5G Network Simulator

There are several 5G network simulators useful for various processes such as designing, modeling, simulating, etc. phdservices.org is a prominent organization specializing in providing top-notch 5G Network Simulator concepts and solutions, delivering exceptional simulation outcomes. With a proven track record of earning the trust of over 6000 customers, you can confidently entrust us with your information. We are committed to providing full support every step of the way. Including major characteristics and relevant parameters, we provide a collection of most prominent 5G network simulators to consider: 

  1. MATLAB with 5G Toolbox

Explanation: In order to structure, model, simulate, and assess 5G systems, the 5G Toolbox of the MATLAB offers reference instances and standard-based functions.

Major characteristics:

  • It enables 3GPP 5G NR principle.
  • Creation and analysis of waveform.
  • MIMO and Beamforming
  • Modeling and simulation of physical layer
  • Link-level simulation
  • Channel modeling.

Relevant Parameters:

  • Bandwidth
  • Resource allocation
  • Carrier frequency
  • Modulation schemes
  • QoS metrics
  • Channel models (for instance: CDL, TDL)
  • Number of antennas
  1. ns-3 (Network Simulator 3)

Explanation: In research and educational platforms, NS-3 is employed in an extensive manner. It is referred to as a discrete-event network simulator. To simulate different network protocols, it offers efficient modules in addition to 5G. 

Major characteristics:

  • For custom platforms, it offers a flexible framework.
  • Enables combination with actual-time applications.
  • Provides assistance for beamforming and MIMO.
  • Practical mobility models.
  • Extensive 5G-LTE-EPC module.

Relevant Parameters:

  • Transmission power
  • Carrier frequency
  • Network topologies
  • Mobility models
  • QoS parameters
  • Bandwidth
  • Scheduler types
  1. OMNeT++

Explanation: OMNeT++ is generally utilized to construct network simulators. It is considered as a modular, adaptable, component-related C++ simulation framework and library. For LTE and 5G NR simulation, Simu5G is an ideal OMNeT++ library.

Major characteristics:

  • Offers assistance for different QoS classes.
  • Supports combination with other simulators such as SimuLTE and INET.
  • In-depth 5G NR model.
  • Full stack simulation.
  • Multi-RAT and multi-connectivity platform.

Relevant Parameters:

  • Number of antennas
  • Mobility models
  • Carrier frequency
  • QoS parameters
  • Traffic models
  • Bandwidth
  • Channel models
  1. GNS3 (Graphical Network Simulator)

Explanation: To simulate complicated networks, GNS3 enables the integration of actual and virtual devices. It is specifically a network software emulator. For network arrangement and testing, it is majorly employed.

Major characteristics:

  • Enables combination with actual hardware.
  • Intricate network topologies.
  • Provides assistance for different network protocols.
  • Simulation of actual and virtual devices.

Relevant Parameters:

  • Protocol settings
  • Network topologies
  • QoS settings
  • Device configurations
  • Traffic generation
  1. QualNet

Explanation: QualNet is particularly examined as a network modeling software. By means of emulation, analytical modeling, and simulation, it forecasts the activity of the networks.

Major characteristics:

  • It is more flexible to extensive networks.
  • Large-scale protocol libraries.
  • High-fidelity network simulation.
  • Enables 5G NR and LTE.
  • Actual-time network emulation.

Relevant Parameters:

  • Traffic patterns
  • Bandwidth
  • Network configurations
  • Number of antennas
  • Carrier frequency
  • QoS parameters
  • Mobility models
  1. SimuLTE

Explanation: SimuLTE is relevant to the OMNeT++ architecture, and is termed as a system-level simulator. For LTE and 5G networks, it is highly suitable. For the performance assessment of 5G/LTE networks, it is significantly modeled.

Major characteristics:

  • For different scheduling methods, it offers assistance.
  • Facilitates combination with other OMNeT++ modules.
  • In-depth Channel models.
  • Simulation of full protocol stack.
  • Provides assistance for 5G NR and LTE.

Relevant Parameters:

  • Carrier frequency
  • Mobility models
  • QoS parameters
  • Transmission power
  • Scheduling algorithms
  • Bandwidth
  1. SRS (Software Radio Systems)

Explanation: For the simulations of 4G and 5G network, the open-source software-defined radio solutions, such as srsRAN and srsLTE are offered by SRS.

