A Review of Low Power Wide Area Technology in Licensed and Unlicensed Spectrum for IoT Use Cases

Bulletin of Electrical Engineering and Informatics
Vol. 7, No. 2, June 2018, pp. 183~190
ISSN: 2302-9285, DOI: 10.11591/eei.v7i2.1174  183
Journal homepage: http://journal.portalgaruda.org/index.php/EEI/index
A Review of Low Power Wide Area Technology in Licensed and
Unlicensed Spectrum for IoT Use Cases
Noor Laili Ismail1
, Murizah Kassim2
, Mahamod Ismail3
, Roslina Mohamad4
1,2,4
Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor, Malaysia
3
Department of Electrical, Electronics & System Engineering, Faculty of Engineering and Built Environment,
Universiti Kebangsaan Malaysia (UKM) 43600 Bangi, Selangor, Malaysia
Article Info ABSTRACT
Article history:
Received Feb 10, 2018
Revised Apr 16, 2018
Accepted Apr 30, 2018
There are many platforms in licensed and license free spectrum that support
LPWA (low power wide area) technology in the current markets. However,
lack of standardization of the different platforms can be a challenge for an
interoperable IoT environment. Therefore understanding the features of each
technology platform is essential to be able to differentiate how the
technology can be matched to a specific IoT application profile. This paper
provides an analysis of LPWA underlying technology in licensed and
unlicensed spectrum by means of literature review and comparative
assessment of Sigfox, LoRa, NB-IoT and LTE-M. We review their technical
aspect and discussed the pros and cons in terms of their technical and other
deployment features. General IoT application requirements is also presented
and linked to the deployment factors to give an insight of how different
applications profiles is associated to the right technology platform, thus
provide a simple guideline on how to match a specific application profile
with the best fit connectivity features.
Keywords:
IoT
LoRa
LPWA
LTE-M
NB-IoT
Sigfox
Copyright © 2018 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Noor Laili Ismail
Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM),
40450 Shah Alam, Selangor, Malaysia.
E-mail: lailiis@yahoo.co.uk
1. INTRODUCTION
IoT has become the notion of the future internet in which smart sensors, devices and everyday
objects are connected and communicated with each other without human intervention, and extends the
capability into smart object networking, a scenario that has help to set the groundwork for today’s IoT. The
goal of IoT is to bring smart objects or devices together anytime, anywhere in a universal network, creating
an intelligent system [2]. IoT has shifted computing paradigm from human oriented to autonomous smart
devices, commonly in monitoring, remote diagnostics & control, leading to cost savings. As IoT proliferates,
it will have an impact on the network traffic distribution, characteristics and performance [3], [4]. IoT will
demand a wide range of new technologies and skills, a new cloud service, a new network and hardware
platform, a new type of high volume data processing and so on. IoT innovation is geared to offer a wide
spectrum of new services, generate new market segments and revenues. This will result in high increasing
demand of network capacity by years [5], and even some of its various use cases is expected to introduce
different requirements on connectivity economically and technically. The advent of LPWA technology at this
point of time is seems to back the instances, for few primary reasons such as cost, coverage and power
consumption [6].
Supporting vasts connected devices that will potentially be mounted in remote areas require a very
low-end device cost and easy to install, not only because the number of devices could be huge, but also to
minimize the risk of theft. The need for a high capacity gateway is also important to limit the number of

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184
gateways, thus reduced the infrastructure cost. High power efficiency devices are as well critical to prolong
the network lifespan and avoid high battery maintenance cost. In IoT landscape especially in rural area,
monitoring might be placed in an area without wired infrastructure with no or very poor access to any cellular
base station. Therefore, the technology must be able to provide a good coverage service to enable
connectivity of the devices. The ability to scale efficiently and support diverse IoT requirements from
different use cases would also become important for massive IoT deployment in the long run. In physic law,
low power and wide coverage can be achieved by trading off the bit rate. This marks the unique characteristic
of LPWA technology as compared to traditional network connectivity in IoT landscape such as Bluetooth,
Zig-Bee, Wi-Fi and cellular [7].
