How to Calculate Network Achievable sum rate in NS2

To implement the Network Achievable sum rate in ns2 signifies the extreme data rate which a network can assist, given specific constraints like bandwidth, power and intrusion. In wireless communication systems, it is commonly measured by counting the data rates of all users in the assumption of optimal resource allocation. It is vital for analysing network performance and efficiency, particularly in multi-user or multi-cell environments.

To measure the achievable sum rate in NS2, you need to consider factors like signal-to-noise ratio (SNR), channel bandwidth, and modulation schemes for each user. It is usually calculated using Shannon’s capacity formula, which states the maximum data rate that can be done under ideal conditions:

Achievable Data Rate (bps)=B×log⁡2(1+SNR)\text{Achievable Data Rate (bps)} = B \times \log_2(1 + \text{SNR})Achievable Data Rate (bps)=B×log2(1+SNR)

Where:

B is the bandwidth in Hz.
SNR is the signal-to-noise ratio for the communication link.

The achievable sum rate is the total of the single data rates for all users in the network or within a particular cell.

Steps to Calculate Network Achievable Sum Rate in NS2

Model the Wireless Network

In NS2, model your wireless network with several users (UEs) and base stations. Each user interacts with the base station, and the achievable sum rate will based on the SNR and bandwidth of each user’s link.

Example Setup for Wireless Network in NS2:

# Define the bandwidth (in Hz) available for each user

set bandwidth 20e6 ;# 20 MHz = 20e6 Hz

# Define base station and user nodes (UEs)

set bs1 [$ns node] ;# Base station for cell 1

set ue1_1 [$ns node] ;# UE 1 in cell 1

set ue1_2 [$ns node] ;# UE 2 in cell 1

# Set up wireless links

$ns wireless-link $ue1_1 $bs1 54Mb 10ms

$ns wireless-link $ue1_2 $bs1 54Mb 10ms

Here, the base station (bs1) serves multiple users (UEs). The achievable data rate for each user depends on their respective SNR and bandwidth.

Calculate Signal-to-Noise Ratio (SNR)

Estimate the SNR for each user by using predefined value or compute it in terms of the network conditions (transmission power, path loss, noise, etc.). The SNR is commonly calculated as:

SNR (linear)=Received PowerNoise Power\text{SNR (linear)} = \frac{\text{Received Power}}{\text{Noise Power}}SNR (linear)=Noise PowerReceived Power

The SNR in decibels (dB) is:

SNR (dB)=10×log⁡10(Received PowerNoise Power)\text{SNR (dB)} = 10 \times \log_{10} \left( \frac{\text{Received Power}}{\text{Noise Power}} \right)SNR (dB)=10×log10(Noise PowerReceived Power)

You can set up a function in NS2 to measure the SNR for each user based on its distance from the base station and the noise level.

Example SNR Calculation:

# Function to compute SNR (assuming transmission power, path loss, and noise)

proc calculate_snr {tx_power path_loss noise_power} {

# SNR (linear scale) = Received power / Noise power

set snr [expr $tx_power / ($path_loss * $noise_power)]

return $snr

}

# Example usage

set tx_power 1.0 ;# Transmission power in Watts

set path_loss 0.5 ;# Path loss factor

set noise_power 1e-9 ;# Noise power in Watts

set snr_ue1 [calculate_snr $tx_power $path_loss $noise_power]

puts “SNR for UE 1: $snr_ue1”

In this sample:

tx_power is the transmission power.
path_loss is the path loss factor according to the distance amongst the user and the base station.
noise_power is the power of the noise.

Calculate Achievable Data Rate for Each User

Once you have the SNR for each user, you can compute the achievable data rate using the Shannon capacity formula:

Achievable Rate (bps)=B×log⁡2(1+SNR)\text{Achievable Rate (bps)} = B \times \log_2(1 + \text{SNR})Achievable Rate (bps)=B×log2(1+SNR)

TCL Function to Calculate Achievable Rate:

# Function to calculate achievable data rate using Shannon’s formula

proc calculate_achievable_rate {bandwidth snr} {

set rate [expr $bandwidth * log(1 + $snr) / log(2)] ;# log base 2

return $rate

}

# Example usage

set achievable_rate_ue1 [calculate_achievable_rate $bandwidth $snr_ue1]

puts “Achievable Data Rate for UE 1: $achievable_rate_ue1 bps”

This function estimates the achievable data rate for a given user based on its SNR and the existed bandwidth.

Calculate Achievable Sum Rate for Each Cell

The achievable sum rate for each cell is the count of the achievable data rates for all users inside the cell.

TCL Script to Calculate Achievable Sum Rate:

# Assume SNR values have been computed for each UE

set snr_ue1 10 ;# SNR for UE 1

set snr_ue2 8 ;# SNR for UE 2

# Calculate the achievable data rate for each UE

set rate_ue1 [calculate_achievable_rate $bandwidth $snr_ue1]

set rate_ue2 [calculate_achievable_rate $bandwidth $snr_ue2]

# Calculate the sum rate for the cell

set sum_rate [expr $rate_ue1 + $rate_ue2]

puts “Achievable Sum Rate for Cell 1: $sum_rate bps”

This script:

Calculates the achievable data rate for each user depend on their SNR and bandwidth.
Amounts the data rates for all users in the cell to calculate the achievable sum rate.

Log Achievable Data Rates and Sum Rate to a File

You can log the achievable data rates and sum rate to a file for further analysis or visualization.

Example of Logging Achievable Data Rates:

# Open a log file

set logfile [open achievable_sum_rate_log.txt w]

# Log the individual and sum rates

puts $logfile “Achievable Data Rate for UE 1: $rate_ue1 bps”

puts $logfile “Achievable Data Rate for UE 2: $rate_ue2 bps”

puts $logfile “Achievable Sum Rate for Cell 1: $sum_rate bps”

# Close the file

close $logfile

This will store the achievable data rates and the sum rate for each cell to a text file for further analysis.

Analyze Achievable Sum Rate Over Time

If you want to assess how the achievable sum rate evolves over time, you can compute it occasionally during the simulation and log it at regular breaks.

TCL Script to Log Achievable Sum Rate Over Time:

# Function to log the achievable sum rate over time

proc log_achievable_sum_rate {time_interval} {

global ns logfile rate_ue1 rate_ue2

# Calculate sum rate

set sum_rate [expr $rate_ue1 + $rate_ue2]

# Log the sum rate at the current simulation time

puts $logfile “Time: [$ns now], Achievable Sum Rate: $sum_rate bps”

# Re-schedule this function to run after the time interval

$ns at [expr [$ns now] + $time_interval] “log_achievable_sum_rate $time_interval”

}

# Start logging the sum rate every 10 seconds

$ns at 0.0 “log_achievable_sum_rate 10”

This will log the achievable sum rate every 10 seconds during the simulation, granting you to assess how the rates vary over time.

By following this structured process, you can calculate the network achievable sum rate in ns2 and also get to know about how to model the wireless networks. If needed, we will offer any additional details regarding this sum rate.

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