How to Implement Network Physical Layer Communication in NS2

To implement the Network Physical Layer Communication in Network Simulator 2 (NS2), we need to model the essential characteristics of data transmission through a communication medium.  This layer is accountable for the actual transmission of raw bits over a physical medium, managing properties like modulation, signal propagation, error rates, bandwidth and more. Since ns2 offers few built-in abilities for physical layer simulation, extending or tailoring it permits for more precise and certain modeling customized based on the research or project requirements.

Below is a overall guide to implementing and customizing the Physical Layer in NS2:

Step-by-Step Implementation:

1. Understand NS2’s Existing Physical Layer

Before extending or tailoring the Physical Layer, it’s crucial to understand how NS2 currently manages it.

• Wireless Models: NS2 mainly supports wireless network simulations as well as models like IEEE 802.11 (Wi-Fi), IEEE 802.15.4 (ZigBee), and others. These models integrate physical layer characteristics like signal propagation, meddling, and basic modulation schemes.
• Components:
  • PHY Layer: Handles modulation, coding, and signal processing.
  • MAC Layer: Manages medium access control, interfacing with the PHY layer.
  • Channel Models: Replicate signal propagation, path loss, fading, and intervention.
• Key Files and Classes:
  • phy.cc and phy.h: State the Physical Layer classes.
  • channel.cc and channel.h: Handle channel properties and signal propagation.
  • Modulation schemes and error models are surrounded inside these classes.

Know the elements that will help you find where to make alterations or extensions.

2. Set Up Your NS2 Environment

Make certain to install the ns2 on your system. You can download NS2 from the official NS2 website. Follow these steps:

1. Download NS2:

wget https://sourceforge.net/projects/nsnam/files/latest/download -O ns-allinone-2.35.tar.gz

1. Extract and Install:

tar -xzvf ns-allinone-2.35.tar.gz

cd ns-allinone-2.35

./install

1. Set Environment Variables: Add the following lines to your .bashrc or .bash_profile:

export PATH=$PATH:/path/to/ns-allinone-2.35/bin:/path/to/ns-allinone-2.35/tcl8.5.10/unix:/path/to/ns-allinone-2.35/tk8.5.10/unix

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/ns-allinone-2.35/otcl-1.14:/path/to/ns-allinone-2.35/lib

Replace /path/to/ with the actual installation directory.

1. Verify Installation:

ns

This should open the NS2 interactive shell.

3. Design the Physical Layer Model

To execute or extend the Physical Layer, you need to decide what certain characteristics you want to model or improve. Frequent extensions include:

• Advanced Modulation Schemes: Executing modulation methods like QAM, PSK, OFDM, etc.
• Error Models: Launching more precise Bit Error Rate (BER) models, integrating noise, intrusion, or channel impairments.
• Signal Propagation Models: Optimizing path loss models, including multipath fading, shadowing effects, etc.
• Multiple Antennas: Accomplishing MIMO (Multiple Input Multiple Output) strategies.

For this guide, let’s concentrate on executing the latest modulation scheme (such as Quadrature Amplitude Modulation – QAM) and optimizing the error model.

4. Implementing Advanced Modulation Schemes

4.1. Extend the PHY Layer Classes

1. Navigate to the PHY Layer Source Files: The Physical Layer classes are often discovered in ns-2.35/ns-2.35/simulator or similar directories.
2. Create a New Modulation Class: For instance, to execute 16-QAM, you can generate a new class QAMModulator.

qam_modulator.h:

#ifndef QAM_MODULATOR_H

#define QAM_MODULATOR_H

#include “phy.h”

class QAMModulator : public PHY {

public:

QAMModulator();

~QAMModulator();

// Override the modulation method

virtual void Modulate(Packet *p);

// Additional methods for QAM

void SetModulationOrder(int order); // e.g., 16 for 16-QAM

private:

int modulation_order;

};

#endif // QAM_MODULATOR_H

qam_modulator.cc:

#include “qam_modulator.h”

#include <iostream>

QAMModulator::QAMModulator() : modulation_order(16) {

// Initialization code

}

QAMModulator::~QAMModulator() {

// Cleanup code

}

void QAMModulator::SetModulationOrder(int order) {

modulation_order = order;

}

void QAMModulator::Modulate(Packet *p) {

// Implement QAM modulation logic here

// This is a placeholder for the actual modulation process

std::cout << “Modulating packet with ” << modulation_order << “-QAM” << std::endl;

