Hindawi
Modelling and Simulation in Engineering
Volume 2021, Article ID 9806333, 10 pages
https://doi.org/10.1155/2021/9806333
Research Article
A Classical LTE Cellular System Simulator for Computer
Network Education
Julius Yaw Ludu , Justice Kwame Appati , Ebenezer Owusu ,
and Prince Boakye-Sekyerehene
Department of Computer Science, University of Ghana, Legon, Accra, Ghana
Correspondence should be addressed to Justice Kwame Appati; jkappati@ug.edu.gh
Received 14 September 2021; Accepted 2 November 2021; Published 15 November 2021
Academic Editor: Noé López Perrusquia
Copyright © 2021 Julius Yaw Ludu et al. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
The proposal of LTE in the standardization of cellular network systems has received considerable attention in the research domain,
and most subscribers widely use it. Despite the enormous acceptance of the system, academia as an industry is usually
disadvantaged in training students due to the cost implication in setting up a prototype. In bridging this gap, simulators are
traditionally developed as a testbed to aid students appreciate how these systems work. Although there are several simulators
available on the market, these simulators are quite expensive to acquire while others come with license restrictions. In this study,
a classical LTE cellular system simulator is proposed as a testbed to aid the education of computer networks at college. The
proposed simulator is an extension of the functionality of LTE-Sim frameworks. Usability testing of the proposed study reveals
that the system is much easier to simulate the various scenarios in wireless communication.
1. Introduction colleges now use computer network simulator (CNS) soft-
ware. This helps simulate numerous types of network equip-
Education is essential and serves as the foundation for the ment and carries out a wider range of experiments. Students
growth of every human being. Its effects are obvious not only leverage on these CNS to conduct their experiment, much
in childhood, but also in maturity. Every educational institu- like they would be in a real lab [3].
tion’s priority is hinged on providing appropriate motivation In a few decades, the world at large has experienced a
and high-quality standards. Educational resources are one of steeper increase in how data is used in a cellular ecosystem
the methods that may be utilized to supplement the educa- [4–6]. As the drive for a more enhanced technology evolves
tional process. Students can be motivated to learn if they in this space, the demand for a higher data rate, high con-
have access to appropriate materials [1]. As computer sci- nectivity speed, power efficiency, and low cost in application
ence and technology advances, several computing courses use also increases [7]. More cellular technologies are being
and curriculums have been developed and made available developed in response to the varying need of users in the
on the internet. The majority of them are very self-sufficient, telecommunication industry. Among these technologies,
which creates issues such as a new learner’s inability to the long-term evolution (LTE) developed by the 3rd Genera-
quickly access suitable curriculums and courses without fur- tional Partnership Project (3GPP) is proposed to cater for
ther help [2]. Furthermore, many colleges do not have the the evergrowing demand in the use of data [8, 9]. Histori-
funds to create state-of-the-art labs and keep same up to date cally, digital communication was birth in the ‘90s as an off-
on a regular basis. Owing to the limits of real-world equip- shoot of the fixed wired telephony industry. This was in
ments, it has become difficult to carry out all types of exper- the form of 2G GSM, which was primarily for voice service
imentation in the real lab. To tackle these issues, several with data service ranked low on the priority queue [10].
2 Modelling and Simulation in Engineering
Today
Mobile broadband services
1986 1992 2004 2012 ~2020 ~2030 Smart-&
Intelligent networks Green-World
1G 2G 3G 4G 5G 6G and
beyond
• Advanced mobile • Global system for •Wideband-code • Long-term • 5G NR
phone service mobile (GSM) division multiple evolution (LTE)
• •LTE-advanced IMT-2020(AMPS) • Digital-AMPS access (W-CDMA)
• Total access • IS-95 •High speed packet Today
communication access (HSPA)
system (TACS) •CDMA2000
Testbeds Prototypes Trials Commercialization
Foundation of land mobile
radio communications 3GPP: Release 14 Release 15 Release 16
Massive machine type Enhanced mobile
communication ITU broadband
~200,000/km2 ~20 Gbps
Ultra-reliabel low-
latency communication
~1 ms
Figure 1: Trends in cellular network systems [13].
