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A study of LoRa low power and wide area network technology

A Study of LoRa Low Power and Wide Area
Network Technology
Umber Noreen
e de Bretagne Occidentale
Brest, France
ene Bounceur
e de Bretagne Occidentale
Brest, France
Laurent Clavier
Lille, France
AbstractLoRaT M is low power wide area wireless network
(LPWAN) protocol for Internet of Things (IoTs) applications.
LPWAN has been enabling technology of large scale wireless
sensor networks (WSNs). Effective cost, long range and energy
efficiency of LPWANs make them most suitable candidates for
smart city applications. These technologies offer novel commu-
nication paradigm to address discrete IoT’s applications. LoRa
is a recently proposed LPWAN technology based on spread
spectrum technique with a wider band. LoRa uses the entire
channel bandwidth to broadcast a signal which makes it resistant
to channel noise, long term relative frequency, doppler effects
and fading. This paper focuses on the emerging transmission
technologies dedicated to IoT networks. Characteristics of LoRa
are based on three basic parameters: Code Rate (CR), Spreading
Factor (SF) and Bandwidth (BW). This paper provides in depth
analysis of the impact of these three parameters on the data rate
and time on air.
KeywordsWireless sensor Networks, LoRaT M , LPWAN,
Smart cities, Internet of things.
The evolving field of WSNs has an extensive range of
potential applications in industry, science, transportation, civil
infrastructure and security etc. WSNs comprised sensing (mea-
suring), computation, and communication into a single tiny
device called sensor node [1] [2]. WSNs typically consist of
a large number of heterogeneous sensor devices that contain
processing capability, sensor(s) and/or actuator(s), a power
source (batteries and eventually some energy harvesting mod-
ules), multiple types of memory and a radio frequency (RF)
based transceiver. This large number of sensors are densely
deployed over a large field and inter-networked together. They
monitor physical or environmental conditions that generate
sensor readings and deliver them to a sink node in order to
be further processed [2].
Wireless network industry is gradually changing their in-
terest towards LPWAN. LPWAN technologies (SigFox, LoRa,
Weightless-W etc) successfully propose wide area connectivity
from a few to tens of kilometers for low data rate, low
power and low throughput applications [3]. Their market is
anticipated to be huge. Nearly a quarter of overall thirty billion
IoT/M2M devices are assumed to be connected through the
internet using LPWAN [4]. Smart cities are considered as the
biggest potential customers of LPWAN, which includes smart
metering, smart grids, smart parking, optimized driving and
walking routes, energy radiation measurements, measurements
of nuclear power station radiation, weather adaptive street
lighting, smart waste management, structural health monitor-
ing, air pollution monitoring, water leakages monitoring, forest
fire detection and so forth, as also shown through Figure 1.
In a wireless sensor network composed of many spatially
scattered wireless nodes, communication is constrained by
various impairments such as the wireless propagation effects,
network interference, and thermal noise. The effects of signals
propagation in the wireless environment include the attenuation
of radiated signals with distance (also known as path loss),
the blocking of signals caused by large obstacles (also called
shadowing), and the reception of multiple copies of the same
transmitted signal (also called multipath fading) [5]. The net-
work interference is due to accumulation of unwanted signals
radiated by other transmitters from inside or outside of the
network, which undesirably affects signal reception at receiver
nodes in the network. The thermal noise is introduced by the
receiver electronics and is usually modeled as additive white
Gaussian noise (AWGN).
Due to the scarcity of radio spectrum, it is not completely
possible for large wireless networks to communicate without
interference. Probably other radio devices will make transmis-
sion using the same radio frequency band at the same time.
Consequently, at the receiver, many undesired signals from
interfering transmitters will add to the desired transmitter’s
signal. This phenomenon is called interference, and it causes a
performance degradation of communication networks [6] [7].
