measuring a lora network - diva portal1219450/fulltext01.pdf · measuring a lora network...

Thesis no: MCS-20YY-NNURI: urn:nbn:se:bth-16344

Measuring a LoRa NetworkPerformance, Possibilities and Limitations

Robin Franksson

Alexander Liljegren

Faculty of ComputingBlekinge Institute of TechnologySE-371 79 Karlskrona, Sweden

This thesis is submitted to the Faculty of Computing at Blekinge Institute of Technology inpartial fulfillment of the requirements for the bachelor degree in Software Engineering. Thethesis is equivalent to 10 weeks of full-time studies.

Contact Information:Author(s):Robin FrankssonE-mail: [email protected]

Alexander LiljegrenE-mail: [email protected]

University advisor:Anders CarlssonDept. Computer Science & Engineering

Faculty of Computing Internet : www.bth.seBlekinge Institute of Technology Phone : +46 455 38 50 00SE–371 79 Karlskrona, Sweden Fax : +46 455 38 50 57

Abstract

The main goal of this thesis is to highlight the various limitations that the LP-WAN LoRa and by proxy other similar technologies currently suffers from to givefurther insight into how these limitations can affect implementations and prod-ucts using such a network. The thesis will be supported by experiments that testhow a LoRa network gets affected by different environmental attributes such asdistance, height and surrounding area by measuring the signal strength, signal tonoise ratio and any resulting packet loss. The experiments are conducted usinga fully deployed LoRa network made up of a gateway and sensor available to thepublic.

To successfully deploy a LoRa network one needs to have concrete informationabout how to set it up depending on different use cases as battery lifetime anda solid connection has to be kept in mind. We test the various performanceaspects of a LoRa network including signal quality and packet loss at differentcommunication ranges. In addition to that we also test different environmentsand investigate how these can impact the performance.

The conclusions made in this thesis are that a LoRa network is limited in itsuse cases for smaller scale projects with low gateway elevation that still requirea large distance. This is due to the obstruction of the signal quickly making itreach unusable levels at roughly 300m in a city and 600m in a forest. Making theline of sight free either by elevation of the hardware or by adapting to the terrainmakes the network perform very well making the possibility for packet loss lowerwhich in combination with the low duty cycle of the transmissions is needed asevery packet lost is going to be very noticeable.

Keywords: LoRa, LPWAN, IoT, Transmission Range, Arduino, Raspberry Pi

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Contents

Abstract i

Glossary iii

1 Introduction 1

2 Research Background 32.1 Wireless communication for IoT . . . . . . . . . . . . . . . . . . . 32.2 LPWAN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.3 LoRa & LoRaWAN . . . . . . . . . . . . . . . . . . . . . . . . . . 52.4 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.5 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.6 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . 72.7 Hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3 Literature Review 9

4 Research Method 124.1 Literature Study . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.2 Empirical Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4.2.1 Case Study Topology . . . . . . . . . . . . . . . . . . . . . 124.2.2 Components setup . . . . . . . . . . . . . . . . . . . . . . 134.2.3 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . 15

5 Results and Analysis 205.1 Experiment - Open space . . . . . . . . . . . . . . . . . . . . . . . 205.2 Experiment - Dense forest . . . . . . . . . . . . . . . . . . . . . . 225.3 Experiment - Urban city . . . . . . . . . . . . . . . . . . . . . . . 245.4 Experiment - Gateway elevation . . . . . . . . . . . . . . . . . . . 26

6 Conclusion and Future work 286.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

References 30

Appendix 31

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Glossary

SS Chirp - Chirp Spread Spectrum (A spread spectrum technique that uses wide-band linear frequency modulated chirp pulses to encode information and allowsimultaneous low-data-rate transmission from several users.)

OFDMA - Orthogonal Frequency-Division Multiple Access (Multi-user versionof the popular orthogonal frequency-division multiplexing(OFDM) digital modu-lation scheme.)

NB - Narrow Band (Focuses specifically on indoor coverage, low cost, long batterylife, and enabling a large number of connected devices. The NB-IoT technologyis deployed “in-band” in spectrum allocated to Long Term Evolution(LTE))

PRR - Packet Reception Rate (The % of sent packets that actually reach thereceiver)

RSSI - Received Signal Strength Indication (Measurement of the power presentin a received radio signal, a value closer to 0 dBm is better.)

SNR - Signal-to-noise ratio (Defined as the ratio of a signals power to the powerof the noise, a value greater than 0 dB indicates more signal than noise)

Duty Cycle - The % of time that a device is transmitting signals of a certaintime period i.e. a device that transmits data 2 time units every 10 time units hasa duty cycle of 20%

Ton - Time on air (The package transmission time i.e. the time the packageis "in the air")

SF - Spreading Factor (LoRa operates with spread factors from 7 to 12. SF7is the shortest time on air, SF12 will be the longest. Each step up in spreadingfactor doubles the time on air to transmit the same amount of data.)

