Analysis and Simulation of Cellular IoT (NB-IoT, LTE-M, LTE CAT0, 5G)

This report provides a comprehensive analysis of cellular IoT technologies, focusing on NB-IoT, LTE-M, and 5G networks. It begins with an introduction to cellular networks and the evolution of low-powered IoT based LPWAN systems, including their origins and applications. The report delves into the 4G-based cellular wireless networks, discussing their features, similarities, and differences. It also explores the emerging trend of 5G, highlighting its enhancements for fixed wireless access, increased bandwidth, and low-power wide area applications. The report addresses IoT receiver requirements, including received signal strength and frequency reuse, and discusses the issues related to cellular IoT. Finally, it uses CellPlaner to simulate the air interface, providing practical insights into network design and performance.

COURSE TITLE: Telecommunications
Course Code:
Task: Group Assignment
SUBMITTED BY
SUBMITTED TO
DATE: September 22, 2019

Contents
Table of Figures...........................................................................................................................................iii
Introduction.................................................................................................................................................1
Origin of low-powered IoT based LPWAN systems......................................................................................1
4G based cellular wireless networks...........................................................................................................3
New trend: 5G.............................................................................................................................................5
IoT receiver requirements...........................................................................................................................6
Received signal strength-.........................................................................................................................6
Frequency reuse factor-..........................................................................................................................6
Transmit power requirement..................................................................................................................6
Issues related to cellular IoT........................................................................................................................8
Using CellPlaner to simulate air interface....................................................................................................9
REFERENCES..............................................................................................................................................14

Table of Figures
Figure 1: LPWA Cellular IoT.........................................................................................................................4
Figure 2: Smart City.....................................................................................................................................8
Figure 3: CellPlaner Simulator.....................................................................................................................9
Figure 4: Smart city Position......................................................................................................................10
Figure 5: Simulate Smart City....................................................................................................................10
Figure 6: Simulation...................................................................................................................................11

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Key Terms: Cellular Networks, Cellular IoT, Internet of Things IoT, 5G, 4G, Low Power Wide
Area Networks LPWAN
Introduction
Cellular networks are wireless networks in which the last communication link is wireless i.e.
transmission of information or power happens without any physical connection between the
communicating node. It is distributed over wide geographical area divided into cells. Every cell
in the geographical area is served by one transmitter or a base station. The base station provides
geographical network coverage through which data in the form of voice, audio or visual is
transmitted. Cellular IoT relies on the existing cellular network infrastructure to enhance
communication amongst IoT devices
Origin of low-powered IoT based LPWAN systems
Low- power wide area network (LPWAN) is a wireless telecommunication wide area network
that is designed specifically to permit long rage communications at low bit rate among several
connected devices. These networks uses low power but carries little amounts of data and hence
the name [1]. They operate on a bit rate that is between 0.3 kbps and 50 kbps per channel. This
diverges from wide area network which is designed to connect users or businesses that carries
more data but consumes a lot of power.
These networks are more closely related to alarm to Alarmnet which was built and designed by
ADEMCO Company. It operated in the range of 928 MHz band and was designed was designed
with low data rates. It sent very little amount of data. They were mainly used to monitor alarm
panels. In the 1990’s cellular network realized that they could carry data as well as voice and
this saw the rebirth of 2G networks. As result of, many alarm panel networks migrated to cellular
network in order to take advantage of the widespread coverage and very low hardware costs.
The ARDIS is an all in one platform which was that was designed for data applications. It was
developed and owned by the Motorola Company in the 1980’s. It was a moderately low speed
network that was purposely made for sales automation and, fleet monitoring and tracking, email
and online transactions. It was later absorbed by an American network. User data was picked up
from ARDIS customer based and integrated into later technologies [2].
The most recent technological advancements have led to the re -emergence and wide growth of
LPAN technologies. This has been partly fueled by the increasing demand for internet services
around the around the world. People and businesses are starting to look for low-cost and low –
data devices. They have proven to be vital in many applications such as environmental sensors
that are used to monitor the environment and keep track of such items such as pollution. It has
also been applies in oil and gas monitoring.