This paper gives a short description of Bluetooth, ZigBee
and Wi-Fi, and the brief description of LoRa as LPWAN
Rest of article is organized as follows. Section II de-
fines some of the existing potential candidates for LPWAN
technologies. Section III describes some key features of
LoRa technology. Conclusive remarks are drawn at the end
in Sections IV.
Several low power wireless technologies can be utilized
for WSNs. Choice of a particular technology for a particular
application can be made by examining required data rates,
power consumption and range [8]. Some of these major
communication technologies, which utilizes licensed free ISM
bands, have been discussed and compared further in this
Fig. 1. Smart city applications
Bluetooth ZigBee Wi-Fi
Max. end-devices 255 (2 Billion in BLE) more than 64000 Depends on number
of IP addresses
Peak Current
Consumption 30 mA 30 mA 100 mA
Range 10 m 10 to 100 m 100 m
Data Rate 1 Mbps up to 250 kbps 11 Mbps and
54 Mbps
Relative Cost Low Low Medium
Topology Star Star and Mesh Star and
FHSS (Frequency Hopping
Spread Spectrum)
DSSS (Direct Spread
Spectrum Sequence)
OFDM (Orthogonal Frequency
Division Multiplexing)
section. Also, comparison of some basic features related to
these technologies are highlighted in Table I.
A. Bluetooth
Bluetooth is a wireless personal area network (WPAN)
technology based on IEEE standard 802.15.1. It was launched
in 1994 by Ericsson. It utilizes licensed free 2.4 GHz frequency
band with up to 1MHz channel frequency band. Bluetooth
adopts frequency hopping spread spectrum (FHSS) transmis-
sion technique and offers maximum data rate up to 1Mb/s.
Conventional Bluetooth can connect eight nodes to each other
with seven slave nodes and one master node. Bluetooth based
networks can be deployed in a point-to-point master-slave
manner. The power consumption of any type of communication
network strongly depends on the distance between transmitter
and receiver nodes, the preferred power to be retained by the
signal and most importantly type of data being exchanged.
Bluetooth based networks are able to exchange more or less
all types of data like multimedia or text etc. [9].
Another extension of Bluetooth was proposed as Bluetooth
4.0 also known as Bluetooth Low Energy (BLE) after the
Bluetooth 1.0, 2.0 and 3.0. It was designed as alternative
low power solution to classic Bluetooth. Bluetooth and BLE
are used for different purposes. Conventional Bluetooth can
handle almost all the variety of data, but it consumes more
power and cost. BLE is used for low data rate applications,
and can therefore, have longer battery life time. Like classic
Bluetooth, BLE also utilizes licensed free ISM band and
offers 40 different channels. Three among these are labeled
as advertising channels and are used establish a connection.
The remaining 37 channels are labeled as data channels and as
name suggest are used to exchanged data after the connection
established between sender and receiver [9].
B. ZigBee
The IEEE standard 802.15.4 commonly known as ZigBee
is most popular choice in Low Rate Wireless Personal Area
Networks (LR-WPAN) and WSNs. IEEE standard 802.15.4
has only defined the characteristics of physical (PHY) layer
and Medium Access Control (MAC) layer. These charac-
teristics have been adopted by ZigBee. ZigBee has defined
the specifications for network layer and application layer. In
wireless networks, MAC layer allows efficient access of wire-
less physical medium, wireless node associations, data frame
validation and security services. Based on the application
requirements, ZigBee based networks can be centralized and/or
decentralized [10].
ZigBee based wireless network can adapt star topol-
ogy and/or peer-to-peer topology. Star topology offers both
contention-based and contention-free wireless medium access
to its member nodes. In peer-to-peer topology, nodes can
communicate with other nodes within their radio range. De-
centralized or peer-to-peer topology based wireless network
supports contention-based un-slotted carrier sense multiple
access with collision avoidance CSMA/CA wireless MAC
protocol. In CSMA/CA protocol nodes compete with each
other to access the shared wireless medium. More than 64000
nodes can be connected in zigBee where each one needs only
to allocate a role. ZigBee uses direct spread spectrum sequence
(DSSS) transmission technique and offers up to 250 kbps of
data rate in 2.4 GHz frequency band [11] [12]. Spreading
techniques are applied to increase the signal bandwidth (BW).