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Chapter 1Introduction

The interest and applications for IoT (Internet Of Things) has in recent yearsincreased significantly, in just a couple of years tens of billions of different kindof machines are estimated to be connected[1]. Most of these devices will be de-ployed in WAN(Wide Area Network) solutions. This introduced a demand fornew communication standards that targets the key features needed to deploy thetechnology in society such as low power consumption and long range coverage.This led to the creation of LPWANs (Low Power Wide Area Network) which isdesigned for low bit rate long range communication. The goal is to replace devicesthat today rely on cellular communications like GSM or 4G at a higher cost andpower consumption with new ones that adapt this low bit rate communicationstyle to provide battery lifetimes up towards 10 years while maintaining a com-munication range of ∼30km under optimal circumstances.

Due to the technology being new and not thoroughly fleshed out together withbeing accessible and completely open to the public this thesis will have a fo-cus on measuring and evaluating one of these LPWAN technologies in particularnamely, LoRa and its communication protocol LoRaWAN. Currently the researchon LoRa is very limited and mainly focused on how certain factors like tempera-ture, humidity and precipitation affect the maximum range and battery life whilethe research on how a LoRa network actually performs and what its limitationsare is limited mostly to simulations and theories. In this thesis we hope to providefurther insight over how these limitations affect possible use cases by showing sig-nal quality, signal-to-noise ratios and packet loss in various environmental areas.

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Chapter 1. Introduction 2

Chapter 2 describes the background for the work and provides an overview ofthe current technologies used for IoT. It also attempts to give further insight intoLPWANs.

Chapter 3 presents the literature review and considers previous research onLoRa detailing the reasoning for its development, its use cases and how certainenvironmental conditions affect signal quality and packet loss.

Chapter 4 presents research method and explains our planned experiments in-cluding the setup and specification of the hardware used and describing the en-vironmental conditions for each experiment.

Chapter 5 illustrates our results with graphs detailing the signal quality, signal-to-noise ratio and packet loss. Also includes an analysis of these results and howthey can affect certain use cases of LoRa.

Chapter 6 summarizes our findings for the performance measurement and detailshow the found restrictions affect the value of a LoRa network implementation. Italso presents future work and limitations in our research and explains the workneeded to confirm and/or continue the findings presented in this thesis.

Chapter 2Research Background

2.1 Wireless communication for IoTCurrently in the world a great variation of technologies is used for IoT whereeach is made to fit a certain niche. For our "smart homes" we use WiFi whenpossible and Bluetooth when not. A relatively new candidate however which isused for several home products is ZigBee which low power and low range is aperfect fit for tools like home automation i.e. lighting, temperature, security andsensors. As distance increases the possibilities of using such technologies getslimited since both WiFi and ZigBee are limited to ∼100m, so for products thatrequire a higher range the cellular networks like GSM up to 5G are used, thesehowever come at a heavy price in both licensing costs and battery lifetime.[2] Theinterest in adding this missing piece in radio communication technologies led tothe creation of LPWANs. A comparison of the trade-offs in range and data ratefor the various technologies can be seen in figure 2.1.

Figure 2.1: Data rate vs. range capacity of radio communication technologiesReprinted from:[1]

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Chapter 2. Research Background 4

2.2 LPWANLPWAN or Low-Power Wide-Area Network is an umbrella term for technologiesthat focus on having very high power efficiency while maintaining a high trans-mission range, to meet this goal a sacrifice in data rate is made. The goal of thesetechnologies is to fit the niche of products that require long battery lifetime, havelow duty cycles and require medium to long range[3]. Examples of such productscan be agriculture and industrial sensors, another product is the extension ofthe "smart home" into smart cities where things like traffic and parking can beimplemented with long lifetime sensors that can say the number of parking spotsthat are open or when to empty trashcans. There are several variations of theseLPWAN modulations such as SS Chirp, OFDMA and NB. A comparison of thesemodulations can be seen in figure 2.2 where most of them have unique aspectswhich make them fit for a particular use case. This thesis will have a focus onone of them in particular, namely LoRa.

Figure 2.2: High level comparison between different technologies competing inthe LPWAN space.

Retrieved from:https://lora-alliance.org/sites/default/files/2018-04/what-is-lorawan.pdf

https://lora-alliance.org/sites/default/files/2018-04/what-is-lorawan.pdf


2.3 LoRa & LoRaWANLora is a wireless modulation technology, the physical layer to connect things toa gateway. In a sense similar to how WiFi can connect your laptop to an accesspoint i.e. the link layer between your laptop and the router. LoRa is extremely lowbandwidth and battery consumption with a link-budget that is typically around155 dB. Also similar to WiFi Lora operates on the license-free ISM bands howeverat a lower frequency, for example it is 433MHz for Asia, 868MHz for Europe and915MHz for North America. It is also regulated by standards for transmissionwith regional variations. For Europe these restrictions are:[4].

• Transmission power (14dB)

• Duty-cycle (<1%)

• Bandwidth (125kHz)

Lora uses the communication protocol LoRaWAN. So again, using the WiFi anal-ogy, if LoRa is the WiFi connection, LoRaWAN is the IP protocol. It is intendedprimarily for wireless long battery time devices and targets key points of Inter-net of Things such as mobility, localization and bi-directional communication.The architecture of a LoRaWAN network is typically laid out in a star-of-starstopology where gateways act like bridges relaying messages between the end-point devices and a central network server[5]. Devices in a LoraWAN networkare remote objects that can range from anything between a thermometer to ageolocation based tracking system as can be seen in figure 2.3.

