Thesis Final report

POLITECNICO DI MILANO
School of Industrial and Information Engineering
Master of Science in Telecommunication Engineering
Experimental Performance Evaluation of LoRa
Wireless Links
Supervisor: Prof. Matteo Cesana
Master Thesis of
Malga Trinath Kranthi Kumar: 897453
Meghana Manjunath: 898297

EXPERIMENTAL PERFORMANCE EVALUATION OF LORA WIRELESS LINKS
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ACKNOWLEDGEMENT
I would first like to thank my master thesis advisor Prof.Matteo Cesana of the School of
Industrial and Information Engineering at Politecnico Di Milano. The door to Prof. Matteo
office was always open whenever I ran into a trouble spot or had a question about my research
or writing. He consistently allowed this paper to be my own work but steered me in the right
direction whenever he thought I needed it.
I would also like to thank the experts who were involved in the validation survey for this
project. Without their passionate participation and input, the validation survey could not have
been successfully conducted.
Finally, I must express my very profound gratitude to my parents and to my friends for
providing me with unfailing support and continuous encouragement throughout my years of
study and through the process of researching and writing this thesis. This accomplishment
would not have been possible without them. Thank you.
Author
Malga Trinath Kranthi Kumar
Meghana Manjunath

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ABSTRACT
Now-a-days, long range communication with low bit rate and low power consumption has
enabled LoRa to revolutionize IoT (Internet of Things) technology. LoRa performance was
analysed in to see the viability for Indoor applications. The case study was made in one of the
Politecnico di Milano buildings using point-to-point communication. Owing to its cost
effectiveness, Arduino MKR WAN 1300 is used which is based on Atmel SAMD21 and a
Murata CMWX1ZZABZ Lo-Ra module. Experimental values of RSSI and PER were
calculated and analysed by varying the parameters like transmission power, spreading factor
and the bandwidth.

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ASTRATTO
Al giorno d'oggi, la comunicazione a lungo raggio con una bassa velocità in bit e un basso
consumo energetico ha permesso a LoRa di rivoluzionare la tecnologia IoT (Internet of
Things). Le prestazioni di LoRa sono state analizzate per verificare la fattibilità delle
applicazioni per interni. Il caso di studio è stato realizzato in uno degli edifici del Politecnico
di Milano utilizzando la comunicazione punto-punto. Grazie alla sua convenienza, viene
utilizzato Arduino MKR WAN 1300 basato su Atmel SAMD21 e un modulo Lo-Ra Murata
CMWX1ZZABZ. I valori sperimentali di RSSI e PER sono stati calcolati e analizzati variando
i parametri come potenza di trasmissione, fattore di diffusione e larghezza di banda.

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Table of Contents
I. List of Tables ……………………………………………. 6
II. List of Figures …………………………………………… 7
1. Introduction ………………………………………………. 8
2. Background ………………………………………………. 10
2.1 Overview of Lora ………………………………………10
2.2 State of the Art …………………………………………12
3. Performance Evaluation ………………………………... 17
3.1 Hardware ………………………………………………17
3.2 Software ……………………………………………….19
3.3 Description …………………………………………….21
3.4 Results …………………………………………………25
4. Conclusions ………………………………………………. 37
4.1 Applications ……………………………………………37
4.2 Future Works …………………………………………..38
5. Bibliography ………………………………………………39

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I. LIST OF TABLES
2.1: Comparison …………………………………………………………………………….. 12
3.4.1: Ground Floor RSSI value …………………………………………………………….. 25
3.4.2: First Floor RSSI value ……………………………………………………………….. 27
3.4.3: Second Floor RSSI value …………………………………………………………….. 28
3.4.4: Third Floor RSSI value ………………………………………………………………. 30
3.4.5: Ground Floor PER value …………………………………………………………….. 34
3.4.6: First Floor PER value ………………………………………………………………… 34
3.4.7: Second Floor PER value ……………………………………………………………… 35
3.4.8: Third Floor PER value ……………………………………………………………….. 35