Major characteristics:

  • Allows combination with SDR hardware.
  • Adaptable and customizable.
  • Assistance for full protocol stack.
  • Supports actual-time deployment.
  • Open-source 5G NR stack.

Relevant Parameters:

  • Bandwidth
  • QoS parameters
  • Modulation schemes
  • Carrier frequency
  • Scheduling algorithms
  1. 5G-LENA

Explanation: 5G-LENA is generally related to NS-3, and is referred to as an end-to-end publicly accessible 5G NR network simulator.  For simulating the performance of a 5G network, it is majorly modeled.

Major characteristics: 

  • Supports combination with ns-3 modules.
  • Practical channel models.
  • End-to-end simulation.
  • Wider protocol stack deployment.
  • Assistance to 5G NR characteristics.

Relevant Parameters:

  • Number of antennas
  • Scheduling algorithms
  • Carrier frequency
  • Mobility models
  • Bandwidth
  • QoS parameters
  • Channel models

How to simulate 5G network projects using simulators?

The simulation of 5G network projects with the support of simulators is examined as an interesting and important process. To simulate 5G network projects through the use of prominent simulators such as NS-3, OMNeT++ along with Simu5G, and MATLAB including 5G Toolbox, we suggest step-by-step instructions in an explicit manner: 

  1. Simulating 5G Networks with MATLAB 5G Toolbox

Procedural Instruction:

  1. Arrange MATLAB Platform: Initially, you should make sure that you have MATLAB installed on your system, along with a significant 5G Toolbox.
  2. Determine System Parameters: For the 5G network, configure the fundamental parameters.

% System parameters

carrierFrequency = 28e9; % 28 GHz

bandwidth = 100e6; % 100 MHz

numAntennas = 64; % Number of antennas in the array

numUsers = 10; % Number of users

  1. Develop Channel Model: Specifically for the simulation, outline the channel model.

% Create a 5G TDL-C channel model

channel = nrTDLChannel;

channel.NumTransmitAntennas = numAntennas;

channel.NumReceiveAntennas = 1;

channel.DelayProfile = ‘TDL-C’;

channel.DelaySpread = 100e-9; % 100 ns

channel.MaximumDopplerShift = 300; % 300 Hz


  1. Resource Allocation: Then, plan to allot resources to the appropriate users.

% Resource allocation (simple Round Robin)

numRBs = 100; % Number of resource blocks

allocation = zeros(numUsers, numRBs);

for rb = 1:numRBs

    userIdx = mod(rb, numUsers) + 1;

    allocation(userIdx, rb) = 1;


  1. Beamforming: In the direction of the users, navigate the antenna array by applying beamforming techniques.

% Beamforming using simple steering vector

angles = linspace(-60, 60, numUsers); % User angles in degrees

steeringVector = phased.SteeringVector(‘SensorArray’, phased.ULA(‘NumElements’, numAntennas));

weights = zeros(numAntennas, numUsers);

for k = 1:numUsers

    weights(:, k) = steeringVector(carrierFrequency, angles(k));


  1. Execute Simulation and Examine Performance: The performance metrics such as SINR has to be examined after the simulation execution.

% Example SINR calculation

rxSignal = complex(randn(1000, numUsers), randn(1000, numUsers)); % Dummy received signal

noisePower = 1e-3; % Noise power

sinr = zeros(1, numUsers);

for k = 1:numUsers

    signalPower = norm(rxSignal(:, k))^2;

    interferencePower = sum(norm(rxSignal(:, [1:k-1, k+1:end])).^2);

    sinr(k) = signalPower / (interferencePower + noisePower);


% Display SINR for each user


  1. Simulating 5G Networks with ns-3

Procedural Instruction:

  1. Configure ns-3 Platform: In the beginning, NS-3 and the relevant 5G modules (such as mmWave, LENA) have to be installed.
  2. Create Simulation Script: To specify the simulation platform and network parameters, a simulation script must be developed in Python or C++.