Figure 2.3: LoRa network structureReprinted from:[6]


2.4 PurposeThe purpose of our work is to determine how performance of a LoRa network(range,signal quality and packet loss) is affected by placement. Another goal is to discussthe trade-offs of using such a network in various environments.

By analyzing performance on the end-devices and gateways from a number ofdifferent perspectives we hope to bring some light over how these kind of systemsshould be set up to fit different use cases and also giving a hint to whether thetechnology is feasible given a specific use case.

2.5 ScopeAs outlined above this thesis will mainly be focusing on the performance of aLoRa network. The experiments conducted will provide information about howthe performance is affected by different kind of factors and how it varies from oneenvironment to another.

We are not taking varying weather conditions into account when performing theexperiments and analyzing the results. Although this could affect the results invarying degree, positive or negative. Our measurements will however be con-ducted in similar weather and temperature conditions throughout the test suiteto keep the results as consistent as possible between the different test cases.


2.6 Research QuestionsThe end objective with this study is to provide a better understanding as to howdifferent environmental variables affect the performance of a LoRa network andin turn provide well-grounded information as to how to deploy the network, orwhether to choose another IoT technology that might be better suited for thespecific use-case.

• RQ1: What limitations from a performance perspective and in respect toopen, dense forest and city environments does a LoRa network implementationcurrently suffer from?

As LoRa is a relatively new technology and not thoroughly fleshed out a break-down of what its current limitations are and how they affect different kind ofimplementations and use-cases needs to be performed in order to be able to makea well-grounded decisions before deploying the technology.

• RQ2: How does environment and placement affect signal strength betweengateways and end-nodes?

Since radio waves get affected to greatly varying degrees by which material thesignal has to travel through an investigation into how the environment betweenthe hardware limits a LoRa network and how it can be circumvented will giveinsight into how a deployment of the network should be carried out.

• RQ3: What are the aspects that affect package loss between end-nodes andgateways.

As radio transmitted communication can be very fluctuating in its performanceand affected by a multitude of environmental variables any resulting packet lossneed to be accounted for and analyzed. The importance of every packet reachingits destination is increased for LoRa networks as duty cycle regulations heavilylimit the amount of packets that can be sent.


2.7 HypothesisOur expectations about the results are based on the conclusions of other stud-ies. And also on the general specification of LoRa and LoRaWAN. We expect toget long-range coverage in all of the tests cases that we perform, with variationsbetween different environments. At increased altitude we expect to get a bettersignal and less packet loss.

In the tests conducted in free line of sight our expectation is that the RSSIvalues will not have any dramatic variations at different ranges but differ slightlythe further away the devices get from each other.

For the tests in urban environments we do not expect the range to be very high.We also think that the signal strength will vary greatly between distances as thesignal will have to travel through materials that we have no knowledge about.

We expect the range for the tests in the forest to be quite good. But also deviateslightly due to variables like terrain and big rocks etc in the vegetation.

In the tests conducted at different altitudes we expect that we will get an in-creasing signal quality the higher the gateway gets elevated. We also guess thatthe increase will decay after after the gateway reaches its "optimal" height, mean-ing that any further elevation serves no purpose for that particular device.

Furthermore, our expectation as to how placements of a gateway and end-nodedevices affect the performance in the deployment of a LoRa network is that itsvery important in order to ensure that all the data sent from the devices getsreceived. Especially considering that one device might only be sending data afew times every day.

Chapter 3Literature Review

By the year 2020 it’s approximated that more than 50 billion devices will beconnected to the internet[1], to solve the problem of an ever increasing batteryconsumption level a new technology was needed. The research of Centenaro in[7] describe how in 2009 led by the company SIGFOX there was a resurgence ofinterest for a new wireless telecommunication technology which was designed forlong range communication at a lower bit-rate compared to the commonly usedGSM and 3G. This technology came to be known as LPWAN (Low-Power Wide-Area Network) and it is today available in several forms including Chrip SpreadSpectrum (LoRA), Ultra Narrow Band (Sigfox, NB-IoT) and several others.

According to Mekki in article [1] many of these LPWAN technologies will havea share on the IoT market in the future as each of the technologies are more fitfor different use cases where some focus more on a higher battery lifetime whileothers on maximum range and throughput. A comparison is made for variouspossible implementations of LPWAN where use cases such as smart farming i.ehumidity, temperature and alkalinity sensors which heavily favors the LoRa andSigfox technologies as they do not rely on cellular coverage while applicationssuch as a retailers sale terminal require low latency as to not limit the number oftransactions, this makes a Narrow-Band implementation more attractive as theycan sacrifice power consumption for throughput.

Using these technologies comes with a great variation in performance as radiotransmitted signals at such a low frequency can suffer greatly at various environ-mental variables. This is shown by Cattani in [8] in their studies of how variablessuch as weather conditions, temperature, humidity and precipitation affect thereliability and performance of an LPWAN solution. The conclusion they reachis that the environment has to be considered greatly when choosing what tech-nology to use and if such an implementation is even feasible in the first place asa temperature change as low as from 20°C to 30°C can lead to 50% packet losswhich can be observed in figure 3.1. Cattani in [8] also shows that an increasein temperature by 10°C will reduce the RSSI by 1 dBm. The decrease in signalstrength caused by temperature change could in theory render a perfectly goodLoRa link unusable. Given a change in temperature from 15°C to 60°C wouldgive a 100% PPR reduced to 0%.