2. RESEARCH METHOD
This paper provides an analysis of some LPWA underlying technology namely Sigfox, LoRa, NB-
IoT and LTE-M, its business model and ecosystem in licensed and unlicensed spectrum. Section 2 starts with
the technology evolution and the technical features of each. Section 3 addresses each technology features and
shortly discussed the pros and cons of each in terms of deployment factors. The nature of various IoT
applications is also listed to relate to the deployment factors and give an insight of different application
requirements against the right technology platform. This can serve as a guideline on how to match the best-fit
technology for specific application needs. Section 4 concludes the discussion with a general observation of
the market trend and current situation of LPWA landscape for IoT.
The technology that covers long range communication is somehow new. The drive began with
Sigfox, followed by LoRa and others in unlicensed band spectrum. With the recent announcement of 3GPP
standard release 12 and 13, LPWA technology is set to enter a new phase as cellular carriers are also offering
their IoT connectivity options via LTE-M and NB-IoT in 2017. Starting from here, LTE-M will be rolling out
its initial IoT connectivity in the US, while NB-IoT will initiate in Europe. This marks a significant
technology jump into IoT landscape on LPWAN. In LPWAN protocol, NB-IoT and LTE-M are using
licensed spectrum while Sigfox and LoRaWAN are using license free spectrum. Currently, there are many
license exempt spectrums exist in the market for LPWAN platform such as Weightless, Ingenu, M-Bus,
6Lowpan, but Sigfox and Lorawan are among the most popular at the time being.
2.1. PWA Underlying Technology in Licenced and License Free Spectrum
LoRa and Sigfox have a very different approach in terms of technology and business model. Both
are opposite technology but give similar outcomes, low power, wide range and cheap design. Sigfox is a
French startup company based in Tolouse, founded in 2009. Sigfox acts like a carrier where they sell
subscription for sending data via Sigfox proprietary network, thus its network layer specifications is not
publicly open [9]. The advantage is that they operate in license free spectrum, using cheap devices and offer
an extremely low recurring fee than typical GSM. LoRa is a technology developed by Cycleo in Genoble,
France. Semtech acquired the company and created LoRa Alliance™, an open non-profit association to
address the IoT market and drive the success of the LoRa protocol. The alliance collaborates by sharing of
knowledge and experience to ensure interoperability among operators in an open universal standard. Various
types of organizations and some GSM carriers globally have seen the opportunity to enter the IoT market and
subscribed to the alliance. LTE-M is a pure LTE solution optimized for IoT communications and is part of
3GPP Release 12 and 13 that was finalized in 2016. NB-IoT is another 3GPP Release 13 proposal which is
not based on LTE. In US mostly, it is not backward compatible with existing LTE, although is integrated in
the LTE standard. Both LoRa and Sigfox started their first implementation in Europe. While Sigfox is
pioneering the LPWAN technology earlier years back, LoRa had been rolled out in 2016 and currently is in
active deployment in few countries globally. For LTE-M, AT&T and Verizon are working on rolling out the
LTE-M initial version in the US, whereas NB-IoT will be Europe focused in which Huawei, Ericsson,
Qualcomm, and Vodafone are actively involved in putting the standard together.
2.2. Sigfox, LoRa, NB-IoT and LTE-M Technical Features
Sigfox is based on ultra-narrow band (UNB) binary phase-shift keying (BPSK) technology. It is
completely asynchronous and transmits at extremely low data rate across over hundreds of uplink channels.
Sigfox operates in the 200 kHz of the ISM band; each message is 100 Hz wide. An uplink message has up to
12 bytes payload with maximum frequency of 140 transmissions per day at a fix bit rate of 100 bps. For a 12-
byte data payload, a Sigfox frame will use 26 bytes in total. Sigfox has a very limited downlink channel with
8 bytes payload, available for premium subscribers [11]. It is power efficient as its lightweight protocol to
handle very small messages and data to send translated directly into less energy consumption and longer
battery life. Sigfox uses star topology network. Each device and base station has a unique Sigfox ID for

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A Review of Low Power Wide Area Technology in Licensed and Unlicensed Spectrum… (Noor Laili Ismail)
185
directly to a Sigfox cloud via IP link. The Sigfox station detects, demodulate and report the messages to
Sigfox cloud and back end (BE). The BE pushes the messages to business applications or a device
transmission authentication. Devices transmit messages to Sigfox station that connected client system. While
BE can connect and talk to Sigfox stations, none of them can connect back to the devices.