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SIGFOX built the first model LPWA network in 2009. The company sets up antennas on towers
like the cell companies. These networks receive data transmission from things such as parking
sensors and water sensors. It uses frequencies that are unlicensed. The company started with an
initial outlay of £100 million. It created a lot of interested and boosted excitements about the
industry in Europe. It was during this period when radio technology was becoming less
expensive and also the tools for integrating the applications was becoming cheaper which
permitted many people to use. It became easier to construct and integrate from remote devices
into applications. The advent of online integration also fueled the advancement of LPWAN in
that they offer real time monitoring insights.
LORA is another example of IoT network. It is based in Annapolis, Maryland in the US. It is
built by Link labs and is among the leading innovators in LPWA network technologies that
power IoT. Lora Alliance is a non profit organization that aims to standardize low power wide
area network. It was founded by a group of veteran engineers from Johns Hopkinson University.
LORA provides secure connectivity for a lot of IoT devices and uses Spread Spectrum
Modulation that was developed and patented in 2013 [3].
The emergence of demand side management of energy systems has also fueled the advancement
of LPWAN. With the immense pressure from the environmentalists, there is an immense
pressure to for the integration of renewable energy into interconnected energy systems. Most
current networks do no meet the requirement for demand side management of Energy system.
Apart from LORA and SIGFOX there are several other LPWAN technologies include:
 GreenOFDM from Green Waves Technologies
 Symphony link from link labs
 ThinkPark Wireless from Actility
 DASH 7 from Haystack

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4G based cellular wireless networks
IoT (Internet of Things) network protocols include:
i. Narrowband IoT cellular network
ii. LTE-M cellular network protocol and;
iii. LTE- CAT M1
The following discussions present the features, similarities and differences between the three
network protocols.
To begin with NB-IoT cellular networks refers to low-power wide area network (LPWAN) that
utilize radio technology standard built by 3GPP that makes it possible to access a wide range of
cellular devices and services. The details of the protocol are stipulated in the 3GPP Release 13.
It is mainly focused on indoor coverage. They are low- cost and have high connectivity density
compounded by long battery life [4]. They have improved power consumption with battery life
of up to ten years on just a single charge. The ever growing need of coverage in rural, deep
indoor and ultra low devises complexity has led to the development on new physical layer
signals. They are supported by major mobile operators and chipsets. The network uses a subset
of LTE standard but with limited bandwidth of 200 kHz. The protocol uses OFDM (Orthogonal
Frequency Division Multiplexing) formulation. This is a term that is used in telecommunication
which provides a means of encoding data on multiple carrier frequencies. As for Uplink
communication SCF-DMA formulation is used. NB-IoT has become a popular scheme in wide
digital communications it is used in applications such as digital televisions, audio broadcasting,
4G mobile communication and DSL (Digital Subscriber Line) internet access that is used to
transmit data over telephone lines.
Secondly, LTE-M (Long Term Evolution Mobility) is a radio technology standard developed and
rolled out by 3GPP. It enables the connection of wide range of cellular devices mainly from (M-
2-M) machine to machine and IoT (internet of things applications). It has upload speeds of up to
50 mbps this network protocol has lower latency time and allows for smooth retrieval of IOT
application. This cellular network protocol relies on the real time information.
LTE- CAT M1 is an air interface that enables the connection of IOT and M2M devices with
medium data rate requirements of 375 kbps. The protocols support voice functionality which
enables the use of devices in such environments that require some levels of human interaction.
They are efficient in that they consume less power. Battery life can last for a period of up to ten
years on single charge. They are mainly suitable for use in full mobility and in vehicle handover.
They also have got he feature of extended in building range which enables the use of idle
bandwidth which would not have otherwise been used.

Low
battery
Life
Massive
IoT
Devices
LPWAN
Low Cost
Easy
DeploymentExtend
ed
covera
ge
4
The three IoT cellular network protocols are complementary to each other even though they
address similar issues regarding IoT which are mainly based on their strengths. Both the NB-
based IOT network protocol support ultra low complexity devices with very narrow bandwidth
of up to 200 kHz and whose data rates are around 250 kbps. Both can also be deployed in guard
band of ITB carrier to use the spectrum that would not have otherwise been used. Both can sleep
for extended periods of time with continuous reception (eDRX) and in power saving mode which
serves to reduce the device power consumption.
The divergence between the two is that LTE-CAT M1 operates at a bandwidth of 1.4 MHz with
higher cost and devises complexity than NB-IOT which allows them to have greater data rates of
up to 1mbps, lower latency and more accurate device. The difference’s between the two is also
found in the positioning capabilities. For instance LTE-CAT M1 supports voice calls and
connected mode capability. NB-IoT is ideal for supporting very low data applications.in
extremely challenging conditions. NB-IoT M1 is very suitable for use in utility meters and
sensors. Whereas, LTE-CAT M1 is good for use in vehicles, wearable devices, trackers and
alarm bands because of the fact that they are modified to operate like cell phones.
Figure 1: LPWA Cellular IoT