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Chapter 3. Literature Review 10

Figure 3.1: Increase of packet corruption and loss at higher temperatures (°C)on a LoRa link at the edge of the communication range.

Reprinted from:[8]

This aspect is also mentioned by Wennerström[9] in their long-term study ofmeteorological affects where they show that in Uppsala, Sweden the PRR canfluctuate more than 20% from day to night where a higher fluctuation is presentduring the dryer and hotter months June, July and August.

Another variable that can highly affect PRR is oversaturation of the networkas there is a large risk for package collision when several devices transmit radiosignals in the same time span. This is shown by Ferre[10] in his mathematicaltheory and simulation of approximated packet loss. The results show that usinga max Ton of 1s and a SF of 12 the probability of a packet being lost reaches 10%after just 200 devices. This means that a LPWAN is limited either in the amountof devices used in the network or by the importance of the information. To avoidthis network congestion a specification was created that recommends a limitationon the duty cycles for the signal transmissions where the maximum for the EUbands i.e 863-870MHz is 1% meaning a device is only allowed transmit a signalfor 1 time unit every 100 time units[11].

Petäjäjärvi in article[12] evaluates among other things how a LoRa network per-forms when end-node devices are mobile which could be a potential use-case.Using the LoRa modulation with SF=12 they place an end-node device in a carand then perform measurements as they are moving. Their results indicates thatmoving at speeds exceeding 40 km/h causes the communication performance todeteriorate while speeds around 25 km/h the communication is relatively reliable.They discuss that this behavior can be caused by the doppler effect and that lowerSF values could be less affected by it.

Chapter 3. Literature Review 11

As LoRa networks are open for anyone to use, many networks might be deployedin close proximity to one another. Neighboring networks introduces interference.Thiemo Voigh [13] investigates these interferences and how they can be avoidedusing directional antennae or multiple base stations. They show through simula-tions that neighboring networks impacts performance negatively due to interfer-ence especially when a lot of end-node devices are used. They use five independentnetworks with 200 end-node devices each. Only one of the networks is of interestand the others are there to produce interference. They conclude in their paperthat using directional antennae and focus the radiating energy towards the in-tended gateway improves on RSSI while at the same time reduces interferenceon the neighboring gateways. And therefore increases the performance on all theindividual networks. Although the directional antennae improves on performancethey also conclude that using multiple gateways gives a better result. Deployingmore gateways are economically an inferior choice, but might practically be abetter one.

Chapter 4Research Method

4.1 Literature StudyAs our thesis is focused primarily on the performance and limitations of a LoRanetwork our primary goal while searching for references is to find research papersand articles that discuss its limitations and the reasons behind them. We mainlyfocused on papers that performed live tests as simulations of a LoRa network isstill very inaccurate in respect to real values. We then aim to adapt our testbased on these limitations and reasons. We also searched for studies involvingthe performance of LoRa and IoT technologies in general with the goal of usingthem for comparisons.

4.2 Empirical Study

4.2.1 Case Study Topology

The first stage of setting up any network is to ensure the necessary componentsare configured correctly, this in turn will ensure the accuracy of the data collectedduring the investigation and analysis of the network. But as you will note a LoRanetwork is not too complicated to setup and run as there are very few componentsto configure.

Figure 4.1: The topology of the LoRa network used in this study

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Chapter 4. Research Method 13

4.2.2 Components setup

The end-node device and gateway are powered by portable power supplies. Theend-node device is configured to send a packet every 10 seconds on the 867.10- 868.50Mhz frequencies. The gateway receives and decodes the packet and theforwarder software forwards the packet to LORIOT.io for presentation on a PC.LORIOT.io is a cloud service that lets you access your gateways and extractinformation regarding your deployed networks [14].

End-node device

The end-node device would in a real world use-case have some kind of sensorattached to it and its purpose is to collect sensor data and then send it to thegateway. In our case for the sake of the experiments we mocked this sensor data,just sending array of chars.The LoRaWAN node that we used is set up using the "SX1272 LoRa Shield"by Semtech and an "STMicroelectronics NUCLEO-L073RZ MCU Board". Thiskit which can be seen in figure 3.1 uses the software I-CUBE-LRWAN providedby ST [15] and the app available called "End-Node". The software have supportfor SX1276, SX1276 and SX1272 LoRa shields. The IDE Atollic for embeddeddevices was used to edit the source-code to increase the duty cycle and mockingsensor data, Atollic was also used to flash the code onto the device.

All experiments were conducted using the following parameters for the device:• Bandwidth: 867.1 - 868.5Mhz• Channel size: 125kHz• Spreading Factor (sending and receiving), variable = 7 to 12:• Coding Rate (sending and receiving), fixed = 4/5:• Transmitting Power: 14dBm

Figure 4.2: STMicroelectronics NUCLEO-L073RZ MCU Board with aSX1272 LoRa Shield and a 2 dBi gain omni-directional antenna

Source: http://www.st.com/en/evaluation-tools/p-nucleo-lrwan1.html

http://www.st.com/en/evaluation-tools/p-nucleo-lrwan1.html


Gateway

The gateway that we used is a "Wimod LoRa Lite Gateway" by IMST and isintended for development and evaluation purposes. It consists of a Raspberry Piand a concentrator iC880A. The LoRa specific source code running on the gate-way is provided by the open-source github project LoRa-net [16]. As the gatewayis a commercial product it is pre-configured with the appropriate settings upondelivery. The Rasberry Pi is running Raspbian OS and is pre-installed with therepositories "lora_gateway" and "packet_forwarder" contained in the LoRa-netproject.