LoRa is the physical layer of Long Range radio modulation technique integrated with forward error
correcting capability. The radio modulation technique is using Chirp Spread Spectrum (CSS) technology that
can transmit data with signal strengths below the noise floor. It improves its’ link budget and immunity to
interference [12], [13]. LoRaWAN is referring to the MAC layer protocol. In LoRa modulation, spreading of
the spectrum is achieved by generating a chirp signal that continuously varies in frequency [14]. The
communication parameters such as bandwidth (BW), coding rate (CR) and spreading factors (SF) have a
significant effect on LoRa deployment scalability. The configuration details are described in paper [15]. By
applying different SF, signals are practically orthogonal to each other. This enables different data rates to be
demodulated concurrently on the same channel, thus increasing the network capacity. Data rate (DR) and link
budget (PRX) can be articulated as in Equation 1 and 2 [16].
(1)
(2)
LoRaWAN utilizes three device classes to support different types of application scenarios. The
different device classes enable trade off to be made between latency and power consumption. Class A
consumes the least energy and can be used for applications using sensors or actuators without latency
constraint. Downlink is only available shortly after two successful uplink transmissions. In contrast, Class C
is the most power starving as it allows end device to listen as often as possible on RX2. This profile matches
an application with no latency for downlink communication. Class B will have fixed interval time allocated
for the downlink and suitable for scenarios with low latency requirement [18]. LoRa uses pure ALOHA
random access scheme for simplicity. However, ALOHA contributes to message lost which leads to capacity
drop. LoRa packet structure starts with a preamble field [13], used to synchronize the receiver with the
incoming data flow. Next is a header field which provides information about the length and the CR. It uses
explicit mode. Third is a payload field, which contains the actual data. If the payload and CR are fix, implicit
mode is used by removing the header field, thus reduce the airtime. Cyclic redundancy check (CRC) is the
last field, which protects the payload integrity.
LoRaWAN is typically laid out in stars of stars topology [19]. The communication is bi-directional
although is uplink dominant. Messages from end devices get encrypted and spread out on different frequency
channels and SF to LoRa gateways so each transmission will not interfere with each other. The gateways
receive the messages and forward it to a central core network over Ethernet or 3G. The Network Server then
routes the messages to the correct end application. There is no association between end devices and
gateways, thus any gateways will pick up the messages within its range and forward it to the network server.
This feature allows simplicity for nodes mobility as no handover between gateways is required. The network
server has the intelligent to perform security check, filter duplicate messages, route the messages to an
application server, control radio configuration, send ACKs to gateways and monitor devices and gateways
[20]. Security in LoRaWAN is incorporated at the network and application layer to validate the nodes and to
protect application data from unauthorized access respectively.
LTE-M is an abbreviated version of LTE-MTC, which allows IoT devices operated on batteries to
connect directly to LTE network without a gateway. So to say, LTE-M is a 4G technology downgraded for
M2M communications. The LTE channel is made up of 230 kHz spectrum of Physical Resource Block
(PRB). LTE-M operates on a 1.4 MHz carrier, thus occupies six PRBs in LTE. For control information, IoT
devices will always listen to the six PRB and if to send data will be allocated a number of the PRBs. Power
Savings Mode (PSM) and extended discontinuous reception (eDRX) are proposed in Release 12 and 13
respectively to make LTE-M more power efficient [21]. PSM allows the IoT devices to enter a deep sleep
mode without having to re-join the network when it wakes up. In eDRX mode, IoT devices only wake up
occasionally while connected without losing its network registration [22]. LTE-M introduces half duplex
FDD and its band support is limited to sub-GHz band to further reduced cost. LTE-M offers 1Mbps DL and
500bps UL, which still considered high for M2M applications. LTE-M allows reuse of the LTE installed base
and benefits from all the security and privacy of mobile network features, such as entity authentication,
confidentiality, data integrity, and mobile equipment identification [23].
 
n
4
4
CR
Where
;
CR
*
SF
2
BW
*
SF
DR



M(dB)
-
(dB)
l
(dB)
L
-
(dB)
G
+
(dBm)
P
=
(dBm)
P CHANNEL
SYSTEM
SYSTEM
TX
RX

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186
NB-IoT is a new radio access technology which uses an even simpler access scheme, SCFDMA
(Single Carrier Frequency Division Multiple Access), thus further reduced cost and device complexity than
that of LTE-M, thus optimized it for low end IoT requirements. It is Half Duplex FDD and is based on single
PRB operation throughput. As the PHY layer has been changed, fundamental link budget gain is achieved
with targeted uplink coverage improvement of 20dB. The peak bit rate is 500 kps for DL and 40 kps for UL.
