How to Begin Implement Network Channel Capacity in NS3

To begin and analyzing network channel capacity in NS3 has includes the measure of theoretical or observed maximum data rate a communication channel can accomplish for below the specified environments. The Channel capacity is an essential metric for networking and influenced through the factors such as bandwidth, signal-to-noise ratio (SNR), and interference.

Steps to Implement Network Channel Capacity in NS3

1. Understand Channel Capacity

• Definition: Channel capacity (CCC) is the maximum success data rate in bits per second (bps) complete the transmission channel deprived of error.
• Shannon-Hartley Theorem:

C=B⋅log⁡2(1+SNR)C = B \cdot \log_2(1 + \text{SNR})C=B⋅log2​(1+SNR)

where:

• • CCC: Channel capacity (bps).
  • BBB: Channel bandwidth (Hz).
  • SNR\text{SNR}SNR: Signal-to-noise ratio (linear, not dB).
• Practical Observations:
  • Use tools such as FlowMonitor to estimate the real throughput that reflects the capacity effective for below the replication environments.

2. Set Up the NS3 Environment

1. Install NS3:
   • Assure the tool NS3 is installed and operational. Download it from the NS3 website.
2. Choose a Network Scenario:
   • Use the wireless or wired network that channel capacity can be influenced through noise, interference, or congestion.

3. Calculate Channel Capacity

1. Define Theoretical Capacity:
   • Uses the Shannon-Hartley theorem for calculate the theoretical channel capacity according to their bandwidth and SNR.
2. Measure Actual Throughput:
   • Use NS3 tool components such as FlowMonitor to seizure throughput, reflecting the channel capacity for effective.

4. Implement Channel Capacity Measurement

Under is an example NS3 script to calculate the theoretical and observed channel capacities.

Example Script: Channel Capacity in NS3

#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/flow-monitor-helper.h”

using namespace ns3;

double ComputeShannonCapacity(double bandwidth, double snr) {

return bandwidth * std::log2(1 + snr); // Shannon capacity in bps

}

void MeasureThroughput(Ptr<FlowMonitor> monitor, double simulationTime, double theoreticalCapacity) {

FlowMonitor::FlowStatsContainer stats = monitor->GetFlowStats();

uint64_t totalBytes = 0;

for (auto const &flow : stats) {

totalBytes += flow.second.rxBytes;

}

double observedThroughput = (totalBytes * 8.0) / simulationTime; // Throughput in bits per second

NS_LOG_UNCOND(“Theoretical Channel Capacity: ” << theoreticalCapacity / 1e6 << ” Mbps”);

NS_LOG_UNCOND(“Observed Throughput: ” << observedThroughput / 1e6 << ” Mbps”);

}

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

CommandLine cmd;

cmd.Parse(argc, argv);

// Create nodes

NodeContainer nodes;

nodes.Create(2);

// Configure Point-to-Point link

double bandwidth = 10e6;  // Bandwidth in Hz (10 Mbps)

double noisePower = 1e-10; // Noise power in Watts

double signalPower = 1e-6; // Signal power in Watts

double snr = signalPower / noisePower; // Signal-to-noise ratio (linear)

PointToPointHelper pointToPoint;

pointToPoint.SetDeviceAttribute(“DataRate”, StringValue(“10Mbps”));

pointToPoint.SetChannelAttribute(“Delay”, StringValue(“2ms”));

NetDeviceContainer devices = pointToPoint.Install(nodes);

// Install 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);

// Install applications

uint16_t port = 9;

UdpEchoServerHelper server(port);

ApplicationContainer serverApp = server.Install(nodes.Get(1));

serverApp.Start(Seconds(1.0));

serverApp.Stop(Seconds(10.0));

UdpEchoClientHelper client(interfaces.GetAddress(1), port);

client.SetAttribute(“MaxPackets”, UintegerValue(100));

client.SetAttribute(“Interval”, TimeValue(MilliSeconds(100))); // Packet every 100 ms

client.SetAttribute(“PacketSize”, UintegerValue(1024));        // Payload size: 1024 bytes

ApplicationContainer clientApp = client.Install(nodes.Get(0));

clientApp.Start(Seconds(2.0));

clientApp.Stop(Seconds(10.0));

// Compute theoretical channel capacity

double theoreticalCapacity = ComputeShannonCapacity(bandwidth, snr);

// Install Flow Monitor

FlowMonitorHelper flowmonHelper;

Ptr<FlowMonitor> monitor = flowmonHelper.InstallAll();

// Schedule throughput measurement

double simulationTime = 10.0; // seconds

Simulator::Schedule(Seconds(simulationTime), &MeasureThroughput, monitor, simulationTime, theoreticalCapacity);

Simulator::Run();

Simulator::Destroy();

return 0;

}

Explanation of the Script

1. Theoretical Capacity:
   • Estimated using the Shannon-Hartley theorem: C=B⋅log⁡2(1+SNR)C = B \cdot \log_2(1 + \text{SNR})C=B⋅log2​(1+SNR)
   • Bandwidth (BBB) is 10 MHz, SNR is measured from the signal and noise power.
2. Observed Throughput:
   • Amount of using the FlowMonitor component that monitor the payload bytes for received during the replication.
3. Comparison:
   • Logs are together the theoretical channel capacity and observed throughput for comparison.
4. UDP Traffic:
   • An UdpEchoClient forward the congestion to a UdpEchoServer, generating network activity for throughput capacity.

5. Run the Simulation

1. Make a replication for the script:

./waf –run “your-script-name”

1. Track the logs for theoretical and detected the channel capacities.

6. Analyze Results

• Theoretical vs Observed:
  • Associate the theoretical capacity for ideal conditions by studied the throughput such as realistic conditions.
• Impact of SNR:
  • Modify the signal or noise power and follow the impact of channel capacity.

Advanced Extensions

1. Wireless Networks:
   • Use the Wifi or Lte component to estimate the channel capacity in wireless environments.
2. Interference:
   • It replicates the several users or flows and follow on how interference the impact of capacity.
3. Dynamic Scenarios:
   • Launch the mobility or alter the SNR environments for examine the dynamic channel capacities.
4. Visualization:
   • Distribute the outcomes for graphical analysis using tools such as MATLAB, Python, or Excel.
5. Protocol Comparison:
   • Validate the channel capacity for below various transport protocols for sample TCP vs UDP.

Network Channel Capacity had been Calculated and Executed in the simulation by use of Shannon-Hartley theorem in ns3 tools. Further assistance regarding the project will be provided in another manual.