All experiments were conducted using the following parameters for the gateway:• Bandwidth: 867.1 - 868.5Mhz• Channel size: 125kHz• Spreading Factor (sending and receiving), variable = 7 to 12:• Coding Rate (sending and receiving), fixed = 4/5:• Transmitting Power: 14dBm

Figure 4.3: Wimod LoRa Lite Gateway, 2dBi gain Omni directional antennaSource: https://wireless-solutions.de/downloads/Evaluation-Tools/LoRa_Lite_

Gateway/WiMOD_LiteGateway_QuickStartGuide_V1_3.pdf

https://wireless-solutions.de/downloads/Evaluation-Tools/LoRa_Lite_Gateway/WiMOD_LiteGateway_QuickStartGuide_V1_3.pdf

https://wireless-solutions.de/downloads/Evaluation-Tools/LoRa_Lite_Gateway/WiMOD_LiteGateway_QuickStartGuide_V1_3.pdf


4.2.3 Experiments

Our research method mainly consists of conducting experiments on a live LoRanetwork consisting of a gateway and an end-node device. With all of the hardwarebeing battery supplied we have a mobile setup and the ability to do the experi-ments in different kind of environments. From these experiments we can extractrelevant information such as RSSI and SNR values together with packet-loss etc.

In all of the experiments the end-node device transmits a packet with a 2 bytepayload every 10 second with a transmitting power of 14dBm. The spreading fac-tor can vary from SF7 to SF12. The SF value is chosen automatically based onthe time it takes for the gateway to acknowledge the packet. For all experimentsbut the height test the experiment is done twice, once with the antennas alignedmeaning both are vertical and once when they are misaligned where one antennais horizontal and pointing towards the other that is positioned vertically.

All experiments are to be conducted during the month of April in the times-pan 11am - 1pm. They are also to be performed in sunny weather and in atemperature range of 16°C - 20°C . This is done to minimize the affect theseparameters can have on the result as they are not otherwise accounted for.

To achieve a higher accuracy for the experimental results we conducted eachexperiment for 30 consequent measurements for each distance. The average ofthese measurements is then used as the basis for our conclusions. The average,minimum value, maximum value and standard deviation for each measurementis presented in the appendix.


Open SpaceHere we set up the equipment on a location were we can have at least one kilo-meter with a free line of sight. We then move the end-node device further andfurther away from the gateway and on each 300 meters we do a measurement. Assoon as we lose a single data-packages in the transmissions we decreased the stepto 100 meters. We then continue until either 0 packages are received or we runout of space that still maintain free line of sight. In Figure 4.4 the location anddistances can be seen. The gateway is stationary while the end-node device getspositioned at different distances.

Figure 4.4: Measurement location for open space experiment


Dense forestOn this part we find a location where the terrain was relatively flat and with adense vegetation. We then do the measurements, starting at 300 meters. Fromthen on we increase the distance by 100 meters each step since we can expectthe signal to drop more drastically compared to having free line of sight. Figure4.5 shows the location and setup of gateway and end-node device. Gateway isstationary in the bottom right while the device gets moved further away on astraight line.

Figure 4.5: Measurement locations for dense forest experiment


UrbanIn this test we do our measurements inside of a city that has houses made of avariation of materials that are located on the same height. We start our mea-surements at 150 meters and increasing the range by another 150 meters for eachmeasurement while maintaining the same increment of houses for each measure-ment. Figure 4.6 shows gateway and device positions where the gateway as beforeis stationary and the device gets moved.

Figure 4.6: Measurement locations for city experiment


Gateway elevationFor this test we place the gateway and end-node 400 meters apart from one an-other. We then elevate the gateway in steps of 10 meters starting at 0 whilemoving the gateway to maintain a 400m distance between the two making mea-surements each step. Figure 4.7 is an illustration of how the experiment is setupwhere the end-node device is partly stationary (only moved to maintain the 400mdistance) while the gateway is continuously getting elevated.

Figure 4.7: Measurement locations for gateway elevation experiment

Chapter 5Results and Analysis

5.1 Experiment - Open spaceFor the first experiment we measured a variation of distances where the line ofsight between the device and gateway was completely free and they were locatedas close to the same height as possible. The purpose of the experiment was tounderstand the limits of sea and cropland based use cases as those mostly featuretransmissions with no noise or obstruction of the signal. Looking at figure 5.1beginning at ∼0m distance we see a clear difference in RSSI between having theantennas aligned versus having them misaligned but no difference when it comesto SNR. As the distance increases the RSSI and SNR values decrease at a fastrate at first which after the first measurement decreases. The differential betweenaligned and misaligned gets smaller for RSSI while for SNR it gets larger. After900m the first package loss is observed for the misaligned antenna and from thereon out the number only increases. Having the antennas aligned however led to0 packets lost even at our maximum distance of 1100m where we ran out of space.