Other services like SMS for text messaging and packetized tle to no user guide, which complicates its use as an intro-
data through GPRS and HSPA were made possible in later ductory course at the tertiary level [20, 21].
years [11, 12]. Figure 1 shows the trend of how cellular net- In this study, we proposed an LTE simulator with the
works have fed over the years. functional ability to perform standard network scenarios
With the introduction of LTE, an entirely new air inter- and further extend the capability of the LTE-Sim framework.
face on an all-IP technology based on Orthogonal Frequency To resolve the issue of usability, the proposed system is pre-
Division Multiplexing (OFDM) was implemented, setting sented in the form of a GUI, which allows users to enter only
the basis for a 4G capable mobile communication technol- the required parameters of a given network scenario
ogy [14] which is known to be more spectrally efficient. selected. For ease of result interpretation in teaching and
Thus, it can deliver more bits per Hertz, providing an econ- learning, the output of each scenario formulated is in the
omy of scale and spectrum reuse [15]. Some other benefits form of a graph. Comparatively, a quick survey demon-
derived from LTE is the smooth integration and handover strates that the proposed system will serve the intended pur-
to and from existing 3GPP networks. It also supports full pose in a classroom setup as opposed to other proposed
mobility and global roaming and ensures that operators systems. Subsequent sections of this study are structured as
can deploy while bringing subscribers to a true mobile follow: Section 2 talks about the materials and methods used
broadband (~5–10Mb/s/~15ms latency), enabling a quality for this study. It gives an overview of the proposed platform
video experience and media mobility [16]. With improved and the system requirement. In the same section, we discuss
capacity, speed, and latency, LTE made accessing applica- the user interface requirement and the various parts of the
tions faster and enabled a wealth of new applications previ- system. In the third section, we have the system testing
ously available only on a wired Internet connection. This has and discussion where a test scenario is demonstrated to ver-
necessitated the need to appreciate this technology in both a ify the proposed system functions. Finally, we end with a
wet and dry lab. Over the years, the simulation method has conclusion.
been adopted as the standard mechanism for analyzing
and evaluating the performance of an emerging protocol or 2. Materials and Methods
model [17]. For the purpose of usability and network educa-
tion, these models and protocols are implemented through 2.1. System Overview. In this study, five (5) major compo-
graphical user interfaces (GUI). Currently, there are very nents are required to build the proposed system. These com-
few simulation environments that have been developed for ponents are the main simulation platform, the LTE-Sim file,
use in computer science (CS) education in the area or net- graphs for simulation results, the parameter dialog, and tools
works to mimic the performance of LTE systems [3, 18, containing some defined libraries. Figure 2 gives a schematic
19]. Unfortunately, the few that exists comes with a com- representation of the context diagram of the proposed sys-
mercial license, making it unsuitable for training in an aca- tem. From Figure 2, the main simulation platform is created
demic environment. Other simulation environments are when the system is executed. The main simulation platform
made publicly available through the open-source movement, houses the various simulation scenarios and most of the
but this also comes in a more sophisticated package with lit- standard LTE dedicated simulations. Among the standard
Modelling and Simulation in Engineering 3
Legend
1 3 1: Create scenario workspace
Sub-working space 2: Create scenario parameters
Scenarios Scenarios 3: Create testing workspace
modules modules
4: Set module parameters
Simulation
2 parameter 4 5: Create parameter dialog
functions 6: Pass simulation parameters
7: Generate results
13 5 8: Create folder
9: Pass files to library
Simulation results 7
(graphs) LTE-sim
6 Parameter dialog 10: Execute files using libraries
11: Copy files to MATLAB
8
12: Return simulation graphs
Output folder 9 13: Show simulation results
12
MATLAB tools 11 Trace folder 10 Tools (libraries)
Figure 2: Context diagram of the proposed system.
scenarios are single cell, single cell with interference, single From Section 2.1, each component is considered a build or
cell with streets, a single cell with Femto, and multicell. block, and each is tested and implemented. The first build
The system also has the ability to test for AMC mapping, takes care of the main simulation area, and the second build
SINR urban, mobility models, throughput urban, scalability considers the various parameter dialogs for various scenarios
test macro with Femto, throughput with building, through- and testing modules. Build three is for the compilation of
put macro with Femto, and multicell SINR plot. various functions used in the LTE-Sim.
