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How to Implement Cognitive Radio Networks in OMNeT++

To implement the Cognitive Radio Networks (CRNs) in OMNeT++ take in set up a reproduction situation among the developing cognitive radio-specific protocols, defining network models, and cognitive radio nodes. The INET framework may be lengthy to maintenance CRN functionalities. This step-by-step guide to help to get started with a basic CRN simulation in OMNeT++ is mentioned below.

Step-by-step Implementation:

Step 1: Install OMNeT++ and INET Framework

  1. Download OMNeT++:
    • Download the latest version to move on the OMNeT++.
  2. Install OMNeT++:
    • For the operating system we have to follow the installation instructions.
  3. Download and Install INET Framework:
    • This framework is often sing OMNeT++. For the internet protocols provided by the INET framework.
    • From the INET network we can download it.

Step 2: Set Up Your Project

  1. Create a New OMNeT++ Project:
    • Exposed the OMNeT++ IDE.
    • Move on File -> New -> OMNeT++ Project.
    • Select the appropriate choices to enter a project name.
  2. Set Up Directory Structure:
    • For NED files and configuration to simulates and make sure the project had the necessary folders.
  3. Add INET to Your Project:
    • Proceeding the project in the Project Explorer.
    • Choice Properties -> Project References.
    • Form the box for INET.

Step 3: Define Cognitive Radio Network Models Using NED

  1. Create NED Files:
  • Make a fresh NED file like CognitiveRadioNetwork.ned in the src directory, in the NED file to determine the network topology. Given below the sample examples:

packagecognitive;

import inet.node.inet.StandardHost;

import inet.node.inet.Router;

import inet.networklayer.configurator.ipv4.Ipv4NetworkConfigurator;

import inet.physicallayer.common.packetlevel.RadioMedium;

import inet.mobility.single.RandomWaypointMobility;

network CognitiveRadioNetwork

{

parameters:

int numCognitiveNodes = default(10);

types:

channel radioChannel extends RadioMedium {}

submodules:

configurator: Ipv4NetworkConfigurator {

@display(“p=100,100”);

}

baseStation: Router {

@display(“p=200,100”);

}

cognitiveNode[numCognitiveNodes]: StandardHost {

@display(“p=300+100*i,200”);

mobility.typename = “RandomWaypointMobility”;

}

radioMedium: radioChannel {

@display(“p=400,100”);

}

connections allowunconnected:

for i=0..numCognitiveNodes-1 {

cognitiveNode[i].wlan[0] <–> radioMedium <–> baseStation.wlan[0];

}

}

Step 4: Implement Cognitive Radio Communication Logic

  1. Modify INET’s Physical Layer:
    • To support cognitive radio functionalities like vigorous field contact and sensing is access by INET’s physical layer.
  2. Update NED for Cognitive Radio:
  • To configure the cognitive radio nodes for inform the NED file.

network CognitiveRadioNetwork

{

parameters:

int numCognitiveNodes = default(10);

types:

channel radioChannel extends RadioMedium {

@display(“bgb=600,600;bgi=background;bgf=bg.jpg”);

}

submodules:

configurator: Ipv4NetworkConfigurator {

@display(“p=100,100”);

}

baseStation: Router {

@display(“p=200,100”);

}

cognitiveNode[numCognitiveNodes]: StandardHost {

@display(“p=300+100*i,200”);

mobility.typename = “RandomWaypointMobility”;

}

radioMedium: radioChannel {

@display(“p=400,100”);

physicalEnvironmentModule = “^.^.physicalEnvironment”;

backgroundNoiseModule = “^.^.backgroundNoise”;

}

connections allowunconnected:

for i=0..numCognitiveNodes-1 {

cognitiveNode[i].wlan[0] <–> radioMedium <–> baseStation.wlan[0];

}

}

Step 5: Implement Custom Cognitive Radio Modules

  1. Create C++ Modules:
    • To make a fresh C++ class on the src directory.
    • Express the custom cognitive radio logic to involve the necessary OMNeT++.

#include <omnetpp.h>

#include “inet/applications/base/ApplicationBase.h”

#include “inet/applications/udpapp/UdpBasicApp.h”

#include “inet/networklayer/common/L3AddressResolver.h”

#include “inet/networklayer/contract/ipv4/Ipv4Address.h”

#include “inet/networklayer/contract/IL3AddressType.h”

#include “inet/physicallayer/contract/packetlevel/IRadio.h”

using namespace omnetpp;

using namespace inet;

class CognitiveRadioApp : public ApplicationBase

{

protected:

virtual void initialize(int stage) override;

virtual void handleMessageWhenUp(cMessage *msg) override;

void senseSpectrum();

void sendPacket();

void handlePacket(cPacket *pkt);

cMessage *sensingEvent = nullptr;

};

 

Define_Module(CognitiveRadioApp);

 

void CognitiveRadioApp::initialize(int stage)