DSSS phase shifts a sine wave pseudo-randomly with ”chips”.
These continuous strings or chips are called pseudo-noise (PN)
code symbols or PN-sequence. This phenomenon helps to
increase the signal power, decrease the interference effects on
received signal, allows sharing of spectrum among multiple
users and provides resistance against intended or unintended
signal jamming. PN-sequence remains known at transmitter
and receiver. ZigBee is low power and low cost system which
makes it well suited for WSNs [13]
C. Wi-Fi
Although, Bluetooth and ZigBee are low power and low
complexity wireless sensor technologies, but they have some
limitations, such as low data rate, short range, and less pene-
tration across obstacles. With the advancement in the fields of
wireless and system on chip (SoC) technologies, a number
of Wi-Fi based wireless sensor SoCs have been developed
for low power wireless sensor applications [14]. Wi-Fi is
a wireless local area network (LAN) technology based on
IEEE standard 802.11. In literature though, IEEE standard
802.11 and Wi-Fi is used interchangeably, and we will also
follow the same convention in this paper. IEEE standard 802.11
provides set of specifications for media access control (MAC)
and physical layer (PHY) for implementing wireless WLAN
in the frequency band of 900 MHz, 2.4GHz, 3.6GHz, 5GHz
and 60 GHz [15]. 2.4 GHz frequency operation band is most
common in many extensions of IEEE standard 802.11, with
14 distinct channels. Wi-Fi based WSNs could be network-
centered or data-centered networks and consists of a large
Fig. 2. Up-chirp and down-chirp waveform
number of low power nodes distributed over the large area.
Wi-Fi offers data rate of 11Mbps to 54Mbps (250 Mbps: Wi-Fi
Direct) with 100 m transmission range. The number of nodes
in the network depends on the number of IP addresses.
Orthogonal Frequency Division Multiplexing (OFDM) is
the variant of Multi-Carrier Modulation and is employed in
several IEEE Wireless Local Area Network (WLAN) standards
like IEEE 802.11a and IEEE 802.11g. IEEE standards 802.11n
and 802.11ac also utilize OFDM modulation technique but
coupled with a multiple input multiple output (MIMO) [16].
D. SigFox
It supports narrowband (or ultra narrowband) technology
with standard radio transmission method called binary phase-
shift keying (BPSK) (going up). Which allows the receiver to
only listen in a very small part of the spectrum that mitigates
the noise impact. It requires an inexpensive endpoint radio and
a more sophisticated base station to manage the network. These
transmissions use unlicensed frequency bands [15]. Section II
defines some of the existing potential candidates for LPWAN
LPWAN is the rapidly growing area of the communication
industry. Amongst the recently introduced low power and long
range technologies, the semiconductor manufacturer Semtech
has introduced extensive utilization of advanced spread spec-
trum technologies with their Long-Range LoRaT M product
line. In comparison with legacy modulation techniques, the
spread spectrum modulation technique implied in LoRa assures
an increased link budget as well as better immunity to network
interferences. LoRa utilizes wider band usually of 125 kHz
or more to broadcast the signal. LoRa allows the usage of
scaleable BW of 125kH z, 250kHz or 500kHz [17]. Usage of
a wider band makes LoRa resistant to channel noise, long term
relative frequency, doppler effects and fading. But, spreading
a narrowband signal over wider band makes less efficient use
of spectrum until the end devices utilize orthogonal sequences
and/or different channels which result higher overall system
The transmitter generates chirp signals by varying their
frequency over time and keeping phase between adjacent
symbols constant. The transmitted signal is noise alike signal
which is resistant to multipath fading and doppler shifts, robust
CR value 1234
no. of redundant bits 1234
Coding rate 4/5 2/3 4/7 1/2
Fig. 3. Data Rates offered in LoRa with different code rate and bandwidth
values, (SF = 7).
to interferences and jamming attacks and difficult to decode
by an eavesdropper. Receiver can decodes even a severely
attenuated signal 19.5dBs below the noise level [18]. Chirp
spread spectrum (CSS) is a subcategory of DSSS, and it allows
to send one bit per each chirp. It takes much larger BW for
transmission than actually required for the considered data rate.