Executing a scenario or a dedicated test in the main sim- Build four is the creation of tools as libraries to convert
ulation platform first creates a subworkspace followed by trace files into an appropriate structure for use in MATLAB.
parameter initialization relating to the specific scenario to Finally, build five is for the display of outputs in the form of
be performed. These parameters are editable using the graphs. Figure 3 gives a schematic view of the IDM as
parameter dialog with their outputs sent to the LTE-Sim applied in this study.
module. The LTE-Sim module performs computation using
the predefined functions and returns the required output as 2.3. User Interface Requirement. This section explains, in
graphs for further analysis and interpretation. On the other brief, the interface requirement of the proposed system as
hand, dedicated simulation is executed through the LTE- follows:
Sim module resulting in files stored in an output folder.
Appropriate libraries use up these files to produce MATLAB (1) Users of the system should be presented with the
codes stored in the trace folder. These codes are executed to main simulation page. The page should contain the
generate graphs that are displayed to users through the main menu defined as File, Scenarios, Test, About,
subworkspace. and Exit. The scenario menus should fire up the
standard simulation scenarios for both single and
multicells
2.2. System Specification and Functional Requirement. In this
study, the Iterative Model Design (IMD) was leveraged to (2) The test menu should present the dedicated test
build the proposed architecture. This design paradigm was modules such as mobility model, test with Femto,
found appropriate for this study as it starts with a simple scalability test, and test with buildings or streets
implementation of small components and iteratively (3) The user should decide on either simulating a sce-
improves the evolving versions until the system is complete nario or performing a test module
and ready for deployment. At each iteration, there is an extra
degree of freedom that permits the modification of the Figures 4 and 5 show the sample screens of the main
design and the creation of new functional capabilities [22]. simulation platform and the deducted test module.
Main LTE simulation platform
4 Modelling and Simulation in Engineering
Build 1 Design &
development Testing Implementation
Build 2 Design & Testing Implementation
development
Build 3
Requirement Design & Implementation
development Testing
Build 4 Design &
development Testing Implementation
Build 5 Design &
development Testing Implementation
Figure 3: Iterative model design of the proposed system [23].
File Scenarios Test About Exit
Figure 4: Main simulation platform.
File Scenarios Test About Exit File Scenarios Test About Exit
Simple scenario Test AMC mapping
Single cell without interferance Test mobility model
Single cell with interferance Scalability test macro with femto
Multi cell scenario Test SINR (urban)
Single cell with femto Test throughput (urban)
Single cell with street Test throughput macro with femto
Test throughput building
Test SINR (femto)
Test Multicell SINR plot
Figure 5: A scenario menu and a testing menu.
Modelling and Simulation in Engineering 5
File Scenarios Test About Exit
Single cell without interference scenario −
Set simulation parameters
Single
Location: (605, 4722)
Figure 6: A workspace for single cell without interference.
2.4. Simulation Subworkspace. Figure 6 presents a view of the interference with a fixed eNodeB at the center of the cell is
simulation subworkspace. In this workspace, the user is pro- defined given that the users are moving at a speed of 3 kmph,
vided with an environment where they can either perform a and the mobility of each user equipment (UE) traveling cell
scenario or run a test. A similar workspace is presented to is described with a random direction model. Assume that the
users for all other scenarios or test modules depending on users are moving in a bounded region equal to 1 km, the
the activity selected. The workspace also interfaces with the number of connections to an eNodeB at a particular time
parameter dialog to capture all required parameters for a varies from 10 to 100 UEs, and each UE receives one video
given test or scenario. flow, one VOIP flow, one constant bit rate, and one best
effort flow at the same time. With the given assumptions,
2.5. Simulation Parameter Settings. This interface of the pro- the performance result of the three different standard
posed system helps users define parameters for their test or schemes is explored and evaluated in this section. The simu-
scenario. The interface comes with two tabs, the initial lation of this scenario took 120 sec, and the comparison is
parameter setup and other simulation parameters. The ini- divided into subgraphs based on the performance indices
tial setup compartment presents default values to the user such as packet loss ratio (PLR). Figure 9 shows the through-
and allows them to alter them to their needs. Figure 7 is a put of the system over an increasing number of users. From
demonstration of how the dialog functions. the graph, it is observed that the system’s throughput with
The other parameter tab considers parameters such as respect to video trace degrades as the number of users
the number of users’ equipment, radius, video, number of increases. M-LWDF demonstrated a higher performance
VOIP, and best effort flows. In building this dialog, three using the throughput metric over EXP/PF and PF schemes
schedulers were adopted, thus Modified Largest Weighted from the scenario.