These results show that even at a distance of +1100m we still have a strongsignal thats only decaying at a tiny rate if at all which could potentially lastfor several more kilometers. This phenomenon is also observable in a study byPetäjäjärvi in article [12] where they show that with a clear view and a gatewaylocated 24m above the sea level it was possible to reach distances of about 30kmwhile maintaining a PRR of approximately 67%. This follows our hypothesis aswe guessed that the RSSI value would decrease rapidly but that the coveragewould still be passable as there was minimal signal noise and no obstruction. Inthis scenario the LoRa technology is very suitable and the limitation is primarilygiven by the specification of LoRa itself namely the trade-off between range andbandwidth. An overview of these trade-offs can be seen in table 5.1.

Data Rate Configuration Bits/s Max payload0 SF12/125kHz 250 591 SF11/125kHz 440 592 SF10/125kHz 980 593 SF9/125kHz 1 760 1234 SF8/125kHz 5 470 2305 SF7/125kHz 11 000 2306 SF7/250kHz 50 000 230

Table 5.1: Data rates for EU 863-870 MHz[17]

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Chapter 5. Results and Analysis 21

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200

−120

−100

−80

−60

−40

−20

0

Distance (m)

RSS

I(dBm)

Aligned antennasMisaligned antennas

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200

0

5

10

Distance (m)

SNR

(dB)

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,20070

80

90

100

Distance (m)

PRR

(%)

Figure 5.1: Open space experiment results


5.2 Experiment - Dense forestIn this experiment the equipment was set up in a location where the vegetationwas dense and consisting mainly of pine trees. The experiment was set up in asimilar way as the previous one in that an attempt was made to maintain a +/-0height differential for the end-node and gateway, we did however allow for terrainbetween them to provide a fairer measurement.

The trend in RSSI is almost exactly the same for both aligned and misalignedantennas as the one for an open space as is demonstrated in figure 5.2. We cansee a drastic decrease that is more severe than the one we saw with free line ofsight. The SNR on the other hand starts to decrease after only 300 meters andreaches negative numbers on misaligned antennas at 400m and for the aligned at500m. This would indicate that this environment has a big impact on SNR andby proxy on RSSI as well. The RSSI value seems to max out at -120 dBm as nopackage was observed with a lower value.

SNR however doesn’t follow a similar structure as a packet can seemingly belost at an average of -5 dB while a packet with -13 dB can be read without prob-lem.

Similarities between these results and the results of Oana in article[18] can beseen on the maximum range reached in a dense forest environment where theywould reach up to around 390m with an omni-directional antenna. The range theyachieved in their tests was with an output power of the transmitter at 13dBm.Comparing this to our results where we get a max range at around 500meter withno significant packet-loss and transmitting at 14dBm. Taking into account thatthe environmental variables on the different sites is likely to be slightly different,our results would partially confirm the result of that study. Although Oana con-cludes in [18] that vegetation does impact on performance they also state thatthe dense forest environment where their tests were conducted did not seem toaffect the connectivity of LoRa.


0 50 100 150 200 250 300 350 400 450 500 550 600 650

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Figure 5.2: Dense forest experiment results


5.3 Experiment - Urban cityThe final distance based experiment was conducted in a city neighborhood witha flat environment and streets that had two houses between them made of a vari-ation of materials. This let us perform measurements on a per street basis to givea fair measurement.

A more drastic drop in both RSSI and SNR than in the previous experimentsis visible in figure 5.3 and it can be observed that the values become lower at150m than that of the previous experiments at 300m. For the next distance mea-surement step to 300m an extreme drop in signal quality can be observed wherethe PRR for having the antennas aligned gets as low as 32% while not a singlepacket can be read while having them misaligned.

While packets seemingly get lost due to poor signal quality the packets thatactually get through maintain a mean SNR value of -7.1 dB while for the exper-iment in the forest the value could reach as low as -13.6 dB without the packetbeing lost. This would imply that the noise hasn’t reached the level where it ob-fuscates the signal but rather that the packet is lost due to the signal link (RSSI)being lower than the receivers sensitivity. The attenuation of the signal happensdue to it having to pass through or around several materials where most consistof materials harder than wood. For example assuming the attenuation rate of airis 0 dB/m at ∼900MHz the rate for wood is 5 dB/m while for concrete it is 22dB/m. [19]. This means that in a city environment there is a heavy dependencyon the placement of both gateway and end-node as a single house can have alarge affect on the signal quality. This problem can be mitigated by placing thegateway (and if possible the end-node) at higher location to make the RF pathloss lower while going around objects than through them.


0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320

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0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320−10

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Figure 5.3: Urban city experiment results


5.4 Experiment - Gateway elevationStarting with both the gateway and device on the ground at the same heightand 400m apart, the RSSI values were slightly below -100 dBm as can be seenin figure 5.4. The first 10 meters of elevation on the gateway side resulted in arise in RSSI to around -95dBm and the SNR value to improve by 2dBm. Fur-ther elevation to 20m drastically improves the RSSI and gives a value of -75dBmfrom there on the increase stagnates and the RSSI value is basically unchanged upto 40 meters, the SNR value however continues to rise although at a decaying rate.