// Actual modulation code would convert bits to QAM symbols

}

1. Integrate the New Modulation Class:
   • Identify and consume the new modulation scheme by fine-tuning the phy.h and phy.cc.
   • For instance, attach a new modulation type in phy.h:

enum ModulationType { BPSK, QPSK, QAM };

1. • Update the PHY class to add modulation configurations:

class PHY : public Handler {

public:

// Existing members

ModulationType modulation;

 

// Method to set modulation

void SetModulation(ModulationType m) { modulation = m; }

// Override modulation method

virtual void Modulate(Packet *p) = 0;

};

1. • In your modulation class, ensure that the modulation type is set appropriately.
2. Recompile NS2: After including new files or altering available ones, you need to recompile NS2.

cd ns-allinone-2.35/ns-2.35

make clean

make

Repair any compilation errors when happens because of the adjustments.

4.2. Update OTcl Scripts to Use the New Modulation Scheme

1. Define a New PHY Type in OTcl: You need to inform NS2 about the new modulation scheme in your OTcl script.

Example:

# Define a new PHY type with QAM modulation

set qam_phy [new Phy/QAMModulator]

$qam_phy set modulation_order_ 16

1. Assign the New PHY to Nodes: When generating nodes in your simulation, allocate the QAM PHY layer.

Example:

set node1 [$ns node]

$node1 set phy_ $qam_phy

set node2 [$ns node]

$node2 set phy_ $qam_phy

1. Use the PHY in Communication: Make sure that your traffic uses the PHY layer’s modulation scheme.

Example:

# Create a simple wireless connection

set topo [new Topography]

$topo load_flatgrid 1000 1000

set prop [new Propagation/TwoRayGround]

$ns node-config -propagationModel $prop

# Assign the QAM PHY to all nodes

$ns node-config -phy_ $qam_phy

# Create a link

$ns duplex-link $node1 $node2 10Mb 10ms DropTail

5. Enhancing the Error Model

Accurate error modeling is important for simulating realistic communication situations. Let’s establish a more sophisticated Bit Error Rate (BER) model that accounts for Signal-to-Noise Ratio (SNR).

5.1. Define a BER Calculation Method Based on SNR

1. Create a New Error Model Class:

ber_model.h:

#ifndef BER_MODEL_H

#define BER_MODEL_H

class BERModel {

public:

BERModel();

~BERModel();

// Calculate BER based on SNR

double CalculateBER(double snr);

private:

// Parameters for the BER calculation

// These can be adjusted based on the modulation scheme

};

#endif // BER_MODEL_H

ber_model.cc:

#include “ber_model.h”

#include <cmath>

BERModel::BERModel() {

// Initialize parameters if needed

}

BERModel::~BERModel() {

// Cleanup if needed

}

double BERModel::CalculateBER(double snr) {

// Example BER calculation for QAM

// BER = 0.2 * erfc(sqrt(snr))

// This is a placeholder formula; actual BER formulas depend on modulation

return 0.2 * erfc(sqrt(snr));

}

1. Integrate BERModel into PHY Layer:

Integrate the BER estimation by modifying the phy.cc.

phy.cc:

#include “phy.h”

#include “ber_model.h”

PHY::PHY() {

// Existing initialization

ber_model = new BERModel();

}

PHY::~PHY() {

// Existing cleanup

delete ber_model;

}

double PHY::ComputeBER(double snr) {

return ber_model->CalculateBER(snr);

}

Make certain that ber_model.h is attached in phy.h and that a BERModel instance is existed inside the PHY class.

1. Simulate SNR in the Channel Model:

Alter the channel model to compute and offer SNR values in terms of factors like distance, transmission power, and noise.

channel.cc:

#include “channel.h”

#include <cmath>

double Channel::CalculateSNR(double tx_power, double distance) {

// Simplistic path loss model: SNR = tx_power / (distance^2 * noise)

double noise = 1e-9; // Example noise power

double path_loss = pow(distance, 2);

return tx_power / (path_loss * noise);

}

void Channel::Transmit(Packet *p, double tx_power, double distance) {

double snr = CalculateSNR(tx_power, distance);

double ber = phy_->ComputeBER(snr);

// Introduce errors based on BER

// Example: flip bits with probability equal to BER

// Implement bit flipping logic here

}

1. Recompile NS2: After making alterations, recompile NS2 to establish the new error model.

cd ns-allinone-2.35/ns-2.35

make clean

make

6. Implement Signal Propagation Models

Precise signal propagation models are vital for simulating realistic physical layer activities. Let’s execute a more latest path loss model like the Log-Distance Path Loss Model.

