inrecent years, the in-situ antenna measurements utilizingUASs have aroused scientific interest, e.g., [1], [2], [3],and [4]. The obvious advance of in-situ measuring isthat it enables analyses of antenna radiation patterns inrealistic conditions, and takes into account the influenceof the surrounding environment when measuring theradiation pattern via multipath contributions from theground and surrounding structures. A perfect example of
the latter is the experiment wherein an UAS was used formeasuring a circular azimuthal path with a 20◦ elevationangle of a log-periodic antenna at 433MHz mounted ona ship [1].
An interesting practical example demanding UAS-based antenna measurement was introduced in [2] forthe radio-astronomical usage of the Square KilometerArray (SKA) project. In the SKA experiment, even thesmall subarray was found to be too large to be measuredin an anechoic chamber, requiring the development ofan in-situ measurement. To prepare the SKA measure-ments, several experiments from single antennas (e.g.,[5] and [6]) to a 3x3-aperture array of Vivaldi antennaelements were conducted [7]. Another example of radio-astronomical use was introduced in [8] where theypresented the results of the UAS-based measurementsof a calibration dipole verifying the UAS method forcalibrating the radio arrays used in astronomy.
Antenna radiation pattern measurements were success-fully performed in Australia using UAS in the far fieldof “live” broadcast antennas using ultra high frequency(UHF) and very high frequency (VHF) digital televisionsystems [9]. Beyond the examples conducted with eitherVHF or UHF bands, Duthoid et al. [3] reported in-situ antenna characterization measurements performedin super high frequency (SHF) band at 9.8GHz. Thissystem is aimed at radar systems where the in-situantenna includes undesirable reflections, diffraction, andother external sources of contamination. The antenna issurrounded by other elements such as radome, tower, andlightning protection. Additionally, ground irregularitiesfrom geography and weather conditions that are differentfor each site impact the performance of radars.
Although it has no direct impact on the measurementcase presented in this paper, the literature review ofUAV antenna measurements revealed a limiting factor,one which is worth mentioning. In cases of very largeantenna arrays, the far field range is too large forpractical measurements with small UAV with limitedflight time and clear visibility requirements. To overcomesuch limitations, a method including the near field to farfield transformation allowing shorter UAS flights in thenear field was introduced in [4]. The methodology wasvalidated with measurements in UHF and SHF bands, at2950MHz and 4650MHz.
UASs have been used in the context of mobile networkcharacterization of 3D RF fields in [10] although thescope was not primarily the antenna radiation pattern.The measurements were performed mostly 500m awayfrom the base station antenna and the goal was to suggestpotential improvements in the speed and accuracy ofmulti-node radio network planning and the deploymentof hastily-formed (e.g., emergency) networks, and gen-eral network design and optimization. To the best of ourknowledge, this is the first scientific article where UAS
was used for 3D antenna measurement with the mobilenetwork besides a Finnish language Bachelor level thesiswork in [11].
III. MEASUREMENTS OF THE ENVIRONMENT ANDSYSTEM TESTS
When the radiation pattern of the antenna is studiedin 3D, several issues must be taken into account. Thesystem parameters must be known beforehand whenmeasurements are planned, as the test environment aswell as weather conditions can effect the measurements.
A. Test Environment
The study was performed in the field trial environ-ment of Centria University of Applied Sciences. Thisenvironment covers approximately 4 km2 area in a ru-ral/suburban environment of Ylivieska, Finland. Cho-sen as eNodeB (eNB) for these measurements was thePuuhkala site. That site has the most versatile antennatechniques available in the trial environment. The sitehas a self-supporting mast, which means that there areno supporting wires around the mast. The antenna mastis located at small hill surrounded by pine trees. Reportedantenna installation height in the mast is 42m andthe total height of the mast is 60m. Figure 1 showsthe Puuhkala site and the environment around it. Themeasurements took place in clear weather where thetemperature was around 15 ◦C and wind speed was 1–4m/s. These conditions were beneficial also for the UASoperation; both wind and rain create a risky environmentfor the flight.
B. Antenna
In the measurement configuration, an antenna with anoperating frequency band of 1710MHz to 2180MHzwas used in 2.1GHz Long Term Evolution (LTE) band1 with 5MHz bandwidth operated from Puuhkala eNB.Antenna is commercial quad port Remote ElectricalDowntilt (RET) compatible antenna with a 65◦ hori-zontal beamwidth [12]. The antenna length is 1300mmand the width is 300mm. Figure 2 and 3 presentmanufacturer’s antenna patterns with 8◦ downtilt.