Delay First (M-LWDF), Exponential Proportional Fair Theoretically, MLWDF is known to prioritize real-time
(EXP), and Proportional Fair (PF). On executing these flows with the highest delay for their head of line packets
parameters, the user is present with seventeen (17) different and the best channel condition; hence, the better QoS
graphs from four (4) different applications, thus VOIP, con- requirements noted. It also supports multiple data users,
stant bit rate (CBR), video, and infinite buffer. These graphs which also results in a better performance in the throughput
also encompass some performance indexes such as system over EXP/PF and PF.
throughput, average delay, packet loss ratio (PLR), spectral Figure 10 also shows the ratio of packet loss under the
efficiency, and fairness. Figure 8 gives a sample presentation same schemes. From the graph, a significant difference is
of the spectral efficiency. observed between these three schemes. The PF scheme
recorded the highest PLR with increasing users, followed by
3. System Testing and Discussion EXP/PF and M-LWDF. In video streaming applications, it is
recommended that the packet loss ration threshold be kept
This section of the study explains the proposed system’s below 0.01, which in effect makes M-LWDF more desirable.
validity and assesses the proposed system’s potency and its In Figure 11, we have a plot of packet delay and the
usefulness to be used in college as an academic tool for com- number of users to evaluate the performance of the three
puter networks. To start with, a single cell scenario without schemes. From the graph, we observed that the EXP/PF
6 Modelling and Simulation in Engineering
File Scenarios Test About Exit
Single cell without interference scenario −
Set simulation parameters
Single
Simulation parameters setup
Intial setup Other parameters
Number of simulation: 10
Number of minimum users: 1
Interval between users: 1
Number of maximum users: 1
User speed: 3
RUN SIMULATION CLOSE SIMULATION
Location: (192, 5000)
Figure 7: Initial simulation setup parameters.
File Scenarios Test About Exit
LTE simulation graphs-single cell without interference
INF_BUF_PLR VIDEO_PLR VOIP_PLR INF_BUF_Throughput VIDEO_Throughput VOIP_Throughput INF_BUF_Delay VIDEO_Delay VOIP_Delay
Sepcetral efficiency INF_BUF_Fairness Index VIDEO_FI Fairness Index VOIP_FI Fairness Index CBR_PLR CBR_Throughput CBR_Delay CBR_Fairness Index
Cell-spectral-efficiency
0.2
+ +
0.18 + + +
+
0.16 +
+
0.14
+
0.12
0.1
0.08
0.06
1 2 3 4 5 6 7 8 9 10 11 12 13
Users
+ PF
MLWDF
EXP/PF
Figure 8: Spectral efficiency vs. number of users.
performs slightly better than M-LWDF and PF. This obser- M-LWDF scheme has a better spectral efficiency perfor-
vation is usually attributed to the use of exponential function mance than EXP/PF and PF schemes.
in the EXP/PF scheduler to delay targets in real-time traffics Finally, we have Figure 13, which demonstrates the per-
compared to the M-LWDF scheduler. formance schedulers in assessing the fairness index of the
Observation in cell spectral efficiency is not different scenario. From the graph, again, M-LWDF emerged better
from that of the throughput since this was only run for video compared to EXP-PF and PF. Once again, this observation
applications, as shown in Figure 12. The plot shows that the is attributed to the fact that the PF component responsible
Spectral-efficiency (bpsS)
Modelling and Simulation in Engineering 7
File Scenarios Test About Exit
LTE simulation graphs-single cell without interference
VOIP_Delay Sepcetral efficiency INF_BUF_Fairness Index VIDEO_FI Fairness Index VOIP_FI Fairness Index CBR_PLR CBR_Throughput CBR_Delay CBR_Fairness Index
INF_BUF_PLR VIDEO_PLR VOIP_PLR INF_BUF_Throughput VIDEO_Throughput VOIP_Throughput INF_BUF_Delay VIDEO_Delay
VIDEO_Throughput
2e+06
1.8e+06
1.6e+06
+
1.4e+06
1.2e+06
+
+
1e+06
+
+
+
800000
600000
400000
10 20 30 40 50 60 70 80 90 100
Users
+ PF
MLWDF
EXP/PF
Figure 9: System throughput vs. number of users.