A single chirp waveform can be defined as:
c(t) = (exp((t)),T
0, otherwise (1)
where φ(t)is the phase of chirp waveform. Examples of up-
chirp and a down-chirp waveform are shown in Figure 2.
Apparently, characteristics of LoRa modulation depends on
following three parameters:
Code rate (CR)
Forward error correction (FEC) techniques are used in Lora
to further increase the receiver sensitivity. Code rate defines the
amount of FEC. LoRa offers CR values between 0 to 4, where
CR = 0 means no FEC. LoRa uses code rates of 4/5,2/3,4/7
and 1/2,also shown in Table II. Which means, if the code
rate is denoted as k=n, where k represent useful information,
and encoder generates nnumber of output bits, then nk
will be the redundant bits. The redundancy allows the receiver
to detect and often to correct errors in the message, but it
also decreases the effective data rate. Data rates corresponds
to each CR value in LoRa are shown in Figure 3, over three
bandwidths. As the CR value increases, the effective data rate
decreases in each bandwidth spectrum.
Spreading factor (SF)
LORa employs multiple orthogonal spreading factors (be-
tween 7 to 12). SF provides a tradeoff between data rate
Fig. 4. Spreading in LoRa
Fig. 5. Data Rates offered in LoRa with different spreading factor and
bandwidth values, (CR = 0).
Spreading Factor (SF) Chip Length 2SF
7 128
8 256
9 512
10 1024
11 2048
12 4096
and range. Choice of higher spreading factor can increase
the range but decreases the data rate and vice versa. Each
symbol is spread by a spreading code of length 2SF chips.
At the transmitter, the spreading code is subdivided into codes
of length 2SF /S F . Then each bit of symbol is spread using
the subcode also shown in Figure 4. So, it takes 2SF chips
for spreading of one symbol (SF bits ×2SF =S F ), as
shown in Table III. This spreading code is also known at the
receiver. The substitution of one symbol for multiple chips
of information means that the spreading factor has a direct
influence on the effective data rate [19]. The relation between
the data rate and the choice of SF is shown in Figure 5, over
three bandwidths.
At the receiver, spreading code is multiplied by the received
bits to regenerate the input data. Spreading mechanism can also
see in Figure 4.
Bandwidth (BW)
LoRa provides three scaleable BW settings of
125kH z, 250kHz and 500kHz also shown in Figure
6. Transmitter sends the spreaded data at a chip rate equal
Fig. 6. The LoRa Bandwidth Corresponds to the Double Sided Transmit
Spectrum Bandwidth
to the system bandwidth in chips per-second-per-Hertz. So a
LoRa bandwidth of 125 kHz corresponds to a chip rate of
125 kcps.
A. Packet Structure
Figure 7 shows packet structure used by LoRa. LoRa
offers maximum packet size of 256 bytes. The LoRa packet is
composed as follows [20]:
Preamble field: is used for the synchronization pur-
poses. The receiver synchronized with the incoming
data flow.
Header field: depends on the choice of two available
operation modes. In default explicit operational mode,
the number of bytes in the header field specifies
forward error correction (FEC) code rate, payload
length and presence of CRC in the frame. The second
implicit operational mode specifies that coding rate
and payload in a frame are fixed. In this mode, frame
doesn’t contains this field, which gives reduction in
transmission time. Header field also contains 2 byte
CRC field which allows the receiver to discard packets
with invalid header. Header field along with its CRC
field are 4 bytes long and are encoded with 1/2
coding rate, while coding rate for the rest of the frame
specifies in PHY header. The first byte of header field
specifies the payload length.
