How to Begin Implement Network Link Strength in NS3

To implement and examine Network Link Strength in NS3, we require estimating the metrics that describe the value and reliability for communication connection. Link strength frequently connects to factors like as Signal-to-Noise Ratio (SNR), Received Signal Strength Indicator (RSSI), or link quality metrics derived from these values.

Steps to Implement Network Link Strength in NS3

1. Understand Link Strength

• Definition: Link strength is an amount of the reliability or quality for the communication connection, often derived from signal strength, noise, interference, and distance among nodes.
• Metrics:
  • RSSI (Received Signal Strength Indicator): Estimates the power level for the received signal.
  • SNR (Signal-to-Noise Ratio): Percentage of signal power to noise power.
  • Link Quality Indicator (LQI): A qualitative performance of metric used in similar wireless protocols.

2. Set Up NS3 Simulation Environment

1. Install NS3:
   • Assures the NS3 is installed and setting. Download it from the NS3 website.
2. Choose a Network Type:
   • Use the wireless networks for instance WiFi or LTE, as link strength is most related in such environments.

3. Configure and Measure Link Strength

1. Calculate RSSI:
   • Use the YansWifiPhy helper for monitor the received signal strength.
2. Calculate SNR:
   • Derive the SNR using received signal strength and noise power.

4. Implement Link Strength Calculation

Under is a sample for script to estimate and log link strength such as RSSI and SNR in a WiFi network.

Example Script: Link Strength in NS3

#include “ns3/core-module.h”

#include “ns3/network-module.h”

#include “ns3/internet-module.h”

#include “ns3/wifi-module.h”

#include “ns3/mobility-module.h”

#include “ns3/log.h”

using namespace ns3;

NS_LOG_COMPONENT_DEFINE(“LinkStrengthExample”);

void MonitorSignalStrength(Ptr<WifiPhy> phy, Ptr<MobilityModel> mobility1, Ptr<MobilityModel> mobility2) {

double distance = mobility1->GetDistanceFrom(mobility2);

double rssi = phy->GetRxPower(distance); // Received signal strength

double noisePower = -100.0; // Example noise power in dBm

double snr = rssi – noisePower; // Simplified SNR calculation in dB

NS_LOG_UNCOND(“Time: ” << Simulator::Now().GetSeconds() << “s, Distance: ” << distance << “m, RSSI: ” << rssi << ” dBm, SNR: ” << snr << ” dB”);

Simulator::Schedule(Seconds(1.0), &MonitorSignalStrength, phy, mobility1, mobility2);

}

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

CommandLine cmd;

cmd.Parse(argc, argv);

// Create nodes

NodeContainer nodes;

nodes.Create(2);

// Configure WiFi

YansWifiChannelHelper wifiChannel = YansWifiChannelHelper::Default();

YansWifiPhyHelper wifiPhy = YansWifiPhyHelper::Default();

wifiPhy.SetChannel(wifiChannel.Create());

WifiHelper wifi;

wifi.SetStandard(WIFI_PHY_STANDARD_80211g);

WifiMacHelper mac;

mac.SetType(“ns3::AdhocWifiMac”); // Ad-hoc mode

NetDeviceContainer devices = wifi.Install(wifiPhy, mac, nodes);

// Configure mobility

MobilityHelper mobility;

mobility.SetMobilityModel(“ns3::ConstantPositionMobilityModel”);

mobility.Install(nodes);

nodes.Get(0)->GetObject<MobilityModel>()->SetPosition(Vector(0.0, 0.0, 0.0)); // Node 0 at origin

nodes.Get(1)->GetObject<MobilityModel>()->SetPosition(Vector(50.0, 0.0, 0.0)); // Node 1 at 50m distance

// Attach monitor to the PHY layer of the first node

Ptr<WifiNetDevice> wifiDevice = DynamicCast<WifiNetDevice>(devices.Get(0));

Ptr<WifiPhy> phy = wifiDevice->GetPhy();

// Start signal strength monitoring

Simulator::Schedule(Seconds(1.0), &MonitorSignalStrength, phy, nodes.Get(0)->GetObject<MobilityModel>(), nodes.Get(1)->GetObject<MobilityModel>());

Simulator::Stop(Seconds(10.0));

Simulator::Run();

Simulator::Destroy();

return 0;

}

Explanation of the Script

1. WiFi Configuration:
   • Setting a simple ad-hoc WiFi network using YansWifiPhy and AdhocWifiMac.
2. Mobility:
   • Fixed the constant places for nodes to replicate the distance-based signal degradation.
3. RSSI Calculation:
   • WifiPhy::GetRxPower() is used to compute the received signal strength according to their distance.
4. SNR Calculation:
   • SNR is calculated as: SNR (dB)=RSSI (dBm)−Noise Power (dBm)\text{SNR (dB)} = \text{RSSI (dBm)} – \text{Noise Power (dBm)}SNR (dB)=RSSI (dBm)−Noise Power (dBm)
5. Logging:
   • Logs RSSI, SNR, and distance at 1-second intervals.

5. Run the Simulation

1. Make the script:

./waf –run “link-strength-example”

1. During the replication for follow the logs in distance, RSSI, and SNR values.

6. Analyze Results

• Impact of Distance:
  • Improve the distance among nodes and track on how the RSSI and SNR degrade.
• Impact of Noise:
  • Alter the noise power for examines the impact on SNR.

In the conclusion, we obviously simulate the network link strength in the network that was performed in the ns3 tool that enhances to protect the communication inside the wireless network. We design to distribute further information about the network link strength.