Height has as expected a great impact on performance to the point where freeline of sight and the fresnel zone is clear of obstacles is achieved from that pointon any further elevation might not be considered useful. Applying this elevationto the forest and city environments that were previously tested would most likelyimprove the performance greatly and allow for use cases that would otherwise beconsidered impossible i.e. large forest agriculture and city based solution thatspan +1km.


0 5 10 15 20 25 30 35 40−105

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0 5 10 15 20 25 30 35 408

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Figure 5.4: Gateway elevation experiment results

Chapter 6Conclusion and Future work

6.1 ConclusionThe goal of this thesis was to do a performance evaluation of a LoRa networkand from this evaluation, analyze how the limitation set by the performance affectvarious use cases.

Several limitations can be seen when there are obstructions in the way as thesignal drops rapidly up to 300m after which the signal decay rate gets loweredand based on the environment potentially drops to a halt as can be for the ex-periment in the open space where the signal keeps a consistently good qualitythroughout the entirety of the test. In the forest and city tests the quality issignificantly worse to the point that with our setup in a city environment reach-ing distances above 350m is impossible due to the high amount of noise andquantity of dense materials. This problem can be circumvented by elevating thegateway and/or device to the point that free line of sight or close to it is achieved.

This means that large scale implementations deploying a gateway on a radio towerto prevent obstructions would have no problems reaching distances of +15km. Forimplementations on a lower scale, problems can arise as barriers in the form ofhouses, terrain and/or vegetation quickly add up and in most cases limits theimplementations range to a house or neighborhood. In some cases, elevating thegateway to an optimal height could be impossible. The solution would be to useseveral gateways in the same implementation just like a normal telecommunica-tion solution where a device can connect to any radio tower. Another factor isif the device is mobile as having misaligned antennas leaves a large mark on theperformance and there can be more than a 50% difference in PRR.

Regarding packet loss it appears that exceeding the threshold of -120dBm causesthe packet to become corrupted i.e. unreadable or lost completely. SNR howeverseems to have less of an effect as a packet is seemingly as readable at ∼-14dBas it is at a positive value. This means that for most implementations it is veryimportant to have packet loss in regard when planning placement as the RSSIcan fluctuate and as in most cases there are no retransmissions in LoRa if thedevice is at the edge of the communication range the packet can be lost forever.This can be very painful for a lot of use cases as the duty cycles are very limitedand the next transmission can be hours away.

28

Chapter 6. Conclusion and Future work 29

6.2 Future WorkFor future investigation into this subject more case studies are needed as this oneis limited to short term tests and conducted under similar weather conditions forall of the test cases.

Furthermore, an extensive comparison to theoretical and simulated results isneeded to provide information about how the real world performance comparesto a simulated one as there is always external variables affecting, thats not oth-erwise accounted for. Assuming the simulation follows a similar trend, a tool fordeciding if a LoRa network is a feasible solution for a use case could be developed.

References

[1] K. Mekki et al. “A comparative study of LPWAN technologies for large-scaleIoT deployment”. In: ICT Express (2018).

[2] N. Lethaby. “Wireless connectivity for the Internet of Things : One sizedoes not fit all”. In: 2017.

[3] F. Adelantado et al. “Understanding the Limits of LoRaWAN”. In: IEEECommunications Magazine (2017).

[4] R. Sanchez-Iborra et al. “Performance Evaluation of LoRa Considering Sce-nario Conditions”. In: Sensors (2018).

[5] B. Ray. What Is LoRaWAN? https://www.link-labs.com/blog/what-is-lorawan. Accesed: 14/5-2018. 2015.

[6] LoRa Alliance. What is LoRaWAN. https://lora-alliance.org/resource-hub/what-lorawantm. Accesed: 14/5-2018. 2015.

[7] M. Centenaro et al. “Long-range communications in unlicensed bands: therising stars in the IoT and smart city scenarios”. In: IEEE Wireless Com-munications (2016).

[8] M. Cattani, C. Boano, and K. Römer. “Experimental Evaluation of theReliability of LoRa Long-Range Low-Power Wireless Communication”. In:Journal of Sensor and Actuator Networks (2017).

[9] H. Wennerström et al. “A long-term study of correlations between meteoro-logical conditions and 802.15.4 link performance”. In: 2013 IEEE Interna-tional Conference on Sensing, Communications and Networking (SECON).2013.

[10] G. Ferre. “Collision and packet loss analysis in a LoRaWAN network”. In:2017 25th European Signal Processing Conference (EUSIPCO). 2017.

[11] European Commission. ERC RECOMMENDATION 70-03. https://www.efis.dk/sitecontent.jsp?sitecontent=srd_regulations. Accesed:1/5-2018. 2017.

[12] J. Petäjäjärvi et al. “Performance of a low-power wide-area network basedon LoRa technology: Doppler robustness, scalability, and coverage”. In: In-ternational Journal of Distributed Sensor Networks (2017).

[13] V. Thiemo, R. Utz M. Bor, and A. Juan. “Mitigating Inter-network In-terference in LoRa Networks”. In: Proceedings of the 2017 InternationalConference on Embedded Wireless Systems and Networks. 2016.

[14] Loriot. https://www.loriot.io/. Accesed: 14/5-2018. 2016.