NB-IoT requires minimum of 180 KHz for both uplink and downlink channels. Therefore, it enables the
flexibility of 3 deployments options [20]. GSM operator can choose to replace one GSM carrier of 200 KHz
with NB-IoT or an LTE operator can allocate 180 KHz NB-IoT self-contain Physical Resource Block (PRB)
inside an LTE carrier for stand-alone and in band deployment respectively. For guard band deployment, NB-
IoT can use unutilized resource block within LTE guard band frequency with a guaranteed co-existence [24],
[25]. Similar to LTE-M, PSM and eDRX Cycle in idle and connected mode are also utilized to give a better
power efficiency. eDRX supports device configuration above the previous upper limit of 2.56 seconds [26].
Standard LTE grouped sub-carrier by 12, so individual downlink occupies 15 kHz. Sub carrier spacing and
slot, sub frame, and frame duration are 0.5 ms, 1 ms, and 10 ms respectively and is based on OFDMA [27].
The uplink is improved from OFDMA to SCFDMA and support both single and multi-tone transmission.
Single-tone is based on SCFDMA similar to conventional LTE, with the same 15 kHz subcarrier spacing, 0.5
ms slot, and 1 ms sub frame. It achieves the best coexistence performance as it is identical to conventional
LTE. Multi-tone transmission supports two options, 15 kHz or optional reduced 3.75 kHz sub-carrier.
Equation 3 and 4 below define the uplink (FUL) and downlink (FDL) frequency of NB-IoT [28].
(3)
(4)
Where MDL/UL = Offset of NB-IoT Channel Number to downlink/uplink, FDL/UL_low=
Downlink/uplink operating band, NDL/UL= downlink/uplink E-UTRA Absolute Radio Frequency Channel
Number (EARFCN), NoffDL/UL= Minimum range of NDL/UL for downlink/uplink.
To send UL data, User Plane CIoT EPS optimization and the Control Plane CIoT EPS optimization
were defined in the evolved packet system (EPS) [28]. UL data is transferred from the eNB (CIoT RAN) to
the MME on the Control Plane CIoT EPS optimization. Then, it can either be forwarded to the application
server (CIoT Services) through the Service Capability Exposure Function (SCEF) or through Serving
Gateway (SGW) and the Packet Data Network Gateway (PGW) path. Similarly, DL transmission takes the
same path in reverse direction using signaling radio bearer instead of data radio bearer, thus make it most
applicable for transmitting infrequent and small data packets. The SCEF is a new node designed for machine
data and only appropriate to deliver non-IP data over control plane. It is responsible for the network services
abstract interface such as authentication and authorization, discovery and access network capabilities. User
Plane CIoT EPS optimization supports both IP and non-IP data delivery. Data transported on the path to the
application server through the SGW and the PGW over radio bearers similar to the conventional data traffic.
Although it expedites series of data packets to be delivered, however it also crops some.
3. RESULTS AND ANALYSIS
IoT is not a single domination market. Whole range of different used cases and disparity of needs
will translate into different architecture and diverse price points. It may create a lot of opportunities to
network operators, system integrators or chip companies but it will become a challenge to end users in
choosing the right technology that best suit their application scenario [29]. So, it is important to capture the
application needs and recognize what each technology platform has to offer in terms of technical features,
supporting ecosystem and other deployment factors. Generally, the kind of connectivity required for either
smart building, health monitoring or industrial automotive is completely different from each other. In health
monitoring that involves life-threatening decisions or critical data streaming applications that cannot tolerate
in latency, time and reliability are the key consideration. On the contrary, applications like smart city and
environment monitoring that may have thousands of actuators will be focusing on coverage and battery life.
A connectivity option that may best suit an application profile may not work properly for the other
application scenario. For preliminary review and comparison, information on LoRa, Sigfox, NB-IoT and
LTE-M specification are shown in Table 1.