File Scenarios Test About Exit
LTE simulation graphs-single cell without interference
VOIP_Delay Sepcetral efficiency INF_BUF_Fairness Index VIDEO_FI Fairness Index VOIP_FI Fairness Index CBR_PLR CBR_Throughput CBR_Delay CBR_Fairness Index
INF_BUF_PLR VIDEO_PLR VOIP_PLR INF_BUF_Throughput VIDEO_Throughput VOIP_Throughput INF_BUF_Delay VIDEO_Delay
VIDEO-packet-Loss-Ratio
0.8
+
+
0.7 +
+
0.6
+
0.5
+
0.4
0.3
0.2
0.1
+
0 + +
10 20 30 40 50 60 70 80 90 100
Users
+ PF
MLWDF
EXP/PF
Figure 10: System packet loss vs. number of users.
PLR Throughput (bps)
8 Modelling and Simulation in Engineering
File Scenarios Test About Exit
LTE simulation graphs-single cell without interference
VOIP_Delay Sepcetral efficiency INF_BUF_Fairness Index VIDEO_FI Fairness Index VOIP_FI Fairness Index CBR_PLR CBR_Throughput CBR_Delay CBR_Fairness Index
INF_BUF_PLR VIDEO_PLR VOIP_PLR INF_BUF_Throughput VIDEO_Throughput VOIP_Throughput INF_BUF_Delay VIDEO_Delay
VIDEO-Delay
0.6
+
0.5
+
0.4
+
0.3 +
0.2
+
0.1
+
0
10 20 30 40 50 60 70 80 90 100
Users
+ PF
MLWDF
EXP/PF
Figure 11: System packet delay vs. number of users.
File Scenarios Test About Exit
LTE simulation graphs-single cell without interference
INF_BUF_PLR VIDEO_PLR VOIP_PLR INF_BUF_Throughput VIDEO_Throughput VOIP_Throughput INF_BUF_Delay VIDEO_Delay
VOIP_Delay Sepcetral efficiency INF_BUF_Fairness Index VIDEO_FI Fairness Index VOIP_FI Fairness Index CBR_PLR CBR_Throughput CBR_Delay CBR_Fairness Index
Cell-spectral-efficiency
0.16
0.14
+
0.12
0.1
+
+
0.08
+ + + +
0.06
0.04
0.02
10 20 30 40 50 60 70 80 90 100
Users
+ PF
MLWDF
EXP/PF
Figure 12: Spectral cell efficiency vs. number of users.
for fairness in the M-LWDF scheduler is more dominant ensures more adherence to delay bound. In general, as the
compared to the QoS component. This unfortunately is number of users increases, it is expected that the fairness
not the case for EXP-PF since the QoS component only index performance will also drop.
Delay (Sec)
Spectral-efficiency (bpsS)
Modelling and Simulation in Engineering 9
File Scenarios Test About Exit
LTE simulation graphs-single cell without interference
INF_BUF_PLR VIDEO_PLR VOIP_PLR INF_BUF_Throughput VIDEO_Throughput VOIP_Throughput INF_BUF_Delay VIDEO_Delay
VOIP_Delay Sepcetral efficiency INF_BUF_Fairness Index VIDEO_FI Fairness Index VOIP_FI Fairness Index CBR_PLR CBR_Throughput CBR_Delay CBR_Fairness Index
VIDEO-Fairness-Index
1 +
0.9
0.8
0.7
+
0.6
+
0.5
+
0.4 +
+
0.3 +
0.2
10 20 30 40 50 60 70 80 90 100
Users
+ PF
MLWDF
EXP/PF
Figure 13: System fairness index vs. number of users.
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