Payload field: Maximum payload varies from 2to 255
bytes. This field further contains following fields:
MAC header: defines the frame type (data
or acknowledgment), protocol version and its
direction (uplink or downlink).
MAC payload: contains actual data.
MIC: is used as the digital signature of the
CRC: is optional and comprises cyclic redundancy
check (CRC) bytes for error protection for payload
(2 bytes).
B. Time on Air
For LoRa, the actual time on the air for a packet can be
defined as:
Tpacket =Tpreamble +Tpayload (2)
Fig. 7. LoRaT M packet structure
where Tpreamble is preamble duration and Tpayload is payload
duration. Tpreamble can b defined as:
Tpreamble = (npreamble + 4.25)Ts(3)
where npreamble is the preamble length and Tsdenotes time
of 1 symbol and
Ts= 1/Rs(4)
with SF as spreading factor, Rsis symbol rate which is
Rs=BW/2SF (5)
The payload time is:
Tpayload =P LS ymb ×Ts(6)
P LSy mb = 8 + max(ceil(8P L4SF +28+16C RC20H
4(SF 2DE ))(CR +
with the following explanations:
P L : number of payload bytes.
H: 0 when the header is enabled and 1 when there
is no header.
DE : 1 for enabled low data rate optimization and 0
for vice versa.
CR : code rate.
So total time on the air taken by LoRa devices can be
defined by using Equations 2, 3 and 6.
Tpacket =Ts(npreamble +P LS ymb + 4.25) (7)
From the above calculation, one can say that spreading
factor has a direct influence on the time on air of the LoRa
packet. Figure 8 shows time on air for a LoRa frame with
different payload sizes and SF values. Time on air increases
with the increase in payload size and SF values. Although
higher spreading values highly influence the time on air of a
LoRa packet, but time on air also varied with the change in
code rate value. This variation is shown in Figure 9.
Same as SF and C R, the third parameter of LoRa mod-
ulation bandwidth, also influence the time on air of a packet.
Higher the bandwidth means lower the time on air. This is
shown in Figure 10, with different payload values and CR = 0,
SF = 7.
Fig. 8. LoRaT M packet time on air with B W = 125 kH z and CR = 0
Fig. 9. LoRaT M packet time on air with B W = 125 kH z and SF = 7
Various LPWAN technologies are currently contending to
gain an edge over the competition and provide the massive
connectivity that will be required by the world in which
everyday objects are expected to be connected through wireless
network in order to communicate with each other. This paper
focused on one of the most prominent LPWAN technology:
LoRaT M .
In this work, we have analyzed the performance of LoRa,
based on its three basic parameters: code rate, spreading factor
and bandwidth. Lora offers five code rates for forward error
correction which permits the recovery of bits of information
due to corruption by interference. Similarly higher spreading
factor provides longer range. The spreading codes correspond
to each SF are considered as orthogonal. This means that
multiple frames can be exchanged in the network at the same
time, using one the six different (SF = 7,8,9,10,12). An
increase in CR and S F values decreases the effective data
rate and causes increase in time on air of LoRa packet. Choice
of bandwidth also influences on data rate and time on air of a
Fig. 10. LoRaT M packet time on air with C R = 0 and S F = 7
This work is part of the research project PERSEPTEUR,
supported by the french national research agency ANR.
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... Signal interference or interference in overlapping bands distorts so that AWGN processes the following procedure. This study tested the sending of data messages with several iterations to see the system's reliability [20]. Either unlicensed spectrum causes AWGN and fading interference. ...
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In addition to long battery life and low cost, coverage is one of the most critical performance metrics for the low power wide area networks (LPWAN). In this work we study the coverage of the recently developed LoRa LPWAN technology via real-life measurements. The experiments were conducted in the city of Oulu, Finland, using the commercially available equipment. The measurements were executed for the 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) was reporting its data to a base station. For a node operating in the 868 MHz ISM band using 14 dBm transmit power and the maximum spreading factor, we have obtained the maximum communication range of over 15 km on ground and close to 30 km on water. Besides the actual measurements, in the paper we also present a channel attenuation model derived from the measurement data. The model can be used to estimate the path loss in 868 MHz ISM band in an area similar to Oulu, Finland.