// Example C++ script for ns-3

#include “ns3/core-module.h”

#include “ns3/network-module.h”

#include “ns3/internet-module.h”

#include “ns3/point-to-point-module.h”

#include “ns3/applications-module.h”

#include “ns3/lte-module.h”

#include “ns3/mobility-module.h”

using namespace ns3;

int main(int argc, char *argv[])


    // Set up simulation parameters

    uint16_t numberOfNodes = 10;

    double simTime = 1.0; // seconds

    // Create nodes

    NodeContainer ueNodes;    ueNodes.Create(numberOfNodes);

    NodeContainer enbNodes;


    // Set up mobility model

    MobilityHelper mobility;    mobility.SetMobilityModel(“ns3::ConstantPositionMobilityModel”);    mobility.Install(enbNodes);    mobility.SetMobilityModel(“ns3::RandomWalk2dMobilityModel”, “Bounds”, RectangleValue(Rectangle(-500, 500, -500, 500)));


    // Install LTE Devices to the nodes

    NetDeviceContainer enbLteDevs;

    NetDeviceContainer ueLteDevs;

    LteHelper lteHelper;

    enbLteDevs = lteHelper.InstallEnbDevice(enbNodes);

    ueLteDevs = lteHelper.InstallUeDevice(ueNodes);

    // Attach UEs to the eNodeB

    lteHelper.Attach(ueLteDevs, enbLteDevs.Get(0));

    // Install the IP stack on the UEs

    InternetStackHelper internet;


    // Assign IP addresses to the UEs

    Ipv4InterfaceContainer ueIpIface;

    ueIpIface = epcHelper->AssignUeIpv4Address(NetDeviceContainer(ueLteDevs));

    // Attach the applications to the UEs

    uint16_t dlPort = 1234;

    ApplicationContainer clientApps;

    ApplicationContainer serverApps;

    UdpClientHelper dlClient(ueIpIface.GetAddress(0), dlPort);    dlClient.SetAttribute(“MaxPackets”, UintegerValue(1000000));    dlClient.SetAttribute(“Interval”, TimeValue(Seconds(0.01)));    dlClient.SetAttribute(“PacketSize”, UintegerValue(1024));    serverApps.Add(dlClient.Install(ueNodes.Get(0)));

    // Run the simulation    Simulator::Stop(Seconds(simTime));


    // Clean up


    return 0;


  1. Perform the Simulation: For performing the simulation process, execute the developed script.

./waf –run scratch/my-5g-simulation

  1. Examine Outcomes: Employ the tracing and logging characteristics of NS-3 to gather and examine the simulation outcomes.
  2. Simulating 5G Networks with OMNeT++ and Simu5G

Procedural Instruction:

  1. Configure OMNeT++ Platform: First, the Simu5G library and OMNeT++ have to be installed properly.
  2. Develop a New Project: A novel OMNeT++ project must be created. Then, encompass the library of Simu5G.
  3. Create Network Topology: Utilize the NED language to develop a network topology.

network 5GNetwork



        int numUEs = default(10);


        enb: Simu5GEnb {


                numUEs = numUEs;


        ue[numUEs]: Simu5GUE;

    connections allowunconnected:

        enb.phy –> ue[*].phy;

        ue[*].phy –> enb.phy;


  1. Arrange Simulation Parameters: In the OMNeT++ setup file (omnetpp.ini), arrange the significant simulation parameters.


network = 5GNetwork

sim-time-limit = 100s

*.enb.carrierFrequency = 28e9

*.enb.bandwidth = 100e6

*.enb.numAntennas = 64

*.ue[*].numAntennas = 1

*.ue[*].mobility.x = uniform(0, 100)

*.ue[*].mobility.y = uniform(0, 100)

  1. Execute the Simulation: From the command line or OMNeT++ IDE, perform the simulation efficiently.

./5GNetwork -u Cmdenv -c General

  1. Examine Outcomes: For visualizing and examining the simulation data, employ the result analysis tools of the OMNeT++.

5g Network Simulator List

At phdservices.org, we provide a wide range of 5g Network Simulator topics tailored to scholars of all levels. Our team of experts is highly specialized in delivering full thesis writing assistance to scholars. With our dedicated and committed approach, we offer personalized support, meticulous editing, and invaluable guidance to ensure that scholars receive the necessary assistance to develop exceptional thesis. Drop us all your 5G doubts we will give you proper response.

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  13. Platform configurations for local and private 5G networks in complex industrial multi-stakeholder ecosystems
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  18. Managing 5G network slicing and edge computing with the MATILDA telecom layer platform
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