6.1. Define the Log-Distance Path Loss Model

1. Create a New Channel Class:

log_distance_channel.h:

#ifndef LOG_DISTANCE_CHANNEL_H

#define LOG_DISTANCE_CHANNEL_H

#include “channel.h”

class LogDistanceChannel : public Channel {

public:

LogDistanceChannel();

~LogDistanceChannel();

// Override the path loss calculation

virtual double CalculatePathLoss(double distance);

private:

double path_loss_exponent; // Typically between 2 (free space) and 4 (urban)

double reference_distance;

double reference_path_loss;

};

#endif // LOG_DISTANCE_CHANNEL_H

log_distance_channel.cc:

#include “log_distance_channel.h”

#include <cmath>

LogDistanceChannel::LogDistanceChannel() {

// Initialize default parameters

path_loss_exponent = 3.0; // Example value for urban environment

reference_distance = 1.0; // 1 meter

reference_path_loss = 30.0; // Example path loss at reference distance in dB

}

LogDistanceChannel::~LogDistanceChannel() {

// Cleanup if needed

}

double LogDistanceChannel::CalculatePathLoss(double distance) {

if (distance < reference_distance) {

distance = reference_distance;

}

// Log-Distance Path Loss Formula: PL(d) = PL(d0) + 10 * n * log10(d/d0)

double path_loss = reference_path_loss + 10 * path_loss_exponent * log10(distance / reference_distance);

return path_loss; // in dB

}

1. Integrate the Log-Distance Model into the PHY Layer:

Fine-tune the PHY layer to use the new path loss model.

phy.cc:

#include “phy.h”

#include “log_distance_channel.h”

PHY::PHY() {

// Existing initialization

channel_ = new LogDistanceChannel();

}

PHY::~PHY() {

// Existing cleanup

delete channel_;

}

double PHY::GetPathLoss(double distance) {

return channel_->CalculatePathLoss(distance);

}

1. Update the OTcl Script to Use the New Channel Model:

In your OTcl script, certain the utilization of the Log-Distance Channel.

Example OTcl Script:

# Create a Simulator object

set ns [new Simulator]

set nf [open out.nam w]

$ns namtrace-all $nf

# Create nodes

set node1 [$ns node]

set node2 [$ns node]

# Define the Log-Distance Path Loss Model

set path_loss_model [new Channel/LogDistanceChannel]

$node1 set channel_ $path_loss_model

$node2 set channel_ $path_loss_model

# Define duplex link with the new channel model

$ns duplex-link $node1 $node2 10Mb 10ms DropTail

# Set PHY parameters if necessary

# For example, set transmission power

$node1 set tx_power_ 20.0 ;# in dBm

$node2 set tx_power_ 20.0

# Define traffic (e.g., FTP)

set ftp [new Application/FTP]

$ftp attach-agent [$ns node-agent $node1]

set sink [new Agent/Sink]

$ns attach-agent $node2 $sink

$ns connect $ftp $sink

# Start the FTP transfer at time 1.0

$ns at 1.0 “start $ftp”

# End the simulation at time 10.0

$ns at 10.0 “finish”

proc finish {} {

global ns nf

$ns flush-trace

close $nf

exit 0

}

$ns run

1. Recompile NS2: After making changes, recompile NS2.

cd ns-allinone-2.35/ns-2.35

make clean

make

7. Implement Multiple Antenna Techniques (Optional)

Executing MIMO (Multiple Input Multiple Output) strategies can significantly optimize the Physical Layer’s potential by permitting multiple data streams to be transferred and received instantaneously.