Fig. 1. Aerial view of the Puuhkala site.
Fig. 2. Manufacturer’s horizontal pattern.
Fig. 3. Manufacturer’s vertical pattern.
Different mechanical properties, such as antenna in-stallation and mast structure, can affect the radiationpattern. In our case, the antenna was installed so thatthe mechanical tilt was approximately 4◦ and the antennaRET was set to 4◦ to get the desired 8◦ downtilt.
C. Key Performance Indicators in LTE
In an LTE network, in addition to the obstacles suchas trees and buildings between the antenna and UserEquipment (UE), the distance between eNB and theequipment also affects the throughput. The effective useof dynamic modulation and a coding scheme results inhigh data rates and capacity when the UE is locatednear the eNB. Using UAV as a testing platform gives usnew possibilities and opportunities to measure the perfor-mance parameters of an LTE cell, including ReferenceSignal Received Power (RSRP), Reference Signal Re-ceived Quality, downlink throughput, Reference Signal- Signal to Noise Ratio (RS-SNR), and Transmit Powervalues in a real-time environment.
To enhance communication performance via the useof spatial diversity and spatial multiplexing in data trans-mission, the Multiple-Input Multiple-Output (MIMO) ra-dio technology, which utilizes multiple antennas at both
the transmitter and receiver, is used [13]. This technologyhas an impact on the RSRP pattern because the RSRPand Signal to Noise Ratio are proportional to each otheron average. In our case, the Spatial Multiplexing OpenLoop MIMO (SM OL MIMO) was active in the eNBduring the measurement. Polarization diversity was used.
As a Key Performance Indicator (KPI) of an antenna,RSRP is one of the basic physical layer measurements.RSRP is critical because it represents the linear averageof the downlink reference signals of a given channelwidth enabling coverage area evaluation of the LTE cell.Additionally, there is certainly a correlation betweenRSRP and RS-SNR the user plane Quality of Service(QoS).
IV. MEASUREMENT SETUP
The measurement setup includes all the componentsused in operation, both on the ground and in the air (Fig.4). A UAV with the test device was operated from theground level. A suitable ground control station [14] wasused to operate the UAV with automatic mode and aUAV controller was used to fly manually when needed.
A. Test Device
When using the UAV for measurement purposes, thepayload in the UAV must be light to minimize the take-off weight. In this case, the used payload i.e., UE, wasa commercial mobile phone with suitable measurementsoftware [15]. More detailed information about the testdevices can be found in Table I. During the measure-ment, the UE was fastened to the UAV with an adjustableholder. While the UAV was flying around the eNB’santenna, the UE collected data.
All mobile phones have a unique radiation pattern.At the beginning of the study, the antenna radiationpattern of the UE was measured in the anechoic chamber.The measurement did not examine the influence ofthe UAV on the radiation pattern. Based on the UE’santenna radiation pattern results, we determined the mostsuitable position for the UE, where both the vertical andhorizontal patterns had a wide enough angle area with aflat gain, and the gain was sufficient. Radiation pattern
Fig. 4. Measurement setup in use.
TABLE I. Test devices
ROLE EQUIPMENT SPECS
UAS UAV Drone DJI S900 (incl. GPS)Ground Station SW UgCS Desktop applicationGround Station HW Laptop ComputerRemote Controller Futaba T14SG
UE Test SW Nemo HandyTest Device Sony Xperia X
results revealed that the most suitable position of the UEwas the vertical tilt at 45◦. The UE was facing the eNBantenna in vertical position rotated 45◦ to the left whilethe UAV flew around the eNB’s antenna.
B. Unmanned Aircraft System
The UAS used in these measurements was DJI S900Spreading Wings [16], which is a commercial aircraft forprofessional use. The diagonal wheelbase of the UAV is900mm and the total height is 730mm. In this trial,flight operations lasted approximately 15 minutes whenthe take-off weight with UE was 6.5 kg. Among otherfactors, the take-off weight is one of the issues that affectthe flight time of a UAV.
