To implement the network channel coding in ns3, if we want to enhance the consistency of transmitted data over a noisy communication channels we can execute only by simulating the error detection and correction mechanisms. Forward Error Correction (FEC) is one of the methods of channel coding that are used to detect and correct errors in transmitted data. If you want, we can also provide any added information regarding network channel coding.
Here we provide the step-by-step implementation process to create a basic simulation of network channel coding in ns3:
Step-by-Step Implementation:
Step 1: Setup ns3 Environment
Make sure, you have ns3 installed and properly configured.
git clone https://gitlab.com/nsnam/ns-3-dev.git
cd ns-3-dev
./waf configure
./waf build
Step 2: Create the Network Channel Coding Simulation Script
Once the installation is done, we are simulating a noisy channel and apply a basic error correction mechanism by creating a script. That script should be able to set up a network with the error models. We are providing a sample below for your reference.
#include “ns3/core-module.h”
#include “ns3/network-module.h”
#include “ns3/internet-module.h”
#include “ns3/point-to-point-module.h”
#include “ns3/mobility-module.h”
#include “ns3/applications-module.h”
#include “ns3/wifi-module.h”
#include “ns3/error-model.h”
#include “ns3/flow-monitor-module.h”
using namespace ns3;
NS_LOG_COMPONENT_DEFINE(“NetworkChannelCodingExample”);
class SimpleFecErrorModel : public ErrorModel
{
public:
static TypeId GetTypeId(void)
{
static TypeId tid = TypeId(“ns3::SimpleFecErrorModel”)
.SetParent<ErrorModel>()
.SetGroupName(“Network”)
.AddConstructor<SimpleFecErrorModel>()
.AddAttribute(“ErrorRate”,
“The rate of errors (0.0 to 1.0) before FEC”,
DoubleValue(0.01),
MakeDoubleAccessor(&SimpleFecErrorModel::m_errorRate),
MakeDoubleChecker<double>())
.AddAttribute(“FecRate”,
“The rate of errors corrected by FEC (0.0 to 1.0)”,
DoubleValue(0.9),
MakeDoubleAccessor(&SimpleFecErrorModel::m_fecRate),
MakeDoubleChecker<double>());
return tid;
}
SimpleFecErrorModel() : m_errorRate(0.01), m_fecRate(0.9) {}
private:
virtual bool DoCorrupt(Ptr<Packet> p)
{
double errorProb = UniformVariable().GetValue();
if (errorProb < m_errorRate)
{
double correctProb = UniformVariable().GetValue();
if (correctProb > m_fecRate)
{
return true; // Uncorrectable error
}
}
return false; // Error corrected or no error
}
virtual void DoReset(void) {}
double m_errorRate;
double m_fecRate;
};
void CourseChange(std::string context, Ptr<const MobilityModel> model)
{
Vector position = model->GetPosition();
NS_LOG_UNCOND(Simulator::Now().GetSeconds() << “s: Node position: (” << position.x << “, ” << position.y << “, ” << position.z << “)”);
}
int main(int argc, char *argv[])
{
CommandLine cmd;
cmd.Parse(argc, argv);
// Create nodes
NodeContainer nodes;
nodes.Create(10); // Ten nodes in total
// Set up mobility model
MobilityHelper mobility;
mobility.SetPositionAllocator(“ns3::GridPositionAllocator”,
“MinX”, DoubleValue(0.0),
“MinY”, DoubleValue(0.0),
“DeltaX”, DoubleValue(10.0),
“DeltaY”, DoubleValue(10.0),
“GridWidth”, UintegerValue(5),
“LayoutType”, StringValue(“RowFirst”));
mobility.SetMobilityModel(“ns3::ConstantPositionMobilityModel”);
mobility.Install(nodes);
// Set up WiFi
WifiHelper wifi;
wifi.SetRemoteStationManager(“ns3::AarfWifiManager”);
WifiMacHelper mac;
Ssid ssid = Ssid(“ns-3-ssid”);
mac.SetType(“ns3::StaWifiMac”,
“Ssid”, SsidValue(ssid),
“ActiveProbing”, BooleanValue(false));
YansWifiPhyHelper phy = YansWifiPhyHelper::Default();
YansWifiChannelHelper channel = YansWifiChannelHelper::Default();
phy.SetChannel(channel.Create());
NetDeviceContainer devices = wifi.Install(phy, mac, nodes);
mac.SetType(“ns3::ApWifiMac”,
“Ssid”, SsidValue(ssid));
NetDeviceContainer apDevices = wifi.Install(phy, mac, nodes.Get(0));
// Apply FEC error model to emulate channel coding effects
Ptr<SimpleFecErrorModel> errorModel = CreateObject<SimpleFecErrorModel>();
errorModel->SetAttribute(“ErrorRate”, DoubleValue(0.05)); // Example error rate before FEC
errorModel->SetAttribute(“FecRate”, DoubleValue(0.9)); // Example FEC correction rate
devices.Get(1)->SetAttribute(“ReceiveErrorModel”, PointerValue(errorModel));
// Install the internet stack
InternetStackHelper stack;
stack.Install(nodes);