1)
+
(2M
0.0025
+
)
N
-
0.1(N
+
F
=
F DL
offDL
DL
DL_low
DL 
)
(2M
0.0025
+
)
N
-
0.1(N
+
F
=
F UL
offUL
UL
UL_low
UL 

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Table1. Comparison of LoRa, Sigfox, NB-IoT and LTE-M Specifications
Sigfox LoRawan NB-IoT LTE-M
Frequency Band
(Country based ISM
Band)
• EU (868MHz)
• US(902MHz)
[7]
• EU (433, 863-870 MHz)
• US (433, 902-928MHz)
• China (470-510MHz, 779-
787MHz)
• Asean (920-923.5MHz)
[30]
Licensed cellular (LTE)
frequency bands
Licensed cellular
(LTE) frequency
bands
Bandwidth
100 Hz
[31]
250 kHz and 125 kHz
[31]
200 kHz
[32]
1.4MHz
[32]
Uplink & Downlink /
Duplex Mode
UL: Data
DL: ACK
[33]
UL: Data
DL: Data + ACK
[33]
Half Duplex
[26]
Full / Half Duplex
[26]
Coverage Range
Urban: 3–10 km
Rural : 30–50 km
[14]
Urban: 3–5 km
Rural: 10–15 km
[9]
15 Km
[34]
11 Km
[34]
Maximum Data Rate
UL: 100 bps
DL: 600 bps
[7]
LoRa: 0.3 - 37.5k bps
FSK: 50 kbps
[7]
UL: 250 kbps
DL: 170 kbps
[26]
1Mbps(FDD)
[26]
Max #msgs/day
UL: 140 msgs
DL: 4 msgs
[11][31]
Unlimited Unlimited Unlimited
Battery Life
90 months
[7]
105 months
[7]
10 years
[21]
10 years
[21]
Authentication /
Encryption
No
[31]
AES - 128 b
[33]
Yes
[31]
Yes
[35]
Link Budget
UL: 158 dB
[36]
UL: 154 dB
[29]
164 dB
[32]
156dB
[32]
Payload size
UL:12 bytes
DL:8 bytes
[11][33]
19-250 bytes
[33]
1600 bytes
[31]
Latency
10s
[34]
10s
[34]
1.4 - 10s
[31]
10 – 15 ms
[31]
ADR No Yes No No
Localisation /
Mobility
No
[7]
Yes
[35]
No (Release 13)
[26]
Full mobility
[26]
Private Network No Yes No No
Module Cost
$2–5
[11]
$2–5
[11]
$8–12
[11]
$8–12
[11]
Application that transmits infrequently, has rarely burst data with a very limited downlink
capability, very small payload size and data rate, Sigfox can be a fantastic choice. Sigfox offers exceptionally
low hardware prices, as low as $2 per module [11]. In addition to good module price, LoRa also offers good
vendors’ ecosystem. LoRa is more open as it offered hybrid business models; either deployed your own
network and managed them privately or as carriers that are deploying LoRa network. LoRa supports
localization and also utilized adaptive data rate to achieve higher data rate. It offers more downlink capability
as compared to Sigfox. In many cases, they share a similar application use cases and are excellent option for
remote deployment of actuators or sensor based network. The deployments of LoRa and Sigfox are still
progressing, and currently the area covers by both are still relatively limited. The shortcoming of operating in
unlicensed band spectrum is that it has to deal with certain duty cycle imposed by different regions which
restricts the volume and frequency of traffic on devices and gateways, thus drop down the capacity. In some
regions, the operating frequency used by both LoRa and Sigfox is also shared by licensed user without duty
cycle limit, thus interference can become an issue. LoRa and Sigfox also do not have guaranteed SLA. Future
risk of this technology segment is that, as more players of this type of connectivity comes on board, the
network could be congested and they may suffer severe interference that place the network performance and
reliability at risk. Basic understanding of general IoT segments and application requirements with their use
cases are gathered in Table 2, which illustrated the potential best-fit technology platform against the distinct
requirements of diverse IoT applications.