Conference Paper
Smart Grids (SG) may be the most significant technological change in the history of electric grids, that can help curb the looming energy crisis worldwide, with intelligent generation, transmission and distribution of energy using a robust communication network. Power lines are a very promising solution for carrying data to serve as broadband access network in the context of SG, along with the wireless communication techniques. This paper investigates the design and simulation of a digital communication system optimized for Power Line Communication (PLC) in Smart Grids. For the proposed PLC transceiver, we consider Discrete Multitone (DMT) modulation based on a modified bit loading technique for the subcarriers. Our results reveal that the proposed incremental bit loading algorithm enhances data rate, and reduces computation time, as compared to the originally proposed incremental bit loading algorithm for PLC.
Radio communication is considered as a method for providing remote terminal access to computers. Digital byte streams from each terminal are partitioned into packets (blocks) and transmitted in a burst mode over a shared radio channel. When many terminals operate in this fashion, transmissions may conflict with and destroy each other. A means for controlling this is for the terminal to sense the presence of other transmissions; this leads to a new method for multiplexing in a packet radio environment: carrier sense multiple access (CSMA). Two protocols are described for CSMA and their throughput-delay characteristics are given. These results show the large advantage CSMA provides as compared to the random ALOHA access modes.
In this paper, we introduce a mathematical framework for the characterization of network interference in wireless systems. We consider a network in which the interferers are scattered according to a spatial Poisson process and are operating asynchronously in a wireless environment subject to path loss, shadowing, and multipath fading. We start by determining the statistical distribution of the aggregate network interference. We then investigate four applications of the proposed model: 1) interference in cognitive radio networks; 2) interference in wireless packet networks; 3) spectrum of the aggregate radio-frequency emission of wireless networks; and 4) coexistence between ultrawideband and narrowband systems. Our framework accounts for all the essential physical parameters that affect network interference, such as the wireless propagation effects, the transmission technology, the spatial density of interferers, and the transmitted power of the interferers.
Conference Paper
Bluetooth, ultra-wideband (UWB), ZigBee, and Wi-Fi are four popular wireless standards for short-range communications. Specifically, ZigBee network is an emerging technology designed for low cost, low power consumption and low-rate wireless personal area networks (LR-WPAN) with a focus on the device-level communication for enabling the wireless sensor networks. In this paper, after a brief overview of the four short-range wireless standards, the developed ZigBee platforms, ITRI ZBnode, have been presented for wireless sensor networking applications. Moreover, design issues for ZigBee industrial applications and the experimental implementation have been demonstrated via a multi-hop tree network.
Conference Paper
In order to improve coverage and alleviate traffic congestion in single-hop cellular networks (SCN), such as GSM, a new radio network architecture, multihop cellular networks (MCN), was proposed and analyzed (see Lin, Y.D. et al., IEEE INFOCOM, 2000). MCN architecture can improve the coverage and system capacity of SCNs by up to 40%. A detailed concept for realizing the MCN architecture was suggested by R. Ananthapadmanabha, et al. (see Proc. PIMRC, 2001), where a cellular based multihop routing protocol was developed and investigated. Their results indicate that MCN with the cellular based routing protocol provides much higher system throughput than SCN. However the paper gave no reasons for using cellular based routing instead of the ad hoc multihop routing protocols specified by IETF (see This paper is intended to fill that gap with the help of an analysis of routing protocol efficiency. We compare a cellular based routing protocol with three ad hoc routing protocols, DSR, AODV and DSDV. Based on analytical results, it can be concluded that the overhead of the cellular based routing protocol is not heavily influenced by network size and mobility. This translates to excellent scalability for large and dynamic MCNs, while AODV, DSR and DSDV are suitable for MCNs with a small number of hops and low mobility.