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II. LIST OF FIGURES
2.1.1: LoRa Architecture …………………………………………………………………… 11
3.1.1: Arduino MKR WAN 1300 …………………………………………………………… 18
3.1.2: GSM Dipole Antenna ………………………………………………………………… 18
3.2.1: Screenshot of Arduino IDE software ………………………………………………… 19
3.2.2. Screenshot of MATLAB code for plotting graphs …………………………………… 20
3.3.1: Ground Floor Position of Sender (Red Dot) …………………………………………. 23
3.3.2: Ground Floor Position of Receiver (Blue Dot) ………………………………………. 23
3.3.3: First Floor Position of Receiver (Blue Dot) ………………………………………….. 24
3.3.4: Second Floor Position of Receiver (Blue Dot) ………………………………………. 24
3.3.5: Third Floor Position of Receiver (Blue Dot) …………………………………………. 24
3.4.1: SF vs RSSI (Ground floor, BW 125 kHz) ……………………………………………. 26
3.4.2: SF vs RSSI (Ground floor, BW 250 kHz) ……………………………………………. 26
3.4.3: SF vs RSSI (First floor, BW 125 kHz) ……………………………………………….. 27
3.4.4: SF vs RSSI (First floor, BW 250 kHz) ……………………………………………….. 28
3.4.5: SF vs RSSI (Second floor, BW 125 kHz) ……………………………………………. 29
3.4.6: SF vs RSSI (Second floor, BW 250 kHz) …………………………………………… 29
3.4.7: SF vs RSSI (Third floor, BW 125 kHz) ……………………………………………… 30
3.4.8: SF vs RSSI (Third floor, BW 250 kHz) ……………………………………………… 31
3.4.9: SF vs RSSI (Comparison of RSSI value of three floors, BW 250 kHz, TxP 8 dB) ….. 31
3.4.10: SF vs RSSI (Comparison of RSSI value of three floors, BW 125 kHz, TxP 8 dB) … 32
3.4.13: SF vs PER (All floors, BW 125 kHz) ……………………………………………….. 36
3.4.14: SF vs PER (All floors, BW 250 kHz) ………………………………………………. 36

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1. INTRODUCTION
There have been visions of smart, communicating objects even before the global
computer network was launched four decades ago. As the Internet has grown to link all
signs of intelligence around the world, a number of other terms associated with the idea
and practice of connecting everything to everything have made their appearance,
including machine-to-machine (M2M), Radio Frequency Identification (RFID),
context-aware computing, wearables, ubiquitous computing, and the Web of Things.
The internet of things, or IoT, is a system of interrelated computing devices, mechanical
and digital machines, objects, animals or people that are provided with unique
identifiers (UIDs) and the ability to transfer data over a network without requiring
human-to-human or human- to-computer interaction.
There are different communication technologies available now-a-days for Wireless
sensor networks. The choice depends on the amount of exchanged traffic that is needed,
on the power consumption constraints, and on the propagation condition in different
environments. The LoRa technology recently gained interest from research and
industrial community. The advantage of LoRa is that it is cost efficient, low power, low
bit rate and large coverage. This makes it suitable for large-scale deployments in large
industrial environments.
So, in this experiment the test run is done in an indoor environment of building 20,
Politecnico di Milano, Milan, Italy. All the measurements were performed inside a
multi-floor building in order to study the LoRa propagation in such conditions. The
communication is through point-to-point wireless link. In the experiment we kept the
transmitter stable and the receiver kept changing the location. The packets captured at
the receiver end was limited to 100 packets for analysing the Packet error rate (PER)
and Receiver Signal Strength Indicator (RSSI) value. These two values are evaluated
by changing the parameters like transmission power, spreading factor and bandwidth.
This work focuses on LoRa capability aspects in an office environment with different
parameter values.

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For this purpose the thesis is structured in the following way:
The first chapter gives the context for the thesis and a brief introduction to the
experiment conducted.
The second chapter provides overview of the LoRa and its architecture. It also provides
the state of the art about LoRa/LoRaWAN researches. It gives a comparison between
the researches for easier understanding.
The third chapter introduces the different components and terminologies used for the
experiment. It provides description and setup done to conduct the tests. The results and
corresponding graphs has been mentioned
The conclusion chapter wraps up the final result of the experiment and also provides
different applications. It also gives some considerations for future enhancements.

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2. BACKGROUND
2.1. OVERVIEW OF LoRa
LoRa (short for long range) is a spread spectrum modulation technique derived from
chirp spread spectrum (CSS) technology. Semtech’s LoRa devices and wireless radio
frequency technology is a long range, low power wireless platform that has become the
de facto technology for Internet of Things (IoT) networks worldwide. LoRa devices and
the open LoRaWAN® protocol enable smart IoT applications that solve some of the
biggest challenges facing our planet: energy management, natural resource reduction,
pollution control, infrastructure efficiency, disaster prevention, and more. Semtech’s
LoRa devices and the LoRaWAN protocol have amassed several hundred known uses
cases for smart cities, smart homes and buildings, smart agriculture, smart metering,
smart supply chain and logistics, and more. [17]
The term LoRa stands for Long Range. It is a wireless Radio frequency technology
introduced by a company called Semtech. This LoRa technology can be used to transmit
bi-directional information to long distance without consuming much power. This
property can be used by remote sensors which have to transmit its data by just operating
on a small battery.
Typically Lora can achieve a distance of 15-20km and can work on battery for years.
Remember that LoRa, LoRaWAN and LPWAN are three different terminologies and
should not be confused with one another.
Since LoRa defines the lower physical layer, the upper networking layers were lacking.
LoRaWAN is one of several protocols that were developed to define the upper layers
of the network. LoRaWAN is a cloud-based media access control (MAC) layer protocol
but acts mainly as a network layer protocol for managing communication
between LPWAN gateways and end-node devices as a routing protocol, maintained by
the LoRa Alliance.
LoRa employs Chirp Spread Spectrum (CSS) modulation to modulate signals. A chirp
in CSS refers to a signal with constantly increasing or decreasing frequency that sweeps
through and wraps around a predefined bandwidth, referred as upchirps and downchirps
Theoretically, LoRa is able to achieve a data rate up to 27kbit/s. The data rate while
limited, is more than sufficient for LPWAN applications where communication
coverage is prioritized over data rate. LoRa configuration can be modified by
manipulating some key parameters to achieve trade-offs among communication
distances, data rate, and power consumptions. [18]

