How to Implement Network Spectral Efficiency in NS2

To implement Network Spectral Efficiency in NS2 has needs to concentrate on evaluating the throughput across a given bandwidth for a wireless communication network. Spectral efficiency usually measured in bits/s/Hz is critical parameters in wireless networks by way of it reflect how effectively the spectrum is utilized.

Here is a guide on how implement network spectral efficiency in NS2:

Step-by-Step Implementation:

  1. Understand the Key Components

Spectral efficiency is calculated as:

Spectral Efficiency=Throughput (bits/sec)Bandwidth (Hz)\text{Spectral Efficiency} = \frac{\text{Throughput (bits/sec)}}{\text{Bandwidth (Hz)}}Spectral Efficiency=Bandwidth (Hz)Throughput (bits/sec)​

  • Throughput: The actual data rate achieved in the network.
  • Bandwidth: The allocated bandwidth for the communication.
  1. Set up the NS2 Environment

Make sure that we have NS2 installed and configured for wireless network simulations. Wireless channel settings, propagation models, and bandwidth allocation are vital for computing spectral efficiency.

  1. Create a Basic TCL Script for Wireless Network Simulation

We can generate a basic wireless network in NS2 and assess the throughput to estimate spectral efficiency. Below is an example TCL script:

# Create a new NS2 simulator object

set ns [new Simulator]

# Define trace file and output for NAM visualization

set tracefile [open spectral_efficiency.tr w]

$ns trace-all $tracefile

set namfile [open spectral_efficiency.nam w]

$ns namtrace-all $namfile

# Define the topology parameters

set x_dim 500

set y_dim 500

set num_nodes 5

set bandwidth 10e6  ;# 10 MHz bandwidth

# Define topography object

set topo [new Topography]

$topo load_flatgrid $x_dim $y_dim

# Define wireless channel and propagation model

set chan [new Channel/WirelessChannel]

set prop [new Propagation/TwoRayGround]

set netif [new Phy/WirelessPhy]

set mac [new Mac/802_11]

set ll [new LL]

set ant [new Antenna/OmniAntenna]

set ifq [new Queue/DropTail/PriQueue]

set ifqlen 50

# Configure nodes to use AODV routing protocol

$ns node-config -adhocRouting AODV \

-llType $ll \

-macType $mac \

-ifqType $ifq \

-ifqLen $ifqlen \

-antType $ant \

-propType $prop \

-phyType $netif \

-channelType $chan \

-topoInstance $topo \

-agentTrace ON \

-routerTrace ON \

-macTrace ON

# Create nodes (devices)

for {set i 0} {$i < $num_nodes} {incr i} {

set node($i) [$ns node]

}

# Set initial node positions (static)

$node(0) set X_ 50

$node(0) set Y_ 50

$node(0) set Z_ 0

$node(1) set X_ 150

$node(1) set Y_ 150

$node(1) set Z_ 0

# Set up traffic between nodes

set tcp [new Agent/TCP]

set sink [new Agent/TCPSink]

$ns attach-agent $node(0) $tcp

$ns attach-agent $node(1) $sink

$ns connect $tcp $sink

# FTP application to generate traffic

set ftp [new Application/FTP]

$ftp attach-agent $tcp

$ftp start

# Simulation end time

$ns at 10.0 “finish”

# Finish procedure

proc finish {} {

global ns tracefile namfile

$ns flush-trace

close $tracefile

close $namfile

exec nam spectral_efficiency.nam &

exit 0

}

# Run the simulation

$ns run

  1. Explanation of Key Components
  • Wireless Nodes: The script describes 5 nodes with wireless communication among them. They are statically placed in this sample, nevertheless mobility can also be added for more realistic scenarios.
  • Bandwidth: The wireless network uses a 10 MHz bandwidth, defined as bandwidth 10e6.
  • Traffic: A TCP connection among two nodes is used to create traffic. FTP is attached to the TCP agent to mimic file transfer.
  1. Measure Throughput

In NS2, we can extract throughput from the trace file (spectral_efficiency.tr) by evaluating the number of bits transmitted over a particular period.