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New trend: 5G
5G network as an emerging trend provides enhancement for fixed wireless access. High speed
connectivity, increased bandwidth and low- power wide area application. This system transforms
data units using new radio NR interface, use of MM wave spectrum, and other several
advancements. It utilizes MM Security Issues in the Next Wave operating frequencies at 20 GHz
– 300 GHz. This frequency is far much better than the frequencies for 4G. More data is
transferred exponentially at faster speeds, low latency and reduced congestion. Various telecoms
have proposed that 5G is the future of mobile network. 4G supports about 4000 communication
devices per square kilometer of geographical coverage while 5G will support devices up to
1000000. Since the future of IoT sees increased number devices, 5G is able to accommodate
them ensuring a reliable and secure data transmission. 5G implements Massive Multiple input-
Massive multiple output mechanism that offers easy monitoring of devices around a cell site
thereby improving network coverage, transmission speed and capacity.
4G based cellular IoT suffer the problem of congestion. With 5G congestion problem will be
eliminated. 5G will provide the following solutions:
i. Fixed wireless access
5G is primarily concerned with the deployment of fixed wireless access. This wireless access
delivers high cellular connectivity allowing consumers and businesses will be able to get a fast
and reliable wireless broadband service.
ii. Extension of enhanced Mobile Broad Band eMBB. With this development, the rate of
data transfer will increase covering a wide geographical area.
iii. 5G Low Power Wide Area LPWA and massive IoT. 5G will be used to extend
existing LPWA IoT applications. This will see more and more IoT devices developed
for smart cities, underground sensors, aircraft simulation and fleet monitoring among
other areas of IoT applications.
iv. Massive Machine Type Communication IoT using low power wide area technologies
designed for IoT applications. It also supports minimal battery power usage and
supporting large number of connected users
v. Network slicing to tailor connectivity speeds, coverage, security and encryption. A
dedicated network is offered for supporting IoT operations. Quality of Service is
guaranteed and cloud computing capabilities are enhanced through 5G. Since many
devices are expected to be deployed in the near future, servers large enough to
accommodate transmitted, processed and stored data will be essential. Cloud servers
will be utilized in 5G more.
To transition from 4G to 5G requires users to update their software only. This makes integration
an easy task making the field of cellular IoT achieve low power wide area objective while
keeping costs as low as possible.

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IoT receiver requirements
Received signal strength-
Received signal strength refers to the amount of signal received at the antenna. Signal
strength can be measured at the antennae for each packet received. This can be quantified to
form a signal indicator. The strength can tell how far an antenna is from an IoT device. It a
requirement that IoT receiver signal has to be stronger for it to accommodate faster and
larger transmissions of data to the antennae. Weak receiver signals means that data
transmission is slow. Since the ultimate goal is cellular IoT if a low power wide coverage
application, it is therefore imperative that the signal strength accommodate this requirement.
Frequency reuse factor-
This is a concept used in cellular networks to achieve efficiency of the cellular spectrum
system. A cellular network utilizes frequency reuse in geography domains. For instance
when the same network channel is to be reused between to cells or base stations, the
frequency reuse distance has to be minimal. Spectrum efficiency is therefore expressed as a
ratio of frequency reuse distance to cell radius. In cellular IOT it is important to design
cellular systems as a high capacity and as a high capacity and spectrum efficient system.
When frequency is reused in cellular networks, the capacity and the coverage of the network
is increased. This is applicable where cells are located further apart and both equipment
communicating do not transmit at high power. It is important to note that frequency reuse is
determined reuse distance d and the reuse factor R
D=R √ 3 N Where; N is the number of cells.
Frequency reuse factor refers to the number of times that a given frequency can be reused
since bandwidth is dependent on the number of cells and frequency reuse factor it
determines how cellular IoT device operates. Three channels are needed for cellular IOT
equipment to enhance a working frequency reuse.
Transmit power requirement.
Cellular IoT can be employed in an array of fields ranging from smart cities to underground
sensor monitoring these devices are used to control real life events. There is a need to design
low power IoT devices to operate for extended periods of time without running out of
battery. Low-power wide area networks allow such devices to successfully communicate
over wide geographical coverage with reduced costs in terms of power. It is a necessity that
battery life is preserved especially with the number of cellular IoT devices expected to rise in
the near future. Embedded designers have focused attention to power usage. They emphasize
on the design of microcontrollers and sensor systems to operate at low power. Computational

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requirements dictate whether to choose a 32 bit or 8 bit micro controller although this does
not mean that energy requirements have been disregarded. In a sensor data sent over wireless
link is small. Although microcontroller and sensor design greatly determine the power
requirement, it is important that the IoT system is designed to power at minimal energy
supply.