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Transmissions use a wide band to counter interference and to handle frequency offsets
caused by low cost crystals. A LoRa receiver can decode transmissions 19.5 dB below
the noise floor, thus, enabling very long communication distances. LoRa key properties
are: long range, high robustness, multipath resistance, Doppler resistance and low
power. LoRa transceivers available today can operate between 137MHz to 1020 MHz,
and thus can also operate in licensed bands. However, they are often deployed in ISM
bands. [19]
Fig 2.1.1: LoRa Architecture
 End Device, Node, Mote - an object with an embedded low-power
communication device.
 Gateway - antennas that receive broadcasts from End Devices and send data
back to End Devices.
 Network Server - servers that route messages from End Devices to the right
Application, and back.
 Application - a piece of software, running on a server.

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2.2. STATE OF THE ART
A significant amount of studies and experiments have been focused on analysing the
range of LoRa/LoRaWAN. The experiments are done in various places like indoor,
outdoor, rural, urban, ground and also on water. Most of the experiments conducted
have nodes as sender and gateways as receiver.
Reference [1] [2] [3] [4] [5]
Context:
Indoor/Outdoor
Indoor and
Outdoor
Outdoor
Indoor and
Outdoor
Indoor Indoor
Type of Performance
Evaluation:
Empirical/Analytical
Empirical
and
Analytical
Empirical
Empirical
and
Analytical
Empirical Empirical
Table 2.1: Comparison
2.2.1. LoRaWAN Network: Radio Propagation Models and Performance
Evaluation in Various Environments in Lebanon [1]
ABSTRACT: LoRaWAN radio channel is investigated in the 868 MHz band. Extensive
measurement campaigns were carried out in both indoor and outdoor environments at
urban and rural locations in Lebanon. The results show that the proposed PL models are
accurate and simple to be applied in Lebanon and other similar locations. Coverage
ranges up to 8km and 45km were obtained in urban and rural areas, respectively. This
reveals the reliability of this promising technology for long-range IoT communications.

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TYPE OF CONFIGURATION:
END DEVICE: Pycom LoPy with PyTrack expansion board. Pycom LoPy with
PyTrack expansion board was used as LoRa ED, powered by 3.7-volt rechargeable
lithium battery. The LoPy has an integrated LoRa SX1272 transceiver and an additional
WiFi transceiver. PyTrack module includes an embedded global positioning system
(GPS) used to obtain the location of the ED.
GATEWAY: Kerlink Wirnet Station. Kerlink Wirnet Station was used as the GW which
is able to receive LoRa frames from -20 dBm to -141 dBm, depending on the LoRa BW
and SF.
NETWORK SERVER: The GW was connected to the network server provided by an
open source LoRa server.
RESULTS: It was shown that the proposed models fit measurements with more
accuracy and are much simple to be used in areas similar to Lebanon. Moreover, the
performance of LoRaWAN was evaluated in terms of PDR and SNR. The reported
results show the reliability of LoRaWAN communications in real-life environments for
long distances. In a dense urban area, a coverage range up to 9 km was attained, whereas
in the rural case a coverage range up to 47 km was reached using a single deployed GW.
2.2.2. On the Coverage of LPWANs: Range Evaluation and Channel Attenuation
Model for LoRa Technology [2]
ABSTRACT: In this work we study the coverage of the recently developed LoRa
LPWAN technology via real-life measurements. The measurements were executed for
cases when a node located on ground (attached on the roof rack of a car) or on water
(attached to the radio mast of a boat) reporting their data to a base station.
END DEVICE: LoRaMote, which are equipped with a Semtech SX1272 transceiver [9]
with Planar-F type printed circuit board antenna. Firmware version programmed to the
node was 3.1. Besides the SX1272 transceiver, each node included a receiver for GPS
and a set of sensors. During the measurements, the nodes were powered by 9V batteries.
GATEWAY: Kerlink’s LoRa IoT station was connected to the biconical D100-1000
antenna from Aerial.