{

ApplicationBase::initialize(stage);

if (stage == INITSTAGE_LOCAL) {

// Initialization code

if (par(“senseSpectrum”).boolValue()) {

sensingEvent = new cMessage(“senseSpectrum”);

scheduleAt(simTime() + par(“sensingInterval”), sensingEvent);

}

}

}

void CognitiveRadioApp::handleMessageWhenUp(cMessage *msg)

{

if (msg == sensingEvent) {

senseSpectrum();

scheduleAt(simTime() + par(“sensingInterval”), sensingEvent);

} else if (msg->isSelfMessage()) {

if (strcmp(msg->getName(), “sendPacket”) == 0) {

sendPacket();

scheduleAt(simTime() + par(“sendInterval”), msg);

}

} else {

cPacket *pkt = check_and_cast<cPacket *>(msg);

handlePacket(pkt);

}

}

void CognitiveRadioApp::senseSpectrum()

{

// Implement spectrum sensing logic

EV << “Sensing spectrum” << endl;

}

void CognitiveRadioApp::sendPacket()

{

// Create and send a packet

EV << “Sending packet” << endl;

cPacket *pkt = new cPacket(“CognitiveRadioPacket”);

pkt->setByteLength(par(“packetSize”));

send(pkt, “lowerLayerOut”);

}

void CognitiveRadioApp::handlePacket(cPacket *pkt)

{

// Handle received packet

EV << “Received packet: ” << pkt->getName() << endl;

delete pkt;

}

  1. Modify NED to Use Custom Modules:
    • By using the custom cognitive radio application module to inform the NED file.

network CognitiveRadioNetwork

{

parameters:

int numCognitiveNodes = default(10);

types:

channel radioChannel extends RadioMedium {

@display(“bgb=600,600;bgi=background;bgf=bg.jpg”);

}

submodules:

configurator: Ipv4NetworkConfigurator {

@display(“p=100,100”);

}

baseStation: Router {

@display(“p=200,100”);

}

cognitiveNode[numCognitiveNodes]: StandardHost {

@display(“p=300+100*i,200”);

mobility.typename = “RandomWaypointMobility”;

@children:

udpApp: CognitiveRadioApp {

localPort = 12345;

destPort = 54321;

startTime = uniform(0, 1s);

packetSize = 512B;

sendInterval = exponential(1s);

senseSpectrum = true;

sensingInterval = exponential(1s);

}

}

radioMedium: radioChannel {

@display(“p=400,100”);

physicalEnvironmentModule = “^.^.physicalEnvironment”;

backgroundNoiseModule = “^.^.backgroundNoise”;

}

connections allowunconnected:

for i=0..numCognitiveNodes-1 {

cognitiveNode[i].wlan[0] <–> radioMedium <–> baseStation.wlan[0];

}

}

Step 6: Configure Simulation Parameters

  1. Create omnetpp.ini:
    • To make an omnetpp.ini file on the simulations.
    • Outline the simulation parameters, like duration and network parameters:

[General]

network = CognitiveRadioNetwork

sim-time-limit = 100s

# Mobility

**.cognitiveNode[*].mobility.bounds = “0,0,1000,1000”

**.cognitiveNode[*].mobility.speed = uniform(1mps, 10mps)

# Radio medium configuration

**.radioMedium.typename = “Ieee80211ScalarRadioMedium”

**.radioMedium.propagation.typename = “ConstantSpeedPropagation”

**.radioMedium.pathLoss.typename = “FreeSpacePathLoss”

**.radioMedium.obstacleLoss.typename = “TraceObstacleLoss”

**.radioMedium.backgroundNoise.typename = “IsotropicScalarBackgroundNoise”

**.radioMedium.mediumLimitCache.typename = “GridMediumLimitCache”

**.radioMedium.rangeFilter.typename = “ConstantRangeFilter”

# Physical layer configuration

**.cognitiveNode[*].wlan[*].radio.typename = “Ieee80211ScalarRadio”

**.cognitiveNode[*].wlan[*].radio.transmitter.power = 20mW

**.cognitiveNode[*].wlan[*].radio.receiver.sensitivity = -85dBm

Step 7: Build and Run the Simulation

  1. Build the Project:
    • First to select BuildProject , choice on the projects in OMNeT++ IDE.
  2. Run the Simulation:
    • Move on Run -> Run Configurations.
    • To run simulate and for the project to setting up a new run configuration.

Step 8: Analyze Results

  1. View Simulation Results:
    • To examine the outcomes after the simulation completes, by using OMNeT++’s tools.
    • To read the information and to open the ANF (Analysis Framework) to envision.

In this scripts the summary in the method to formulate the Cognitive Radio Networks in OMNeT++. We may perform these evocative to spread the Cognitive Radio Networks and we study more explain to implement custom cognitive radio modules. We are enthusiastic to underwrite the active compressed to state the Cognitive Radio Networks in ns3.

Reach out to us for exceptional simulation and project performance on Cognitive Radio Networks using OMNeT++. Our expert developers specialize in creating cognitive radio-specific protocols, designing network models, and building cognitive radio nodes tailored to your project, ensuring you receive the best ideas and solutions.

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