In order to use the UAS for radio frequency measure-ment purposes, a series of UAS regulations were studiedbeforehand. The Finnish Transport Safety Agency (Trafi)has defined these regulations [17] concerning UAS usagein Finland. These regulations may vary between differentcountries (like traffic regulations) [18] concerning UASs.In addition to the Finnish traffic regulations, specificpermission for the use of the mobile phone (UE) withthe UAS was needed from the Finnish CommunicationsRegulatory Authority. Each flight operation with a UASwas conducted under these regulations and precautions.
V. MEASUREMENT METHOD
The target for this study was the mobile network siteperformance and the antenna radiation pattern verifica-tion using the UAS. The UAS technology has elevatedthe possibility of developing field measurements closerto the antenna pattern measurements performed in thelaboratory. In the laboratory, antenna measurement de-vices have been designed to build a high-resolution 3Dscan of the antenna field pattern, using the ring-shapedelement that surrounds the transmit antenna which col-lects the data by rotating a few degrees in each scan.When the UAV is used as a measurement for the UEplatform, it provides the opportunity to collect real-timedata, using an almost perfect spherical shape, spatially.The spherical route will be beneficial in the analysisof data in case we compare the results from differentdirections and for further predictive approaches such asclustering or regression.
When the radiation pattern is studied, the signalstrength information at a constant radius is needed.
We defined the most suitable measurement points thatcan give accurate data about the radiation pattern ofthe antenna. One must consider issues concerning theenvironment, the measurement setup, and the systemunder the test. One of the measurement setup issuesthat has a substantial impact on the measurements is theflight time, and that is limited because of the battery-powered UAV. The flight time of the selected UAV was18 minutes, which restricts measurement time. Nationallimitations to UASs operations have to be taken intoaccount, such as a maximum flight altitude of 150 metersabove ground level. Antenna mast structure, surroundingbuildings, terrain height variations, or vegetation can alsolimit the measurement. In our case, the mast was self-supporting so there were no supporting wires on theflying route.
Antenna installation height was 42m, so the nationalmaximum flight limitation did not prevent measure-ments; however, the forest surrounding the site limitedmeasurements below the antenna. In order to find themost suitable measurement points and optimize thespherical route, while also minimizing the length of thecircumference of the circular paths, we defined our routein the far field area. Hence, in the far field the radiationpattern does not change shape as the distance increases.Equation 1 is to approximate the far field region:
R =2D2
λ(1)
Where D is the length of the antenna, λ is thewavelength, and R is the radius of the route. With theused antenna at 2100MHz this means that the far fieldstarts approximately from 23.5m. We chose the radiusof 25m for our measurement routes. We called thesecircular paths, forming a sphere, a target route. Eachcircle had its own height from the ground, defining thetilt of the UE. We have defined 26 different tilt angles for26 different circles, starting from a height of 22m fromthe ground. The distance between the eNB antenna andthe UE measurement was the same at each circle, andthis formed a spherical shape as shown in the Fig. 5. Afew circle layers were left out of planned measurementsfor safety reasons avoiding flying too close to obstacles.
In the measurements, the UAV flew around the eNBone circle at a time. In practice, the UAV with UE wasraised manually near the desired circular level, whereautomatic mode was turned on. The UAV flew aroundthe antenna at an even speed, which was approximately1 m/s. Depending on the radius of the circle, sampleswere collected in different amounts in different circularlayers. The UE gathered samples approximately every500 milliseconds. The measurement was performed inthe downlink direction. The UAV flew around the an-tenna in a complete circle with automatic mode and waslanded manually. In each circle, the predetermined angleof the UE was adjusted, and the UE pointed towards the
Fig. 5. Planned measurement points in spheres aroundthe antenna.
eNB’s antenna. The flight direction was the same for allcircles.
VI. RESULTS
The target was to visualize the results of the radiationpattern, depending on the received signal strength fromthe antenna. The signal strength needs to be plotted ata constant radius to make a diagram with the polarplot. The idea is to compose two separate graphs ofthe vertical plane and the horizontal plane. The mostimportant parameter to generate the patterns was signalstrength, RSRP value in this case. To form the correctradiation pattern, the distance between the UE and theantenna must be equal while flying. To achieve this theUAV flew a steady and near-perfect circle at differentheights. This required the information of the geographiclocation, given for example by the UE. Geographic loca-tion information includes latitude, longitude and altitudeparameters. These parameters give information wherethe RSRP value has been collected in three differentdimensions. During the study, we realized that UE’sGPS information is not accurate enough, especially thealtitude information. UAS demands reliable navigationand accurate GPS receiver for autonomous or semi-autonomous operation. We realized that we could utilizethe GPS data of the UAV in visualization. In theseresults, we have replaced UE GPS data with UAV GPSdata. Figure 6 presents the UAV route and measurementpoints with a point cloud.