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RESULTS: The reported results of the measurements show that on the ground on the
distances up to 5 km the amount of successfully delivered packets exceeds 80%. More
than 60% of the packets were received correctly at the distances of 5 to 10 km. On the
distances exceeding 10 km the majority of sent packets were lost. On the water, almost
30 km communication range was reached with about 70% of the packets delivered
successfully at the distances below 15 km. The channel attenuation model was derived
from the presented measurements results. The model can be used by network providers
to estimate the required base station density and may enable more accurate analysis of
the LoRa performance.
2.2.3. LoRa Indoor Coverage and Performance in an Industrial
Environment: Case Study [3]
ABSTRACT: The use case for this paper is taken from the flower industry, where a
large number of trolleys need to communicate with a server during their movement
across the auction floor area. The LoRaWAN network consists of multiple end nodes
and a single gateway per cell, acting as a transparent bridge between the end nodes and
the network server.
END NODES: LoRaWAN motes we used two WiMOD iM880A nodes. Since each
LoRa mote uses counters to distinguish between consequent packets at the receiving
side, we make use of this counter to detect any lost packets during the measurement.
Once we moved to another location the counter was reset to 0 to make it possible to
distinguish the packets from different measurement locations in the logs of the
LoRaWAN server.
GATEWAY: LoRANK gateway which employs a WiMOD iC880A chip. It is able to
receive on 8 channels in parallel at sub-bands 868 MHZ and 867 MHz and all spreading
factors.
SOFTWARE: The simulator is a Python script that compares the starting time of
random transmissions and the transmission time length and calculates the collisions
based on timing overlap and RSSI values.
RESULTS: Based on the measurements we can conclude that we are able to cover the
whole industrial area under consideration, with a surface of ~34000 m2, with SF 7. In
general, the SNR values were above 0 dB with some negative values at some measuring
locations. The average RSSI values were above -100 dBm at all measuring locations.
We did not have any packet losses except some negligible number of packets received
with wrong payload CRC (0.5 - 0.8%) for the indoor measuring points. For the outdoor

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measuring locations, we could have communication only with SF 12 with the most
distant measuring point, at ~400 m.
2.2.4. Performance Analysis of LoRaWAN for Indoor Application [4]
ABSTRACT: Generally, the existing technologies of LPWAN only cover a short
distance in a wide area network and it will limit the performance of IoT applications.
Thus, Long Range Wide Area Network (LoRaWAN) is introduced to address the
setback of LPWAN. In this paper, LoRaWAN performance is analysed to see the
feasibility of LoRaWAN for indoor application. The performance study was carried out
in terms of packet losses, data rates and communication range. The results show that,
the signal strength of LoRaWAN is suitable for indoor usage.
END NODES: KENET LoRa nodes which are equipped with Dragino LoRa Shield
and attached to the Arduino ATMEL 328P board.
NETWORK SERVER: The Things Network. MQTT that acts as the middle man in
which the LoRa gateway will communicate with the LoRa server.
RESULTS: The first measurement is done for SF ranging from 7 to 12 at 125 kHz of
bandwidth. The transmission time increases orderly when the SF increases. It can be
seen that, the distance between the gateway and nodes affects the successful of
packets transmission.
2.2.5. Empirical indoor propagation models for LoRa radio link in an office
environment [5]
ABSTRACT: In this paper, we present some indoor measurements performed in a
standard office environment using LoRa links. The aims of the work is to assess the
indoor propagation performance of LoRa technology and to indicate the best model to
be used for a preliminary design of a LoRa based radio link in an office environment.
The measured data highlights that LoRa technology can be used in office environment
to realize a wireless sensor network. Five commonly used propagation models were also
analysed and their results compared with the measurements. This analysis highlighted
that the Motley-Keenan’s is the best model to describe indoor propagation.

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TRANSMITTERS AND RECEIVERS: Both transmitters and receiver are equipped
with the same electronic components, Microcontroller μC (Arduino© Nano),
communication module and quarter-wave monopole antenna with a gain G=3.16 dB
(Linx Technologies, model ANT-868-CW-RCS), operating in the band 860-868 MHz.
A specific controlling software was developed for each test using the Arduino©
Integrated Development Environment (IDE). The communication module installed in
both the receiver and transmitter is the Adafruit® Feather 32u4 LoRa Radio RFM95. It
is an embedded module, which contains a LoRa® transceiver RFM95 and an
ATmega32u4 microcontroller. The module is controlled by an Arduino©
microcontroller, since the microcontroller of the Adafruit® Feather 32u4 LoRa Radio
RFM9 can be programmed with the same libraries of Arduino©.
RESULTS: Results highlight that LoRa technology can be used with very good
performance in an office indoor environment recently built, with thin walls. The
comparisons between the measured power and the theoretical values computed with the
most common empirical models for indoor propagations show that Keenan’s model is
the best one to be used for a preliminary design of a LoRa based communication link.