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Table 2. General IoT Applications Requirements and Technology Fittings
Nature of Applications Application Domain Applications Specific
Best-fit / Potential
Technology
•Low periodic data
• Low data rate
• Small payload
• Rarely burst data
• No radical changes of data
• Long battery life
• Does not require QoS
• Limited downlink capability
• Limited LTE coverage
• Low cost
• Agriculture
• Smart City
• Environmental monitoring
• Smart Building
• Manufacturing
• Smart farming
• Smart lighting
• Smart parking
• Smart metering –Temperature &
humidity monitoring
• Manufacturing Automation
Sigfox, LoRa
• Good frequency data
• Good data rate
• Require QoS
• Low latency (sec)
• Dense populated areas with
good LTE coverage
• Environmental monitoring and
control
• Smart City
• Smart Building
• Manufacturing
• Wearable
• Gas/Smoke detectors
• Water level monitoring
• Smart metering
• Street light monitoring and control
• Smart Manufacturing
• Industrial monitoring
NB-IoT
• High frequency data
• High data rate
• High QoS
• Very low latency(ms)
• Dense populated areas with
very good LTE coverage
• Mobility
• Voice data
• Transportation and logistics
• Automotive Telematics
• Wearable
• Real-time grid monitoring
• Security and surveillance
• Asset trackers
• Telematics
• Point of Sale terminals
• Smart watches
• Fitness bands
• Patient monitors
• Alarm panels
• Gas/water meters
LTE-M
IoT applications profiles which may need higher bandwidth can choose higher bandwidth
connectivity solutions such as LTE-M and NB-IoT. NB-IoT is considered to be high end LPWA, targeted to
serve ultra-low end IoT application profiles. LTE-M is seems to stand distant apart from the rest of LPWA
technology in terms of data rate, potentially at the expense of higher battery consumption and cost. It also
supports voice data and is targeted to serve critical or high end IoT applications. Given a country wide
deployment in cities area, where power is not really an issue and devices are required to send more frequent
data, then NB-IoT offers a superior option at relatively low cost. Applications in this category are such as
smart city, smart metering, smart manufacturing and industrial monitoring. LTE-M for sure can serve better
for the same application niche but if it doesn’t need the kind of bit rate, it may defeat the preliminary purpose
of LPWA requirements. So, LTE-M is aimed to serve a critical and higher end applications that require real
time communication and far higher bit rate. For instances, applications like gaming, wearable such as patient
monitoring, alarm panels and point of sale terminals. Applications that sending streaming data or video such
as in security and surveillance, automotive telematic or industrial control can also consider using LTE-M.
Unlike LTE-M, NB-IoT does not support devices mobility and localization (as of Release 13). Module cost
for NB-IoT and LTE-M are around $8-$12 [11], but the current industry target for LPWA to get a reasonable
market share is less than $5.
The strength of NB-IoT and LTE-M is that they are standardized technology for the industry and
can make use of existing infrastructure to be cost effective and faster deployment. They are also supported by
a large ecosystem of MNOs which cover nationwide coverage and existing carriers and chip vendors that can
provide economy of scale. Cellular technology for quite long has been engaged and gained fair relationship
within telecommunication industry players. This advantage will help to provide customers with a high
confidence level with respect, reliability and security.Through a high-standardized technology and inter-
vendor interoperability, the technology is capable to guarantee certain level of SLA, which is very important
and is absence in the current unlicensed spectrum technologies mentioned above.
4. CONCLUSION
Based on the current development of LPWA technology in licensed and license free spectrum,
LPWA is seems to gain an increase market share in IoT industry. At present, it is naive to think that an IoT
connectivity option can serve every IoT application scenario. Therefore, choosing the best IoT connectivity
option for a specific need is very fundamental. This paper compared the differences of Sigfox, LoRa, NB-IoT
and LTE-M in terms of their technical features and shortly discussed the pros and cons of their deployment
factors. General IoT application requirements are also presented and associated to the deployment factors to
give an insight of different applications profiles against the right technology platform, thus provide a simple

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guideline on how to fit the right connectivity features for different applications profiles. It might be a stern
competition between the licensed and unlicensed spectrum, but both actually can co-exist as each of them has
a different business model and serve a different IoT market segments and application profiles. How all the
technologies will co-exist or compete with each other after the arrival of cellular technology are much depend
on how they are regulated to fit business requirements and demands, technically and economically.
ACKNOWLEDGEMENT
The author wish to thank Universiti Teknologi MARA (UiTM) and the Ministry of Higher
Education (MoHE) for the support grant of 600-RMI/RAGS 5/3 (35/2015) in this research.
