How to Calculate Network Bit Error Rate in NS2

To calculate the Network Bit Error Rate (BER) in NS2 refers to the ratio of incorrect bits of the total amount of transferred bits through communication channel. It is a crucial parameter for assessing the quality and dependability of the network, certainly when simulating wireless or noisy environments where bit errors are more likely to happen.

We can measure it by evaluating packet errors, the packet size in bits and total amount of transmitted packets due to ns2 can’t directly compute BER during the simulation. Here’s how to calculate the Bit Error Rate (BER) in NS2 using different strategies.

Steps to Calculate Network Bit Error Rate (BER) in NS2

  1. Simulate Network with Error Models

We can launch the error models in ns2 that randomly drop or corrupt packets to simulate and measure Bit Error Rate (BER). Here’s an example of introducing an ErrorModel in NS2 to simulate bit errors:

# Define an error model with a certain error rate

set loss_module [new ErrorModel]

$loss_module set rate_ 1e-5  ;# Bit error rate of 1e-5 (0.00001)

$loss_module unit bit         ;# Error applied at the bit level

$loss_module ranvar [new RandomVariable/Uniform]

# Attach the error model to a link between two nodes

$ns lossmodel $loss_module $node(0) $node(1)

This error model presents a bit error rate of 1e-5, meaning 1 error in every 100,000 bits transmitted amongst node(0) and node(1).

  1. Generate Trace File

Make sure that your NS2 simulation is designed to create a trace file to log the packet transmission, reception, and drop events. This will help you assess packet losses or errors, which are vital for measuring BER.

set tracefile [open out.tr w]

$ns trace-all $tracefile

The trace file will log events like:

  • +: Packet sent.
  • r: Packet received.
  • d: Packet dropped (due to errors, congestion, etc.).
  1. Identify Dropped or Corrupted Packets

You can infer bit errors from packet drops or corruptions in the trace file. Dropped packets are denoted by a d in the trace file, which may signify bit-level errors (for example: because of interference, noise, etc.).

Example trace file line:

d 0.34567 1 0 tcp 1040 ——- [0 1 0 0] ——- [0:0 1:0 32 0] [0] 0 0

Here:

  • d: Packet drop (which could indicate errors).
  • 0.34567: Time of the event.
  • 1040: Packet size in bytes (important for calculating BER).
  1. Calculate Packet Error Rate (PER)

To measure BER, you can first calculate the Packet Error Rate (PER), which is the ratio of dropped packets to the total amount of sent packets. This is a good starting point for estimating bit errors.

You can calculate PER using an AWK script:

awk ‘{

if ($1 == “+” && $4 == “tcp”) {

sent_packets++;

}

if ($1 == “d” && $4 == “tcp”) {

dropped_packets++;

}

} END {

if (sent_packets > 0) {

per = dropped_packets / sent_packets;

print “Packet Error Rate (PER): ” per;

} else {

print “No packets were sent.”;

}

}’ out.tr

This script:

  • Sums the amount of packets sent (sent_packets).
  • Counts the total of packets dropped (dropped_packets).
  • Computes the Packet Error Rate (PER).
  1. Estimate Bit Error Rate (BER) from PER

After calculating PER, you can estimate BER by considering the packet size (in bits). For each dropped packet, we assume that at least one bit was in error.

The relationship between PER and BER for a packet size of N bits is approximately:

BER≈PERN\text{BER} \approx \frac{\text{PER}}{N}BER≈NPER​

Where:

  • PER is the Packet Error Rate.
  • N is the number of bits in a packet (e.g., 1040 bytes = 8320 bits).

AWK Script to Estimate BER:

awk ‘{

if ($1 == “+” && $4 == “tcp”) {

sent_packets++;

}

if ($1 == “d” && $4 == “tcp”) {

dropped_packets++;

}

} END {

if (sent_packets > 0) {

per = dropped_packets / sent_packets;

packet_size_bits = 1040 * 8;  # Assuming each packet is 1040 bytes (8320 bits)

ber = per / packet_size_bits;

print “Estimated Bit Error Rate (BER): ” ber;

} else {

print “No packets were sent.”;

}

}’ out.tr

This script computes:

  • PER (as in the previous step).
  • BER using the relationship between PER and the packet size (in bits).
  1. Analyze Results

After running the AWK script, you’ll get an estimated Bit Error Rate (BER) in terms of the packet drops and packet size. If BER is lower, the more consistent the network. A high BER represents more errors in bit transmission, which might need retransmissions or error correction mechanisms.

  1. Simulate Different BER Scenarios

You can imitate various bit error rates by modifying the ErrorModel parameters in your NS2 simulation. For instance, to replicate a higher BER (more bit errors), you can maximize the error rate in the model:

$loss_module set rate_ 1e-4  ;# Higher BER (1 in every 10000 bits will be erroneous)

Execute the simulation again and monitor how increasing the BER impacts packet drops, latency, and throughput in the network.

  1. BER for Wireless Networks

In wireless networks, bit errors are more often because of intrusion, fading, and noise. You can develop a wireless network simulation in NS2 and apply ErrorModels to replicate various BERs.

Here’s how you might configure a wireless network with error models:

# Define wireless parameters

set val(chan)           Channel/WirelessChannel    ;# Wireless channel

set val(prop)           Propagation/TwoRayGround   ;# Propagation model

set val(netif)          Phy/WirelessPhy            ;# Wireless PHY layer

set val(mac)            Mac/802_11                 ;# MAC layer

# Create error model for wireless link

set wireless_error_model [new ErrorModel]

$wireless_error_model set rate_ 1e-5  ;# BER of 1e-5 for wireless network

$wireless_error_model unit bit

$ns lossmodel $wireless_error_model $node(0) $node(1)

Wireless networks commonly experience variable bit error rates, so simulating and assessing BER under various conditions can help inpect the robustness of the network.

This demonstration will help you with the calculation of Bit Error Rate (BER) in the network using ns2 simulator and it also provides the formula that will be used in the calculation. If needed, we will walk you through another calculation.

Please send us your parameter details, and we will compare them to give you an analysis of your project’s networking. We can also help you calculate the Network Bit Error Rate using the NS2 tool to get the best results.