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3. PERFORMANCE EVALUATION
The main components used for this experiment is the Arduino board. Arduino is an
open-source electronics platform based on easy-to-use hardware and software. Arduino
boards are able to read inputs - light on a sensor, a finger on a button, or a Twitter
message and turn it into an output - activating a motor, turning on an LED, publishing
something online. You can tell your board what to do by sending a set of instructions
to the microcontroller on the board. To do so you use the Arduino programming
language (based on Wiring), and the Arduino Software (IDE), based on Processing.
[16]
The results are presented in form of graphs for which we used the MATLAB software.
3.1. HARDWARE
3.1.1. Arduino MKR WAN 1300: It has been designed to offer a practical and
cost effective solution for makers seeking to add Lo-Ra connectivity to their projects
with minimal previous experience in networking. It is based on the
Atmel SAMD21 and a Murata CMWX1ZZABZ Lo-Ra module.
The design includes the ability to power the board using two 1.5V AA or AAA batteries
or external 5V. Switching from one source to the other is done automatically. A good
32 bit computational power similar to the MKR ZERO board, the usual rich set of I/O
interfaces, low power Lo-Ra communication and the ease of use of the Arduino
Software (IDE) for code development and programming. All these features make this
board the preferred choice for the emerging IoT battery-powered projects in a compact
form factor. The USB port can be used to supply power (5V) to the board. The Arduino
MKR WAN 1300 is able to run with or without the batteries connected and has limited
power consumption.

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Fig 3.1.1: Arduino MKR WAN 1300
3.1.2. Arduino GSM Dipole Antenna: It operates at frequencies:
850/900/1800/1900MHz. It connects to the board via a Micro UFL connector. It is EU
RoHS Compliant.
Fig 3.1.2: GSM Dipole Antenna

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3.2. SOFTWARE
3.2.1. Arduino Integrated Development Environment (IDE): It is a cross-
platform application (for Windows, macOS, Linux) that is written in the programming
language Java, C++ and C. It is used to write and upload programs to Arduino
compatible boards, but also, with the help of 3rd party cores, other vendor development
boards. [20]
Fig 3.2.1: Screenshot of Arduino IDE software

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3.2.2. MATLAB: It combines a desktop environment tuned for iterative analysis
and design processes with a programming language that expresses matrix and array
mathematics directly. It includes the Live Editor for creating scripts that combine code,
output, and formatted text in an executable notebook.[21]
Fig 3.2.2: Screenshot of MATLAB code for plotting graphs

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3.3. DESCRIPTION
In this project we have a point to point communication between two Arduino MKR
WAN 1300 boards where one is used as Sender and the other as Receiver. The boards
were programmed using Arduino IDE (Integrated Development Environment). We
developed and modified a C++ code already available [22] as per our requirements. The
modification was done so as to change three standard LoRa parameters: Spreading
Factor, Bandwidth, and Transmission Power. The aim of this experiment is to determine
the change in RSSI (Received Signal Strength Indicator) and PER (Packet Error Rate)
with respect to distance from the sender and different values of the parameter.
Bandwidth: It is the frequency range of the chirp signal used to carry the baseband
data. Bandwidth can be seen from the width of frequency used between to .
Aside from that, Bandwidth can also represent chip rate from LoRa signal modulation.
[23]
For our experiment we have used two Bandwidths 125 kHz and 250 kHz.
Spreading factor: It can be described as the duration of the chirp or how many chips
are being used to represent a symbol. LoRa operates with spread factors from 7 to 12
where SF7 is the shortest time on air and SF12 is the longest. Each step up in
spreading factor doubles the time on air to transmit the same amount of data. With the
same bandwidth longer time on air obviously results in less data transmitted per unit
of time. The higher the SF value is, the more chips used to represent a symbol, which
means there will be more processing gain from the receiver side.
Symbol Rate:
Spreading Factor shows how many chips used to represent a symbol, with an
exponential factor of 2. 1 symbol may consist of N chip where . A cyclic shift
can be done to represent a bit and sent symbol. If there is N amount of chips, then the
resulting symbol value may range from 0 to N-1, or that 1 symbol may represent SF
bits. [23]

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Bit Rate:
For our experiment we used the values 7, 8, 9 10, 11 and 12.
Transmission Power: Transmission power directly affects the amount of power used
to transmit a chirp. By increasing TX Pow, the signal will have higher chances of
surviving attenuation caused by the environment which effectively increases the signal
power Psignal received by receivers. For example in Europe when using the ISM band
frequencies (863 MHz - 870 MHz) users must comply with the following rules:
 For uplink, the maximum transmission power is limited to 25mW (14 dBm).
 For downlink (for 869.525MHz), the maximum transmission power is limited to
0.5W (27 dBm)
For our experiment we used the values 2 dB, 4 dB, 8 dB, 10 dB, 12 dB and 14 dB.
[24]
Received Signal Strength Indicator (RSSI): It is an estimated measure of power level
that a RF client device is receiving from an access point or router. At larger distances,
the signal gets weaker and the wireless data rates get slower, leading to a lower overall
data throughput. [25]
Packet Error Rate (PER): It is the number of incorrectly received data
packets divided by the total number of received packets. A packet is declared incorrect
if at least one bit is erroneous. The expectation value of the PER is denoted packet
error probability Pp, which for a data packet length of N bits can be expressed as
Pp = 1 - (1- Pe)N
Pp is the packet error rate of N byte packet case, and Pe the bit error rate of one
packet. [15]