REFERENCES
[1] Mehaseb, MA, Y Gadallah, H El-Hennawy. WSN Application Traffic Characterization for Integration within the
Internet of Things. IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks. Dalian, China.
2013.
[2] Satrya, GB, HT Reda, KJ Woo, PT Daely, SY Shin, S Chae. IoT and Public Weather Data Based Monitoring &
Control Software Development for Variable Color Temperature LED Street Lights. International Journal on
Advanced Science, Engineering and Information Technology. 2017; 7(2): 366-372.
[3] Kassim, M, M Ismail, MI Yusof. A New Adaptive Throughput Policy Algorithm On Campus Ip-Based Network
Internet Traffic. Journal of Theoretical and Applied Information Technology. 2015; 71(2).
[4] Kassim, M, M Ismail, MI Yusof. Statistical Analysis And Modeling Of Internet Traffic Ipbased Network For Tele-
Traffic Engineering. ARPN Journal of Engineering and Applied Sciences. 2015; 10(3).
[5] Kassim, M, NA Ayop. Adaptive Policing Algorithms on Inbound Internet Traffic Using Generalized Pareto model.
11th International Conference for Internet Technology and Secured Transactions (ICITST). Barcelona, Spain. 2016.
[6] Boulogeorgos, AAA, PD Diamantoulakis, GK Karagiannidis. Low Power Wide Area Networks (LPWANs) for
Internet of Things (IoT) Applications: Research Challenges and Future Trends. ArXiv e-prints, 2016.
[7] Raza, U, P Kulkarni, M Sooriyabandara. Low Power Wide Area Networks: An Overview. IEEE Communications
Surveys & Tutorials, 2017; 19(2): 855-873.
[8] Margelis, G, D Kaleshi, P Thomas. Low Throughput Networks for the IoT: Lessons learned from industrial
implementations. IEEE 2nd World Forum on Internet of Things (WF-IoT). 2015.
[9] Centenaro, M, L Vangelista, A Zanella, M Zorzi. Long-range communications in unlicensed bands: The rising
stars in the IoT and smart city scenarios. IEEE Wireless Communications, 2016; 23(5): 60-67.
[10] Ali, A, GA Shah, J Arshad. Energy efficient techniques for M2M communication: A survey. Journal of Network
and Computer Applications, 2016. 68: 42-55.
[11] Adelantado, F, X Vilajosana, P Tuset-Peiro, B Martinez, J Melia, T Watteyne. Understanding the Limits of
LoRaWAN. IEEE Communications Magazine. 2017; 55(9).
[12] Aref, M, A Sikora. Free space range measurements with Semtech Lora technology. 2nd International Symposium
on Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems.
Offenburg, Germany. 2014.
[13] Bor, M, J Vidler, U Roedig. LoRa for the Internet of Things. Proceedings of the International Conference on
Embedded Wireless Systems and Networks. Graz, Austria. 2016; 361-366.
[14] Augustin, A, J Yi, T Clausen, W Townsley. A Study of LoRa: Long Range & Low Power Networks for the Internet
of Things. Sensors. 2016; 16(9): 466.
[15] Bor, M, U Roedig, T Voigt, J Alonso. Do LoRa Low-Power Wide-Area Networks Scale? The 19th ACM
International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems. Malta. 2016.
[16] Voigt, T, M Bor, U Roedig, J Alonso. Mitigating Inter-network Interference in LoRa Networks. Computer Science
- Networking and Internet Architecture. 2016.
[17] Ducrot, N, D Ray, A Saadani, O Hersent, G Pop, G Remond. LoRa Device Developer Guide. Orange Connected
Objects & Partnerships 2016. Available from: https://partner.orange.com/wp-content/uploads/2016/04/LoRa-
Device-Developer-Guide-Orange.pdf.
[18] Neumann, P, J Montavont, T Noël. Indoor deployment of low-power wide area networks (LPWAN): A LoRaWAN
case study. IEEE 12th International Conference on Wireless and Mobile Computing, Networking and
Communications (WiMob). New York, USA. 2016.
[19] Kim, B, K-i Hwang. Cooperative Downlink Listening for Low-Power Long-Range Wide-Area Network. MDPI
Sustainability Journal. 2017; 9: 627.
