How to Implement Network Channel Equalization in NS2

To implement the Network Channel Equalization in ns2, we have to simulate an interaction system where signal distortion due to the channel is amended or compensated for utilizing the equalization strategies. Since NS2 doesn’t directly support physical-layer signal processing tasks such as channel equalization out of box , we have to expand their mechanisms to replicate the impacts of channel equalization at a higher abstraction level (like link-layer or application-layer) or model the influence of equalization on packet delivery, delay or error rates.

Here in the following below, we offered the steps to implement this using ns2 tool:

What is Channel Equalization?

In wireless communication systems, channel equalization reimburses for the distortion triggered by the transmission medium (like multipath fading, intrusion, noise). The intent is to reverse the impacts of the channel to enhance the quality of signal reception.

Key Concepts for Simulating Channel Equalization:

  1. Signal Distortion and Noise: The channel launches noise, fading, or interfering, which affects packet transmission.
  2. Error Models: You can use error models in NS2 to replicate packet errors caused by channel distortion.
  3. Equalization Simulation: Equalization can be modeled by altering the error model or optimizing packet delivery rates when equalization is accomplished.

Steps to Implement Network Channel Equalization in NS2

  1. Install NS2

Make certain that you have installed and configured the ns2 on your system properly.

  1. Set Up the Basic Network Topology

Start by defining a simple wireless network topology with nodes, where packets are transferred over a channel that launches errors due to distortion.

Example: Simulating Network Channel with Errors

# Define a simulator object

set ns [new Simulator]

# Define trace and nam files for output

set tracefile [open out.tr w]

set namfile [open out.nam w]

$ns trace-all $tracefile

$ns namtrace-all $namfile

# Define a ‘finish’ procedure to end the simulation and visualize in NAM

proc finish {} {

global ns tracefile namfile

$ns flush-trace

close $tracefile

close $namfile

exec nam out.nam &

exit 0

}

# Set up the topography for the simulation area

set topo [new Topography]

$topo load_flatgrid 1000 1000

# Define the wireless channel

set chan [new Channel/WirelessChannel]

# Create two mobile nodes (representing devices communicating over the channel)

set node1 [$ns node]

set node2 [$ns node]

# Set node positions

$node1 set X_ 200

$node1 set Y_ 200

$node1 set Z_ 0

$node2 set X_ 800

$node2 set Y_ 800

$node2 set Z_ 0

# Set up a duplex wireless link between the nodes

$ns duplex-link $node1 $node2 2Mb 10ms DropTail

# Introduce an error model to simulate channel distortion (without equalization)

# Error model (uniform error distribution)

set em [new ErrorModel]

$em unit packet

$em set rate_ 0.1  ;# 10% packet error rate (simulate channel distortion)

$ns lossmodel $em $node1 $node2

# Define TCP traffic from node1 to node2

set tcp [new Agent/TCP]

set sink [new Agent/TCPSink]

$ns attach-agent $node1 $tcp

$ns attach-agent $node2 $sink

$ns connect $tcp $sink

# Create FTP traffic over TCP to simulate data transfer

set ftp [new Application/FTP]

$ftp attach-agent $tcp

$ftp start 1.0

$ftp stop 5.0

# Schedule the end of the simulation

$ns at 6.0 “finish”

# Run the simulation

$ns run

  1. Explanation of the Script
  • Nodes and Links: Two mobile nodes (node1 and node2) are generated with a wireless channel amongst them.
  • Error Model: An error model is established to replicate a 10% packet error rate caused by channel distortion (without equalization).
  • Traffic: TCP traffic is built among the nodes over the lossy channel to imitate the influence of errors on data transmission.
  • Loss Model: The error model impacts packet delivery amidst the two nodes by erratically dropping packets in terms of the error rate.
  1. Simulate the Effect of Channel Equalization

Establish the corrective mechanisms that enhance packet delivery rates or minimize the error rate to replicate the impact of channel equalization.

Implementing “Equalization” in the Simulation:

  • Without Equalization: The error rate in the channel is high (like 10% packet loss).
  • With Equalization: The error model is adjusted to decrease the error rate, simulating the effect of equalization optimizing the channel’s performance.

Example: Applying Channel Equalization

# Simulate the same setup but with reduced errors due to equalization

# Introduce a second error model with a lower error rate (representing equalization)

set em_equalized [new ErrorModel]

$em_equalized unit packet

$em_equalized set rate_ 0.02  ;# 2% packet error rate (simulating equalization)

$ns lossmodel $em_equalized $node1 $node2

# Re-run the simulation with equalization applied

$ns run

  1. Compare Performance Before and After Equalization

Compute the influence of channel equalization by comparing the performance metrics of the network before and after establishing equalization:

Key Metrics to Measure:

  • Throughput: Analyze the trace file to estimate the throughput with and without equalization and to monitor how many packets were successfully provided.
  • Packet Loss: Compare the packet loss before and after equalization by computing the total amount of lost packets.
  • End-to-End Delay: Measure the delay in packet transmission, as equalization may minimize packet retransmissions, thereby enhancing delay performance.

Example AWK Script to Measure Packet Loss

Here’s an AWK script that sums the total number of dropped packets (because of errors) in the trace file:

awk ‘{

if ($1 == “d” && $4 == “AGT” && $7 == “tcp”) {

dropped_packets++

}

}

END {

print “Total Dropped Packets: ” dropped_packets

}’ out.tr

This script will print the total count of dropped packets during the simulation. Compare the performance by executing this script on the trace file with and without equalization.

  1. Simulate Adaptive Equalization (Advanced)

You can expand the equalization simulation by dynamically modifying the error rate depends on the channel conditions. This simulates an adaptive equalization scheme where the equalizer reacts to differences in the channel.

Example: Adaptive Equalization Based on Channel Conditions

# Procedure to simulate adaptive equalization based on network conditions

proc adaptive_equalization {time node1 node2} {

global ns em_equalized

# Get the current simulation time

set current_time [$ns now]

# Simulate channel condition: periodically reduce error rate (improve equalization)

if { $current_time > $time } {

puts “Applying adaptive equalization…”

$em_equalized set rate_ [expr 0.02 – 0.01 * rand()]  ;# Random reduction in error rate

$ns at [expr $current_time + 1.0] “adaptive_equalization [expr $time + 1] $node1 $node2”

}

}

# Schedule adaptive equalization during the simulation

$ns at 1.0 “adaptive_equalization 1.0 $node1 $node2”

# Run the simulation with adaptive equalization

$ns run

In conclusion, you can improve your knowledge towards the implementation of Network Channel Equalization using the ns2 tool and containing how to analyze the results, how to extend the features in order to optimize it. Nevertheless, we can also offer you any details regarding this manual.

Ns2project.com help you in implementation by providing outcomes in Network Channel Equalization using the ns2 tool. We offer innovative concepts and project support. Our expertise encompasses both link-layer and application-layer aspects relevant to your projects.