// Assign IP addresses
Ipv4AddressHelper address;
address.SetBase(“10.1.1.0”, “255.255.255.0”);
Ipv4InterfaceContainer interfaces = address.Assign(devices);
address.Assign(apDevices);
// Install applications to generate traffic
uint16_t port = 9;
OnOffHelper onoff(“ns3::UdpSocketFactory”, Address(InetSocketAddress(interfaces.GetAddress(1), port)));
onoff.SetConstantRate(DataRate(“1Mbps”));
ApplicationContainer apps = onoff.Install(nodes.Get(0));
apps.Start(Seconds(1.0));
apps.Stop(Seconds(10.0));
PacketSinkHelper sink(“ns3::UdpSocketFactory”, Address(InetSocketAddress(Ipv4Address::GetAny(), port)));
apps = sink.Install(nodes.Get(1));
apps.Start(Seconds(0.0));
apps.Stop(Seconds(10.0));
// Enable FlowMonitor to measure performance metrics
FlowMonitorHelper flowmon;
Ptr<FlowMonitor> monitor = flowmon.InstallAll();
// Run the simulation
Simulator::Stop(Seconds(15.0));
Simulator::Run();
// Print per-flow statistics
monitor->CheckForLostPackets();
Ptr<Ipv4FlowClassifier> classifier = DynamicCast<Ipv4FlowClassifier>(flowmon.GetClassifier());
std::map<FlowId, FlowMonitor::FlowStats> stats = monitor->GetFlowStats();
for (std::map<FlowId, FlowMonitor::FlowStats>::const_iterator i = stats.begin(); i != stats.end(); ++i)
{
Ipv4FlowClassifier::FiveTuple t = classifier->FindFlow(i->first);
NS_LOG_UNCOND(“Flow ” << i->first << ” (” << t.sourceAddress << ” -> ” << t.destinationAddress << “)”);
NS_LOG_UNCOND(” Tx Packets: ” << i->second.txPackets);
NS_LOG_UNCOND(” Tx Bytes: ” << i->second.txBytes);
NS_LOG_UNCOND(” Rx Packets: ” << i->second.rxPackets);
NS_LOG_UNCOND(” Rx Bytes: ” << i->second.rxBytes);
NS_LOG_UNCOND(” Lost Packets: ” << i->second.lostPackets);
NS_LOG_UNCOND(” Throughput: ” << i->second.rxBytes * 8.0 / (i->second.timeLastRxPacket.GetSeconds() – i->second.timeFirstTxPacket.GetSeconds()) / 1024 / 1024 << ” Mbps”);
}
// Clean up
Simulator::Destroy();
return 0;
}
Step 3: Compile and Run the Simulation
- Compile the Simulation:
./waf configure –enable-examples
./waf build
- Run the Simulation:
./waf –run scratch/network-channel-coding-example
Step 4: Analyze Results
If we want to match the properties of channel coding then we have to apply the Custom error model only by simulating a script which will sets up the network topology including the nodes. The error model introduces a certain error rate to the received packets, simulating the impact of noise and the effect of Forward Error Correction (FEC). By using FlowMonitor, we can collect and print out statistics about the traffic flows, such as packet loss, throughput, and delay.
Additional Considerations
We can also be able to enhance, by extending the functionality of the network channel coding simulation, consider the following steps:
1. Advanced Error Models
If you want the models that can be able to emulate the effects of various types of channel coding, then we have to implement more sophisticated error models. The types of channel coding includes convolutional codes, turbo codes, or LDPC codes.
2. Realistic Channel Models
By simulating the effects of the wireless environment on channel coding, we can integrate the realistic channel models that responsible for aspects like fading, shadowing and path loss.
3. Adaptive Coding
If we want to enhance the error correction performance, we have to implement the coding schemes that can be modified depends on the channel condition or any other network parameters.
4. Performance Metrics
We can also determine the performance of the channel coding mechanisms by collecting and analyze additional metrics such as bit error rate (BER), symbol error rate (SER), and signal-to-noise ratio (SNR)
5. Real-World Scenarios
We can also examine the effectiveness of the channel coding when it occurs in a practical applications, simply by simulating the real-world examples such as cellular networks, IoT deployments or vehicular networks.
In conclusion, we successfully learned the implementation process and their additional consideration with the sample about how to implement network channel coding in ns3 through the script.
Implementation of Network Channel coding in ns3tool will be done by our experts if you face hardships after going through the above steeps then reach out for your help. We will help you with performance analysis of your project.