[20] A technical overview of LoRa® and LoRaWAN™. Technical Marketing Workgroup 1.0 2015. Available from:
https://www.kivi.nl/uploads/media/56992a8894516/LoRaWAN101.pdf.
[21] Zayas, AD, P Merino. The 3GPP NB-IoT system architecture for the Internet of Things. IEEE International
Conference on Communications Workshops (ICC Workshops). Paris, France. 2017.
[22] LTE-M – Optimizing LTE for the Internet of Things. Nokia Networks white paper 2015. Available from:
https://novotech.com/docs/default-source/default-document-library/lte-m-optimizing-lte-for-the-internet-of-
things.pdf?sfvrsn=0.

 ISSN: 2302-9285
BEEI, Vol. 7, No. 2, June 2018 : 183 – 190
190
[23] Grant, S. 3GPP Low Power Wide Area Technologies. GSMA Mobile IoT Industry Alignment group 2016 1
September 2016. Available from: https://www.gsma.com/iot/wp-content/uploads/2016/10/3GPP-Low-Power-
Wide-Area-Technologies-GSMA-White-Paper.pdf.
[24] Beyene, YD, R Jantti, O Tirkkonen, K Ruttik, S Iraji, A Larmo, T Tirronen, J Torsner. NB-IoT Technology
Overview and Experience from Cloud-RAN Implementation. IEEE Wireless Communications. 2017; 24(3): 26-32.
[25] Wang, Y YPE, X Lin, A Adhikary, A Grovlen, Y Sui, Y Blankenship, J Bergman, HS Razaghi. A Primer on 3GPP
Narrowband Internet of Things. IEEE Communications Magazine. 2017.
[26] LTE evolution for IoT connectivity. Nokia white paper 2017; Available from:
https://resources.ext.nokia.com/asset/200178.
[27] Schlienz, J, D Raddino. Narrowband Internet of Things. Rohde & Schwarz white paper 2016. Available from:
https://www.rohde-schwarz.com/us/applications/narrowband-internet-of-things-white-paper_230854-314242.html.
[28] Sinha, RS, Y Wei, S-H Hwang. A survey on LPWA technology: LoRa and NB-IoT. ICT Express. 2017; 3(1): 14-
21.
[29] Al-Fuqaha, A, M Guizani, M Mohammadi, M Aledhari, M Ayyash. Internet of Things: A Survey on Enabling
Technologies, Protocols, and Applications. IEEE Communications Surveys & Tutorials. 2015;17(4): 2347-2376.
[30] Lavric, A, V Popa. Internet of Things and LoRa Low-Power Wide-Area Networks: A survey. IEEE International
Symposium on Signals, Circuits and Systems (ISSCS). Iasi, Romania. 2017.
[31] Mekki K, Bajic E, Chaxel F, Meyer F. A comparative study of LPWAN technologies for large-scale IoT
deployment. ICT Express. 2018.
[32] Lauridsen, M, LC Gimenez, I Rodriguez, TB Sorensen, P Mogensen. From LTE to 5G for Connected Mobility.
IEEE Communications Magazine. 2017; 55(3): 156-162.
[33] Nolan, KE, W Guibene, MY Kelly. An evaluation of low power wide area network technologies for the Internet of
Things. IEEE 2016 International Wireless Communications and Mobile Computing Conference (IWCMC). Paphos,
Cyprus. 2016.
[34] Wang, H, AO Fapojuwo. A Survey of Enabling Technologies of Low Power and Long Range Machine-to-Machine
Communications. IEEE Communications Surveys & Tutorials. 2017; 19(4): 2621-2639.
[35] Silva, JdC, JJPC Rodrigues, AM Alberti, P Solic, ALL Aquino. LoRaWAN - A low power WAN protocol for
Internet of Things: A review and opportunities. 2nd International Multi- disciplinary Conference on Computer and
Energy Science (SpliTech). Split, Croatia: IEEE. 2017.
[36] Vejlgaard, B, M Lauridsen, H Nguyen, IZ Kovacs, P Mogensen, M Sorensen. Coverage and Capacity Analysis of
Sigfox, LoRa, GPRS, and NB-IoT. 2017 IEEE 85th Vehicular Technology Conference (VTC Spring). Sydney,
NSW, Australia. 2017.

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