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3.3.1. Experiment Setup Description
The experiment was conducted in Building Number 20 of the Politecnico di Milano,
Milan. It was conducted during normal University hours to include the influence of
people moving around. The sender was fixed at one position in the ground floor inside
the ANT LAB as shown by the red dot in Fig 3.3.1. The receiver was kept at different
floors of the same building as shown by in the figure. The results were obtained on the
Serial Monitor which was later saved into a Text file. A total of 100 packets (each packet
can contain up to 255 bytes) were sent for each position and for different combinations
of the parameter values (a total of 72 combinations).
Fig 3.3.1: Ground Floor Position of Sender (Red Dot)
Fig 3.3.2: Ground Floor Position of Receiver (Blue Dot)

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Fig 3.3.3: First Floor Position of Receiver (Blue Dot)
Fig 3.3.4: Second Floor Position of Receiver (Blue Dot)
Fig 3.3.5: Third Floor Position of Receiver (Blue Dot)

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3.4. RESULTS
3.4.1. RSSI
To test the capability of LoRa radio receiver, we analyse the received packets in terms
of their RSSI values. The graphs show RSSI vs SF with a constant Bandwidth for
different values of Transmission Power. As the number of floors, obstructions and
distance from the sender increases, the RSSI value decreases. However, some receivers
might how slightly higher RSSI value than expected. The difference is very small and
may be caused due to people moving around or doors being closed or opened in the
building.
Ground Floor RSSI Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 -99.12 -103.86 -104.75 -97.2 -95.87 -95.64
4 -92.77 -97.92 -103.64 -104.07 -102.05 -99.46
8 -91.85 -96.02 -96.88 -95.55 -98.61 -102.77
10 -89.74 -89.74 -92.89 -94.57 -92.77 -92.67
12 -90.53 -94.96 -94.09 -91.86 -94.49 -91.61
14 -84.35 -88.68 -92.44 -88.33 -89.85 -91.39
250
2 -92.66 -95.39 -96.36 -96.33 -100.4 -101.41
4 -91.56 -96.25 -98.69 -99.23 -99.57 -103.45
8 -96.44 -96.69 -99.23 -98.47 -103.106 -106.16
10 -93.5 -94.56 -93.74 -93.22 -96.01 -103.11
12 -88.78 -91.12 -91.61 -93.37 -91.74 -101.62
14 -87.53 -91.18 -89.97 -92.18 -94.46 -95.64
Table 3.4.1: Ground Floor RSSI value

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Fig 3.4.1: SF vs RSSI (Ground floor, BW 125 kHz)
Fig 3.4.2: SF vs RSSI (Ground floor, BW 250 kHz)

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First Floor RSSI Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 -94.84 -99.4 -102.07 -105.37 -101.58 -102.2
4 -89.33 -92.2 -95.07 -91.64 -93.44 -93.55
8 -89 -90.47 -89.94 -91.3 -93.01 -92.03
10 -90.07 -93.71 -94.84 -92.67 -97.03 -95.47
12 -86.06 -91.96 -89.96 -94.73 -97.37 -91.22
14 -94.78 -97.38 -93.3 -94.11 -100.38 -99.24
250
2 -91.04 -101.19 -99.74 -106.2 -101.29 -106.73
4 -88.49 -91.34 -90.77 -92.82 -94.21 -99.71
8 -94.34 -92.12 -95.87 -90.21 -94.41 -98.15
10 -91.1 -92.88 -92.53 -87.94 -90.18 -99.89
12 -87.81 -93.84 -94.09 -92.97 -95.04 -96.27
14 -86.06 -96.32 -96.32 -94.47 -95.15 -101.88
Table 3.4.2: First Floor RSSI value
Fig 3.4.3: SF vs RSSI (First floor, BW 125 kHz)

28
Fig 3.4.4: SF vs RSSI (First floor, BW 250 kHz)
Second Floor RSSI Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 -116.18 -119.63 -119.33 -118.88 -118.56 -115.59
4 -113.94 -117.17 -117.35 -116.64 -120 -120.69
8 -110.83 -111.72 -114.43 -113.14 -113.81 -115.26
10 -108.64 -111.36 -112.39 -109.71 -110.79 -110.08
12 -103.59 -105.73 -105.67 -104.76 -104.73 -106.42
14 -100.2 -102.77 -103.43 -104.19 -105.7 -106.25
250
2 -114.95 -116.7 -115.13 -113.24 -117.58 -119.51
4 -114.14 -112.63 -111.27 -114.91 -113.44 -115.27
8 -112.43 -112.73 -112.29 -113.33 -112.32 -116.62
10 -107.58 -110.32 -108.78 -109.09 -109.65 -112.41
12 -102.29 -104.82 -107.43 -105.24 -105.14 -105.12
14 -104.82 -107.95 -106.97 -105.9 -105.8 -110.6
Table 3.4.3: Second Floor RSSI value

