How to Implement Visual MIMO in NS2

To implement Visual MIMO (Multiple Input Multiple Output) in NS2 has needs to mimic a communication system in which multiple optical or visual channels are used to transmit and receive data. The Visual MIMO is usually used in visible light communication (VLC) or optical wireless communication systems in which the light is the carrier of information. This type of interaction can be used in scenarios such as smart lighting or indoor communication systems.

Since NS2 is primarily built for radio frequency (RF)-based communication networks, we can mimic Visual MIMO by approaching the optical wireless channels and modifying existing wireless network models to reflect the unique features of Visual MIMO systems.

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Here is a brief procedure on how to implement Visual MIMO in ns2:

Steps to Implement Visual MIMO in NS2

  1. Set up the NS2 Environment

Make sure that NS2 is installed on the system. We will also need a simple understanding of how NS2 is mimics wireless networks. Since NS2 doesn’t natively support visible light communication (VLC) or optical channels, we can estimate it using a customized wireless channel with particular properties such as diminish range and higher throughput (to simulate line-of-sight communication for optical systems).

  1. Create a TCL Script for Visual MIMO

Below is an instance of a TCL script that mimics a Visual MIMO communication system using optical channel. This script undertakes multiple transmitters and receivers using optical wireless communication.

Example TCL Script for Visual MIMO in NS2:

# Create a new NS2 simulator

set ns [new Simulator]

# Open trace and NAM output files

set tracefile [open visual_mimo.tr w]

$ns trace-all $tracefile

set namfile [open visual_mimo.nam w]

$ns namtrace-all $namfile

# Define the optical wireless channel and propagation model

set val(chan)   Channel/WirelessChannel   ;# Optical wireless channel (using wireless)

set val(prop)   Propagation/TwoRayGround  ;# Optical propagation (approximation)

set val(ant)    Antenna/OmniAntenna;# Omni-directional antenna (optical beam approximation)

set val(netif)  Phy/WirelessPhy;# Physical layer for optical wireless

set val(mac)    Mac/802_11;# MAC layer (modified for optical communication)

set val(ifq)    Queue/DropTail/PriQueue

set val(ifqlen) 50;# Queue length

set val(ll)     LL

set val(rp)     AODV ;# Ad-hoc On-demand Distance Vector routing protocol

set val(x)      500;# X dimension of the simulation area (meters)

set val(y)      500;# Y dimension of the simulation area (meters)

# Topology setup for Visual MIMO system

set topo [new Topography]

$topo load_flatgrid $val(x) $val(y)

# Optical wireless channel parameters

set val(txPower) 0.2          ;# Transmission power (W)

set val(rxPower) 0.1          ;# Reception power (W)

set val(idlePower) 0.01       ;# Idle power (W)

set val(initialEnergy) 100.0  ;# Initial energy at each node

set val(range) 200            ;# Reduced range for optical communication (meters)

# Configure node properties for optical wireless nodes

$ns node-config -adhocRouting $val(rp) \

-llType $val(ll) \

-macType $val(mac) \

-ifqType $val(ifq) \

-ifqLen $val(ifqlen) \

-antType $val(ant) \

-propType $val(prop) \

-phyType $val(netif) \

-channelType $val(chan) \

-topoInstance $topo \

-energyModel EnergyModel \

-initialEnergy $val(initialEnergy) \

-txPower $val(txPower) \

-rxPower $val(rxPower) \

-idlePower $val(idlePower) \

-agentTrace ON \

-routerTrace ON \

-macTrace ON

# Create multiple nodes (representing the MIMO transmitters and receivers)

set tx0 [$ns node]  ;# Transmitter 0

set tx1 [$ns node]  ;# Transmitter 1

set rx0 [$ns node]  ;# Receiver 0

set rx1 [$ns node]  ;# Receiver 1

# Set initial positions for the Visual MIMO transmitters and receivers

$tx0 set X_ 100

$tx0 set Y_ 150

$tx0 set Z_ 0   ;# 2D plane

$tx1 set X_ 150

$tx1 set Y_ 150

$tx1 set Z_ 0

$rx0 set X_ 300

$rx0 set Y_ 300

$rx0 set Z_ 0

$rx1 set X_ 350

$rx1 set Y_ 300

$rx1 set Z_ 0

# Configure communication between multiple transmitters and receivers

# First flow: TX0 -> RX0 (single input single output)

set udp0 [new Agent/UDP]

$ns attach-agent $tx0 $udp0

set null0 [new Agent/Null]

$ns attach-agent $rx0 $null0

$ns connect $udp0 $null0

# Second flow: TX1 -> RX1 (single input single output)

set udp1 [new Agent/UDP]

$ns attach-agent $tx1 $udp1

set null1 [new Agent/Null]