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https://www.link-labs.com/blog/what-is-lorawan

https://www.link-labs.com/blog/what-is-lorawan

https://lora-alliance.org/resource-hub/what-lorawantm

https://lora-alliance.org/resource-hub/what-lorawantm

https://www.efis.dk/sitecontent.jsp?sitecontent=srd_regulations

https://www.efis.dk/sitecontent.jsp?sitecontent=srd_regulations

https://www.loriot.io/

[15] ST. I-CUBE-LRWAN. http://www.st.com/en/embedded-software/i-cube-lrwan.html. Accesed: 4/5-2018. 2018.

[16] LoRa Gateway Project. https://github.com/Lora-net/lora_gateway.Accesed: 4/5-2018. 2017.

[17] LoRa Alliance Technical Committee Regional Parameters Workgroup. Lo-RaWAN Regional Parameters. https://lora-alliance.org/resource-hub/lorawantm-regional-parameters-v11rb. Accesed: 16/5-2018. 2017.

[18] O. Iova et al. “LoRa from the City to the Mountains: Exploration of Hard-ware and Environmental Factors”. In: Proceedings of the 2017 InternationalConference on Embedded Wireless Systems and Networks. 2017.

[19] Ofcom. Building Materials and Propagation. https://www.ofcom.org.uk/research- and- data/technology/general/building- materials.Accesed: 14/5-2018. 2014.

31

http://www.st.com/en/embedded-software/i-cube-lrwan.html

http://www.st.com/en/embedded-software/i-cube-lrwan.html

https://github.com/Lora-net/lora_gateway

https://lora-alliance.org/resource-hub/lorawantm-regional-parameters-v11rb

https://lora-alliance.org/resource-hub/lorawantm-regional-parameters-v11rb

https://www.ofcom.org.uk/research-and-data/technology/general/building-materials

https://www.ofcom.org.uk/research-and-data/technology/general/building-materials

Appendix

Measurement Values - Open SpaceDistance(m) Average Min Value Max Value Standard Deviation

0 -8.84 -21 1 5.66300 -86.56 -95 -80 3.56600 -95.92 -101 -89 2.84900 -108.16 -115 -101 3.361000 -106.88 -114 -103 2.591100 -102.60 -109 -97 3.08

RSSI(dBm) values with the antennas aligned

Distance(m) Average Min Value Max Value Standard Deviation0 -33.64 -51 -27 5.70

300 -99.32 -112 -88 6.51600 -101.4 -111 -93 3.43900 -111.91 -116 -108 2.211000 -113.62 -118 -106 2.361100 -110.68 -109 -97 3.71

RSSI(dBm) values with the antennas misaligned

Distance(m) Average Min Value Max Value Standard Deviation0 10.65 6.8 13.5 1.64

300 8.92 7.7 10 0.98600 10.54 8.2 12.5 1.25900 4.20 -5 7.8 2.541000 5.56 0 7.8 1.821100 7.47 4.2 10 1.66

SNR(dB) values with the antennas aligned


300 7.77 4.8 10 1.38600 7.66 2.2 10.5 1.82900 1.00 -6.5 5.8 3.421000 -1.54 -8.8 4.8 3.431100 2.25 -5.2 7.5 3.96

SNR(dB) values with the antennas misaligned

32

Measurement Values - Dense ForestDistance(m) Average Min Value Max Value Standard Deviation

0 -8.84 -21 1 5.66300 -99.52 -112 -92 5.12400 -113.12 -119 -107 2.96500 -117.33 -120 -112 2.12600 -118.5 -120 -116 1.12


Distance(m) Average Min Value Max Value Standard Deviation0 -33.64 -51 -27 5.70

300 -109.28 -119 -101 4.63400 -116.12 -119 -112 1.97500 -118.71 -120 -116 1.03600 - - - -



300 7.94 3.2 10.8 1.66400 1.35 -10 5.8 3.90500 -3.49 -14.2 2.5 3.60600 -13.62 -17.2 -9 2.44



300 5.70 -2.5 10.8 3.70400 -4.58 -12.5 2 4.28500 -9.58 -16.8 -4.2 3.86600 - - - -


33

Measurement Values - Urban City

Distance(m) Average Min Value Max Value Standard Deviation0 -8.84 -21 1 5.66

150 -106.17 -114 -100 4.23300 -112.63 -114 -110 1.41


Distance(m) Average Min Value Max Value Standard Deviation0 -8.84 -21 1 5.66

150 -109.68 -114 -106 2.13300 - - - -



150 -3.01 -11.8 8.8 5.52300 -7.13 -10.2 -3.5 2.54



150 0.77 -6 7 3.74300 - - - -


34

Measurement Values - Gateway Elevation

Height(m) Average Min Value Max Value Standard Deviation0 -101.92 -119 -95 4.9810 -94.12 -103 -87 3.7920 -74 -83 -67 3.3130 -74.64 -81 -72 2.4640 -77.46 -85 -72 3.26

RSSI(dBm) values

Height(m) Average Min Value Max Value Standard Deviation0 8.15 3 12 2.0610 10.06 6.8 13.2 1.7220 9.17 6.5 12.8 1.7030 10.25 8.5 12.5 0.9240 10.86 8 13 1.44

SNR(dB) values

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