RSRP values were recorded from the beginning of theflight until end of the flight. GPS time was needed todefine the starting point of the measured circular layer,while take-off and landing data was not included. Onlyvalues in a circle around the antenna have been includedwhen the pattern was generated. These measurement
Fig. 6. UAV flying route of one measurement flight.
points are green in Fig. 6. Filtered measurement pointsare red and blue.
The following mathematical operations were used inorder to plot the relationship between the signal strengthand the angle of the radius. First the RSRP resultswere interpolated. Since the spherical route with theinitial point grid was not dense enough, we improved thegrid using linear interpolation. This method utilizes low-degree polynomials in each of the intervals. It selects thepolynomial pieces, so they fit smoothly together. Afterinterpolation, RSRP values were averaged. The values ofnine points were averaged, four values before and afterthe measurement point.
Finally, from the processed measurement data, thehorizontal and vertical planes of radiation pattern wereplotted (Fig. 7 and 8). The measurement data wascompared with the antenna manufacturer’s information(Fig. 2 and 3).
As the mast structure and the placement of the antennain the mast may affect antenna’s electrical properties,
Fig. 7. Measured horizontal pattern.
Fig. 8. Measured vertical pattern.
manufacturer’s antenna measurements can vary frommeasurements carried out after the installations. In ourcase, the measured radiation pattern corresponded to themanufacturer’s reported pattern quite well.
The major difference in the horizontal plane betweenthe radiation patterns was the width and direction ofthe main beam. The UAS measured the half powerbeam width (HPBW) of the horizontal plane, whichwas approximately 55◦; in the antenna specifications,the HPBW is 64◦. The downtilt configuration could beone issue to cause a difference in radiation patterns. Inthe measurements, the combination of the mechanicaltilt and the electrical tilt was used. The manufacturergives a radiation pattern with only the electrical tilt inuse. It was noticeable that the measured main beamwas asymmetrical. Another cause of the differences wasmost probably the antenna mast structures. The measuredUpper Sidelobe Level Suppression (USLS) was 14 dB,and in the antenna specifications the USLS was 18 dB.The measured front-back ratio at 180◦ was 30.7 dB,while in the antenna specification the front-back ratiowas 30 dB. The major difference in the vertical planewas the number of the sidelobes. The measured radiationpattern consisted of less sidelobes than the manufac-turer’s reported one. The measured sidelobes had widerlobe width compared with the antenna specifications.
VII. CONCLUSION AND FUTURE WORK
The original target of the study was to find out ifa UAS could be part of the optimization process usedby mobile network operators to ensure a good customerexperience. A new method of measurement needed to bedeveloped for mobile network testing with UAS. Whenthe method was developed, many technical, safety, andeven regulatory issues had to be considered. BecauseUAV does data gathering measurements from the air,the vertical dimension also needed to be considered inthe measurement result analysis.
The study revealed that the UAS suits the mobile net-work site performance and antenna radiation pattern ver-
ification measurements. Antenna pattern measurementwith the UAS helped to understand how real site imple-mentation affects the patterns measured in the laboratoryenvironment. In our study, the measured radiation patterncorresponded to the manufacturer’s reported pattern quitewell.
The main conclusion of the study is that using UAS fortesting brings new possibilities to performing networkmeasurements and enables actual 3D beamforming mea-surements of future mobile networks. UAS also enablesthe measurements to be done automatically which havenot been possible in traditional network measurementswhile using a car. We were able to measure the beam,even when steered with different tilt and azimuth angles.Future studies will consider further development of themeasurement and visualization of the 3D radiation pat-tern. Repeated 3D study is important for future networksnot only because of emerging 3D beamforming but alsobecause it can be seen that UAS data services demanda different type of mobile network design.
ACKNOWLEDGMENT
This work has been carried out using the frameworkof the IMAGE 5G project [19]. The authors would liketo acknowledge the IMAGE 5G research consortiumconsisting of the Centria University of Applied Sciences,Nokia, PehuTec Oy, Siipotec Oy, Pohjonen Group Oy,the Finnish Communication Regulatory Authority, theFinnish Meteorological Institute, and Business Finland– The Finnish Funding Agency for Innovation.
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