7.1. Extend PHY Layer for MIMO

1. Define MIMO Parameters: Include attributes for the amount of transmit and receive antennas.

phy.h:

class PHY : public Handler {

public:

// Existing members

int num_tx_antennas;

int num_rx_antennas;

// Methods to set antennas

void SetNumTxAntennas(int n) { num_tx_antennas = n; }

void SetNumRxAntennas(int n) { num_rx_antennas = n; }

// Override modulation method

virtual void Modulate(Packet *p) = 0;

private:

// Existing members

};

1. Implement MIMO Modulation: Manage the multiple data streams by modifying the modulate techniques.

phy.cc:

void PHY::Modulate(Packet *p) {

// Example MIMO modulation

for(int i=0; i<num_tx_antennas; i++) {

// Modulate each data stream for each transmit antenna

// Placeholder code

std::cout << “Modulating data stream ” << i+1 << ” on TX antenna ” << i+1 << std::endl;

}

}

1. Update OTcl Script for MIMO Configuration:

Example:

# Create nodes

set node1 [$ns node]

set node2 [$ns node]

# Define PHY with MIMO

set mimo_phy [new Phy/MIMOPhy]

$mimo_phy set num_tx_antennas_ 2

$mimo_phy set num_rx_antennas_ 2

# Assign PHY to nodes

$node1 set phy_ $mimo_phy

$node2 set phy_ $mimo_phy

# Define duplex link with MIMO PHY

$ns duplex-link $node1 $node2 10Mb 10ms DropTail

# Rest of the script…

1. Recompile NS2:

cd ns-allinone-2.35/ns-2.35

make clean

make

8. Testing and Validation

After implementing the Physical Layer enhancements, it’s necessary to authenticate them to make certain they act as predicted.

8.1. Create a Test OTcl Script

Design a simplified OTcl script to investigate the new Physical Layer features like modulation and error rates.

Example OTcl Script:

# Create a Simulator object

set ns [new Simulator]

set nf [open out.nam w]

$ns namtrace-all $nf

# Create nodes

set node1 [$ns node]

set node2 [$ns node]

# Define the QAM PHY

set qam_phy [new Phy/QAMModulator]

$qam_phy set modulation_order_ 16

$node1 set phy_ $qam_phy

$node2 set phy_ $qam_phy

# Define duplex link with QAM PHY

$ns duplex-link $node1 $node2 10Mb 10ms DropTail

# Define traffic (e.g., FTP)

set ftp [new Application/FTP]

$ftp attach-agent [$ns node-agent $node1]

set sink [new Agent/Sink]

$ns attach-agent $node2 $sink

$ns connect $ftp $sink

# Start the FTP transfer at time 1.0

$ns at 1.0 “start $ftp”

# End the simulation at time 10.0

$ns at 10.0 “finish”

proc finish {} {

global ns nf

$ns flush-trace

close $nf

exit 0

}

$ns run

8.2. Run the Simulation

Execute the OTcl script to examine the Physical Layer.

ns test_physical_layer.tcl

8.3. Analyze the Output

• NAM (Network Animator): Visualize the simulation to see packet transmissions and Physical Layer activities.

nam out.nam

• Trace Files: Assess metrics like BER, SNR, packet loss, throughput, etc by inspecting trace files.
• Console Output: Verify the console for debug statements from your C++ classes (such as modulation messages).

9. Further Enhancements

After the execution, consider the following enhancements to maximize the simulation’s realism and difficulty:

9.1. Incorporate Fading Models

Accomplish models like Rayleigh or Rician fading to imitate multipath impacts.

Example:

double LogDistanceChannel::CalculatePathLoss(double distance) {

// Existing path loss

double pl = reference_path_loss + 10 * path_loss_exponent * log10(distance / reference_distance);

// Add Rayleigh fading

double fading = sqrt(-2.0 * log(((double)rand()) / RAND_MAX)) * cos(2 * M_PI * ((double)rand()) / RAND_MAX);

pl += fading;

return pl;

}

9.2. Dynamic Spectrum Allocation

Replicate dynamic distribution of frequency bands to various nodes or services, optimizing spectrum efficiency.

9.3. Energy Consumption Models

Model the energy utilization of devices, particularly related for battery-powered nodes in wireless networks.

9.4. Integration with Higher Layers

Make certain effortless incorporation with MAC and Network Layers to replicate end-to-end communication accurately.

9.5. Implement Realistic Antenna Patterns

Model directional antennas, antenna acquires, and beamforming methods for more precise signal propagation.

At the end of the given procedure, you have seen the brief demonstration of Network Physical Layer Communication with its implementation and extensions or modifications using ns2 tool. Also, we provide more details regarding this layer through another manual.

Our team consists of top developers who are ready to assist you with your project. If you need help implementing Network Physical Layer Communication using the NS2 tool, our experts are here to provide you with valuable insights into your network performance.