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Issues related to cellular IoT
Although cellular IoT is seen is see to provide low power coverage, it suffers a number of
challenges which include:
1. Attack on the air interface- in cellular network air interface refers to the radio
connection between an IoT device and a based station. A number of attacks exists that
attempt to compromise the integrity of the air interface. These threats can either be
active or passive with active air interface attacks a hacker eavesdrops on the
communication between IoT devices and attempts to modify the data. Gaining access
to the channel means a compromise to the operation of the IoT system. However
various solution strategies have been employed to counter this type of attacks. For
instance, data being sent to IoT devices is encrypted [5]. On the other hand, passive
attackers eavesdrop on the communication but do nothing. Although this does not
lead to the compromise on the operation of the IoT device it leads to traffic jam and a
problem of device tracking. Attacks in cellular IoT system means a compromise on
the system integrity. Since passive attacks cause traffic, it may cause delays in the
transfer of vital information.
2. Distributed denial of service. Since there is a growing number of IoT devices an
attack directed on that set of IoT device may lead to a total breakdown of entire IoT
system [6]
It is true to say that the world of IoT faces a challenge of security issues. Every vendor in the
market competes to make releases of new IoT solution. The key security issues become a
bottleneck since the vendors are only concerned on functionality rather than on security.

Infrastructure Citizen
services
Business
services
City Service
Smart city IoT system
9
Using CellPlaner to simulate air interface
A simulation of the air interface was done for smart city cellular IoT using CellPlaner. This
software offers two simulation environments for designing, visualizing debugging and validation
of distributed algorithms that are used in monitoring and data collection of environmental
variables. It helps in visual explanation of concepts of IoT sensor networks as well enabling tests
of wireless protocols.
In the first simulation environment, a design of mobility scenario was performed. Smart city is
an area using different types of IoT devices to collect data used for managing resources. It serves
to integrate a number of key city services including transportation, public safety, environment,
citizen services, and urban city planning and business services. Smart devices and IoT sensors
are embedded in the city environment from which they collect data that will be shared through
smart transmission systems and the collected data is analyzed to provide important information
regarding the city. By making use of CellPlaner software, the smart city platform will enable
creation of sustainable city that responds directly to an array of needs.
Figure 2: Smart City
Depending on the information from the CellPlaner software, a number of features can be used to
establish the degree of smartness of the city. These features include:
i. Technology based communication infrastructure

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ii. High functioning public system of transport
iii. A working sense of city planning
iv. Environmental initiatives
To achieve all those mentioned above, smart city uses a network of interconnected IoT devices
and cellular network technologies e.g. 4G NB-IoT.
Using RF CellPlanner, Smart city was simulated as follows;
i. Set Smart parking- this provides smart city users with real time information on car
parking spots in the city. IoT device sensors collect information on GPS location of
the parking spot, availability of space for parking and the environmental conditions
e.g. temperature and humidity in that parking spot.
ii. Set Smart street lights – smart street lights help to conserve energy use in a smart city.
Most street lights in most city streets consume a lot of power. Smart Street light
solves this problem by switching its status depending on the light conditions of the
surrounding. Smart City Street light will give information on the GPS location of the
smart street light, the ambient light status, lamp status and power consumption.
iii. Set Smart city traffic signal- in a busy city environment, no one likes to waste time
waiting at the traffic signal to begin moving. Smart city traffic signal provides useful
information regarding city condition apart from sending environmental conditions
including noise levels at traffic signals. Obtaining information from smart city traffic
signal helps in determining health status of the city. This helps in strategic planning
and decision making for those involved. It gives information on GPS location of the
smart traffic signal, traffic signal status, level of traffic, noise level and energy
consumption.
iv. Create Smart city garbage can- this smart city item helps in automating waste
management thus keeping the smart city clean. Smart city garbage can gives the PS
location of the garbage can and the level of garbage in the can.
v. Create Smart city transportation – many citizens use public transport. Transportation
in the city is an essential aspect. It sends the information regarding bus number, seats
available in the bus, estimated arrival time to next stop along the highway, fuel
consumption and GPS location of the transport. Smart transportation in the city
enables the citizens to make data driven decisions based on the information collected
by the IoT devices. This makes city transport very efficient.

11
Figure 3: CellPlaner Simulator
Set the cellular network to use. LTE/4G has been used in this simulation. Then, set all other
variables as shown in the figure above.

12
Figure 4: Smart city Position
Set Smart city Variables as shown below;
Figure 5: Simulate Smart City

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Figure 6: Simulation
It first begins with collection of data using smart sensors in real time. Secondly, data analysis for
the data is done through a careful assessment in order to offer meaningful insights. Then, the
insights drawn from the analysis of data is communicated to decision makers via reliable and
faster communication channels- cellular networks. Lastly, action strategy is developed. The
meaningful insights arrived at in analysis process is used as a basis for creating optimal solution
for efficient and effective operations of the city that ultimately raise the living standards of the
people.

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