29
Fig 3.4.5: SF vs RSSI (Second floor, BW 125 kHz)
Fig 3.4.6: SF vs RSSI (Second floor, BW 250 kHz)

30
Third Floor RSSI Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 -118.42 -119.07 -120.27 -120.09 -121.37 -119.69
4 -120.78 -122.64 -122.8 -122.9 -123.09 -123.83
8 -112.8 -114.29 -117.48 -115.24 -114.93 -117.51
10 -116.43 -116.64 -115.62 -114.64 -114.79 -114.07
12 -114.52 -118.22 -116.57 -118.26 -120.75 -118.77
14 -108.89 -110.79 -111.49 -112.92 -112.63 -110.79
250
2 -107.67 -111.16 -114.44 -119.27 -119.1 -123.47
4 -118.39 -112.21 -117.2 -119.89 -119.3 -122.56
8 -110.56 -113.29 -113.06 -114.83 -116.25 -120.33
10 -111.71 -113.42 -114.16 -111.6 -112.88 -118.91
12 -115.68 -115.71 -116.98 -115.12 -117.54 -120.29
14 -105.7 -106.5 -107.72 -108.03 -114.63 -114.19
Table 3.4.4: Third Floor RSSI value
Fig 3.4.7: SF vs RSSI (Third floor, BW 125 kHz)

31
Fig 3.4.8: SF vs RSSI (Third floor, BW 250 kHz)
Fig 3.4.9: SF vs RSSI (Comparison of RSSI value of three floors, BW 250 kHz, TxP 8 dB)

32

33
Fig 3.4.12: SF vs RSSI (Comparison of RSSI value of three floors, BW 250 kHz,
TxP 2 dB)
3.4.2. PER
It is not possible to make conclusions by only looking at the RSSI. Therefore we also
measure the packet error rate and analyse it. We can see from the graphs that in general
the packet loss has an increasing trend when the receiver is farther from the sender
location. Also it can be seen that generally transmitting packets with a higher
transmission power decreases the packet loss.
Ground
Floor
PER Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 0 0 0 0 0 0.0101
4 0 0 0 0.0309 0.01 0.0101
8 0.0101 0 0 0.0204 0 0
10 0 0 0.01 0 0 0
12 0 0 0 0.0416 0 0.0101
14 0 0 0 0.0416 0 0.0101
250
2 0.0101 0 0 0 0 0
4 0 0.0101 0 0 0 0
8 0 0 0 0 0 0
10 0.0202 0 0 0 0.01 0.0101
12 0.02 0 0 0 0 0
14 0 0.01 0 0.01 0.0204 0
Table 3.4.5: Ground Floor PER value

34
First Floor PER Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 0 0 0.01 0.0101 0.0101 0.0101
4 0 0 0.03 0.0309 0 0
8 0 0 0.01 0 0 0
10 0.0204 0 0.02 0 0 0
12 0 0 0.01 0 0 0
14 0 0 0.01 0.0204 0 0
250
2 0.0101 0 0 0 0 0
4 0.0101 0 3.06 0 0.0204 0
8 0.0204 0 0 0 0 0
10 0 0 0 0 0 0
12 0 0 0.01 0.0101 0.04 0
14 0 0 0 0 0 0
Table 3.4.6: First Floor PER value
Second Floor PER Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 0.11 0.05154 0.0204 0.0824 0.0101 0.0101
4 0.3636 0.06122 0 0.04123 0.02 0
8 0.4022 0.0202 0.01 0.0303 0.0202 0
10 0 0 0 0 0 0.0101
12 0.0101 0 0.0202 0.0101 0 0.06315
14 0 0 0.0101 0 0 0.0101
250
2 0.49382 0.0303 0.03061 0 0 0.01
4 0.785 0.2555 0.082474 0.0101 0 0
8 0.22988 0 0.05102 0.05208 0 0
10 0.04166 0.0202 0 0.052631 0 0
12 0.0204 0.0202 0.01 0 0.0204 0.0204
14 0.0101 0 0 0 0.0101 0
Table 3.4.7: Second Floor PER value

35
Third Floor PER Spreading Factor
Bandwidth
(kHz)
Transmission
Power (dB)
7 8 9 10 11 12
125
2 0 0 0 0.0101 0 0.0101
4 0.3636 0.16667 0.66667 0.48 0.04123 0.0202
8 0.42857 0.07142 0.0202 0 0.03092 0
10 0.23076 0.14444 0 0 0.0101 0
12 1.7826 1.04687 0.01 0.03092 0 0
14 0.43421 0.074468 0.0404 0.0101 0 0
250
2 0.7619 0.57142 0.369565 0.06185 0 0
4 0.754098 0.164835 0.10526 0 0.54411 0.291139
8 0.363636 0.06 0.01 0 0.01 0
10 0.506329 0.095744 0.0303 0 0.01 0.01
12 1.4074 0.051546 0.030612 0 0 0
14 0 0 0.030612 0 0.0101 0
Table 3.4.8: Third Floor PER value
Fig: 3.4.13: SF vs PER (All floors, BW 125 kHz)