$ns attach-agent $rx1 $null1

$ns connect $udp1 $null1

# Create Constant Bit Rate (CBR) traffic for both communication links

set cbr0 [new Application/Traffic/CBR]

$cbr0 set packetSize_ 1000        ;# Packet size 1000 bytes

$cbr0 set rate_ 2Mb               ;# Optical wireless communication (higher rate)

$cbr0 attach-agent $udp0

set cbr1 [new Application/Traffic/CBR]

$cbr1 set packetSize_ 1000

$cbr1 set rate_ 2Mb

$cbr1 attach-agent $udp1

# Schedule the start and stop of traffic

$ns at 1.0 “$cbr0 start”

$ns at 1.5 “$cbr1 start”

$ns at 9.0 “$cbr0 stop”

$ns at 9.5 “$cbr1 stop”

# End the simulation at 10 seconds

$ns at 10.0 “finish”

# Finish procedure to close the simulation

proc finish {} {

global ns tracefile namfile

$ns flush-trace

close $tracefile

close $namfile

exec nam visual_mimo.nam &

exit 0

}

# Run the simulation

$ns run

  1. Explanation of Key Components
  • Nodes: We describe four nodes that denotes MIMO transmitters (tx0, tx1) and MIMO receivers (rx0, rx1).
  • Optical Wireless Channel: The script uses an 802.11-based wireless channel to estimate an optical wireless system. The transmission range is set lower (200 meters) to reflect the line-of-sight (LoS) nature of visible light communication.
  • CBR Traffic: Constant Bit Rate (CBR) traffic is created to mimic the data communication among the transmitters and receivers, with a higher transmission rate (2 Mbps) to reflect the higher capacity of optical communication systems.
  • Visual MIMO Communication: Two independent interaction flows are configuring among the MIMO transmitters and receivers that mimics Single Input Single Output (SISO) channels. In real Visual MIMO, this can be expanded to Multiple Input Multiple Output (MIMO) scenarios.
  1. Run the Simulation

Save the script as visual_mimo.tcl and execute it using NS2:

ns visual_mimo.tcl

After the simulation is done, we can envision the communication using NAM:

nam visual_mimo.nam

  1. Analyse the Simulation

We can evaluate the trace file (visual_mimo.tr) to observe the performance of the Visual MIMO communication system. Some are the parameters to focus on include:

  • Throughput: Assess on how much data was successfully transmitted among the MIMO transmitters and receivers.
  • Packet Loss: verify for any packet loss because interference or capacity limits of the optical channels.
  • Delay: Monitor the delay among transmissions and receptions that is vial in real-time communication systems.

Example: Analyze Throughput

To estimate throughput, we can use an AWK script to process the trace file and extract the number of bytes transmitted:

awk ‘/^r/ && /udp/ {sum+=$5} END {print “Throughput: “, sum/10, “bytes/sec”}’ visual_mimo.tr

  1. Extend the Simulation

Here are some ways to expand the simple Visual MIMO simulation:

  1. a) Multiple Input Multiple Output (MIMO)

To mimic more advanced MIMO configurations by adding more transmitters and receivers and defining complex traffic flows. For instance:

# Multiple input, multiple output traffic flows

set udp2 [new Agent/UDP]

$ns attach-agent $tx0 $udp2

$ns connect $udp2 $null1   ;# TX0 communicates with RX1

set cbr2 [new Application/Traffic/CBR]

$cbr2 set packetSize_ 1000

$cbr2 set rate_ 2Mb

$cbr2 attach-agent $udp2

$ns at 2.0 “$cbr2 start”

$ns at 9.0 “$cbr2 stop”

  1. b) Mobility for Optical Transceivers

To mimic mobile transceivers, like drones or vehicles using Visual MIMO for communication. We can use the setdest command to move the nodes during the simulation:

# Add mobility for tx0 (MIMO transmitter)

$ns at 3.0 “$tx0 setdest 400 400 10”  ;# Move tx0 to (400, 400) at 10 m/s

  1. c) Quality of Service (QoS)

To mimic Quality of Service (QoS) mechanisms to prioritize traffic in Visual MIMO systems. We can execute the priority queues or use different scheduling techniques to manage multiple data streams.

  1. d) Channel Interference and Noise

We can add an error model to mimic the effect of interference or noise in the Visual MIMO system:

set loss_model [new ErrorModel]

$loss_model set rate_ 0.01   ;# 1% packet loss

$ns lossmodel $loss_model $tx0 $rx0

This technique will help you to understand how to setup the simulation and how to execute the Visual MIMO in ns2 tool and also we deliver the explanation, advanced features and sample snippets were given. If you need more details about the Visual MIMO we will provide it.