Here is a procedure to calculate throughput from the trace file:

  1. Extract Transmission Events: Use tools such as grep or custom scripts to filter tcp packets sent and received.
    • For example, use grep to find the lines in which packets are successfully delivered to the sink:

bash

Copy code

grep -o “tcp” spectral_efficiency.tr | wc -l

  1. Calculate Throughput: Throughput is estimated using the following formula:

Throughput=Total received bitsSimulation time\text{Throughput} = \frac{\text{Total received bits}}{\text{Simulation time}}Throughput=Simulation timeTotal received bits​

The total received bits can be estimated by multiplying the number of packets received by the packet size (in bits).

  1. Calculate Spectral Efficiency

Once the throughput is estimated, we can calculate spectral efficiency using the formula:

Spectral Efficiency=Throughput (bits/sec)Bandwidth (Hz)\text{Spectral Efficiency} = \frac{\text{Throughput (bits/sec)}}{\text{Bandwidth (Hz)}}Spectral Efficiency=Bandwidth (Hz)Throughput (bits/sec)​

Example Calculation:

Let’s take on the following:

  • Total packets received: 500
  • Each packet size: 512 bytes (4096 bits)
  • Simulation time: 10 seconds
  • Bandwidth: 10 MHz

Step-by-Step:

  1. Total Bits Transmitted: Total Bits=500×4096=2048000 bits\text{Total Bits} = 500 \times 4096 = 2048000 \text{ bits}Total Bits=500×4096=2048000 bits
  2. Throughput: Throughput=204800010=204800 bits/sec\text{Throughput} = \frac{2048000}{10} = 204800 \text{ bits/sec}Throughput=102048000​=204800 bits/sec
  3. Spectral Efficiency: Spectral Efficiency=204800107=0.02048 bits/sec/Hz\text{Spectral Efficiency} = \frac{204800}{10^7} = 0.02048 \text{ bits/sec/Hz}Spectral Efficiency=107204800​=0.02048 bits/sec/Hz
  1. Automate the Calculation (Optional)

We can automate the calculation of throughput and spectral efficiency by composing a post-processing script in Python, AWK, or other scripting languages. The script should:

  • Parse the trace file.
  • Calculate the number of packets received.
  • Compute throughput and spectral efficiency.

Here’s a basic Python script outline for parsing a trace file:

# Simple Python script to calculate throughput and spectral efficiency

def calculate_spectral_efficiency(trace_file, bandwidth, simulation_time):

total_bits = 0

packet_size_bits = 512 * 8  # Assuming 512 bytes per packet

# Open and parse the trace file

with open(trace_file, ‘r’) as file:

for line in file:

if “tcp” in line and “r” in line:  # Assuming “r” marks packet received

total_bits += packet_size_bits

# Calculate throughput (bits per second)

throughput = total_bits / simulation_time

# Calculate spectral efficiency (bits/sec/Hz)

spectral_efficiency = throughput / bandwidth

return spectral_efficiency

# Example usage

bandwidth = 10e6  # 10 MHz

simulation_time = 10  # 10 seconds

trace_file = “spectral_efficiency.tr”

spectral_efficiency = calculate_spectral_efficiency(trace_file, bandwidth, simulation_time)

print(f”Spectral Efficiency: {spectral_efficiency} bits/sec/Hz”)

  1. Advanced Considerations
  • Channel Modeling: Include more realistic channel models like Rayleigh, Rician to see on how diverse environments effects spectral efficiency.
  • Traffic Patterns: Validate with different traffic types (CBR, UDP) and different application loads.
  • Mobility: Add node mobility to replicate real-world scenarios in which devices move around that could impacts the spectral efficiency because dynamic changes in throughput.
  1. Run the Simulation

Save TCL script as spectral_efficiency.tcl and executed it using:

ns spectral_efficiency.tcl

Then, measure the created trace file to calculate throughput and spectral efficiency.In the above procedures were very helpful to implement the spectral efficiency over the network using the ns2 simulation tool and also we provide the more information about the spectral efficiency.

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