36
Fig: 3.4.14: SF vs PER (All floors, BW 250 kHz)

37
4. CONCLUSION
In this report a general overview of LoRa and its architecture was introduced. The
associated LoRa parameters such as Spreading Factor, Bandwidth and Transmission
Power were discussed. In this experiment we studied about LoRa wireless technology
and conducted tests to evaluate its performance inside a building. Based on the results
we can conclude that the LoRa technology can be used with good performance inside a
building similar to the one we conducted in. The sender was fixed in one position and
the receiver was moved to different floors of the building. It is essential to find a good
set of parameter settings so that we get the best network performance.
4.1 APPLICATIONS
 Smart lighting
 Home automation for IoT enables smart appliances
 Air quality and pollution monitoring
 Waste management
 Smart parking and vehicle management
 Shipping and transportation
 Facilities and infrastructure management
 Enhanced home security
 Fire detection and management
 Radiation and leak detection
 Smart sensor technology
 Item location and tracking

38
4.2 FUTURE WORKS
Future enhancements can be considered as follows:
 In our experiment we only considered three parameters: Spreading factor,
Bandwidth and Transmission Power. The same experiment can be repeated for
other parameters like Coding Rate, Carrier Frequency.
 The tests were conducted in only one position on each floor. It can be repeated
for many positions so as to get a more accurate results.
 We only sent 100 packets of data in each position. If more number of packets are
sent we will have more accuracy on the data.

39
5.Bibliography
1. LoRaWAN Network: Radio Propagation Models and Performance Evaluation in
Various Environments in Lebanon, Rida El Chall, Samer Lahoud, and Melhem El
Helou, Senior Member, IEEE.
2. On the Coverage of LPWANs: Range Evaluation and Channel Attenuation Model
for LoRa Technology, Juha Petäjäjärvi, Konstantin Mikhaylov, Antti Roivainen,
Tuomo Hänninen.
3. LoRa Indoor Coverage and Performance in an Industrial Environment: Case Study,
Jetmir Haxhibeqiri1, Abdulkadir Karagaac, Floris Van den Abeele, Wout Joseph,
Ingrid Moerman, Jeroen Hoebeke.
4. Performance Analysis of LoRaWAN for Indoor Application, Muhammad Izzam
Muzammir, Husna Zainol Abidin, Syahrul Afzal Che Abdullah, Fadhlan Hafizhelmi
Kamaru Zaman Faculty of Electrical Engineering, Universiti Teknologi MARA,
5. Empirical indoor propagation models for LoRa radio link in an office environment,
Silvano Bertoldo, Miryam Paredes, Lorenzo Carosso, Marco Allegretti, Patrizia Savi,
Politecnico di Torino, Department of Electronics and Telecommunications (DET),
Corso Duca degli Abruzzi, 24, 10129, Torino (Italy).
6. A Framework for Planning LoRaWAN Networks, Matteo Cesana, Alessandro
Redondi Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di
Milano
7. LoRa Network Planning: Gateway Placement and Device Configuration, Behnam
Ousat and Majid Ghaderi Department of Computer Science, University of Calgary.
8.On fast prototyping LoRaWAN: a cheap and open platform for daily experiments.
9. https://nodered.org/
10. https://intel.github.io/dps-for-iot/
11. https://en.wikipedia.org/wiki/Arduino_IDE
12. A Study of LoRa: Long Range & Low Power Networks for the Internet of Things.
13. https://store.arduino.cc/mkr-wan-1300 17. https://www.adafruit.com/product/385
14. https://community.mydevices.com/t/cayenne-lpp-2-0/7510
15. https://www.wikipedia.org/

40
16. https://www.arduino.cc/en/guide/introduction
17. https://www.semtech.com/lora/what-is-lora
18. https://www.ntu.edu.sg/home/limo/papers/TOSN-LoRa.pdf
19. LoRa Transmission Parameter Selection, Martin Bor, Utz Roedig School of
Computing & Communications, Lancaster University, Lancaster, UK.
20. https://en.wikipedia.org/wiki/Arduino_IDE
21. https://www.mathworks.com/products/matlab.html
22. https://github.com/sandeepmistry/arduino-LoRa
23. https://josefmtd.com/2018/08/14/spreading-factor-bandwidth-coding-rate-and-bit-
rate-in-lora-english/
24. https://lora.readthedocs.io/en/latest/
25. https://helpcenter.engeniustech.com/hc/en-us/articles/234761008-What-is-RSSI-
and-its-acceptable-signal-strength-
26. Performance Analysis of LoRa Radio for an Indoor IoT Applications, Eyuel D.
Ayele, Chiel Hakkenberg_, Jan Pieter Meijers, Kyle Zhang, Nirvana Meratnia, Paul
J.M. Havinga Pervasive Systems Research Group, University of Twente, Enschede,
the Netherlands

41

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