How to Implement Network Blockage mitigation in OMNeT++

To implement the network blockage mitigation in OMNeT++, we have to include mimicking situations where obstacles block the communication path among nodes, leading to signal degradation or loss. To overwhelm this, we can execute strategies like rerouting, the use of relays to maintain communication or beamforming adjustments. Blockage mitigation is specifically related in high-frequency wireless networks like mmWave, where signals are extremely vulnerable to physical obstructions.

Given below is a step-by-step procedure to executing network blockage mitigation in OMNeT++ using the INET framework:

Step-by-Step Implementations:

1. Set Up OMNeT++ and INET Framework:

• Install OMNeT++: Make sure OMNeT++ is installed and configured on the system.
• Install INET Framework: Download and install the INET framework, which delivers models for wireless communication, containing channel models and obstacle simulations.

2. Define the Network Topology:

Make a network topology where nodes communicate with each other, and familiarise obstacles that could cause blockage.

Example NED File (BlockageNetwork.ned):

package mynetwork;

import inet.node.inet.StandardHost;

import inet.node.inet.AccessPoint;

import inet.environment.object.Obstacle;

network BlockageNetwork

{

parameters:

int numObstacles = default(2); // Number of obstacles

submodules:

baseStation: AccessPoint {

@display(“p=500,500”);

}

mobileNode: StandardHost {

@display(“p=300,300”);

}

obstacle[numObstacles]: Obstacle {

@display(“p=400,400”);

}

}

In this example:

• baseStation: Denotes a fixed node, like a 5G base station.
• mobileNode: Signifies a mobile node that may encounter blockages.
• obstacle[]: Represents physical objects that can block the signal path.

3. Configure Obstacle Models:

Use the INET framework’s obstacle models to mimic blockages. These models can attenuate or block signals completely, depending on their properties and the occurrence of the signal.

Example Configuration in omnetpp.ini:

[General]

network = BlockageNetwork

**.obstacle[*].shape = “box”

**.obstacle[*].sizeX = 100m

**.obstacle[*].sizeY = 50m

**.obstacle[*].material = “concrete”  # Material affects signal attenuation

**.obstacle[*].placementZ = 10m  # Elevation of the obstacle

4. Implement Blockage Detection and Mitigation:

The mobile node wants to identify when a blockage happens and mitigate its effects. This could include switching to a various communication path, modifying the beam direction, or increasing transmission power.

Example: Basic Blockage Detection and Rerouting (C++)

#include “inet/common/INETDefs.h”

#include “inet/physicallayer/contract/packetlevel/IRadio.h”

#include “inet/physicallayer/analogmodel/packetlevel/ScalarTransmission.h”

#include “inet/environment/contract/IPhysicalEnvironment.h”

Define_Module(MobileNode);

void MobileNode::initialize() {

currentPath = 1;  // Assume path 1 is the default

scheduleAt(simTime(), blockageCheckTimer);  // Start blockage detection

}

void MobileNode::handleMessage(cMessage *msg) {

if (msg == blockageCheckTimer) {

checkForBlockage();

scheduleAt(simTime() + checkInterval, blockageCheckTimer);  // Periodically check for blockage

} else {

// Handle other messages (e.g., packets)

// …

}

}

void MobileNode::checkForBlockage() {

// Check the signal quality or presence of obstacles

double signalStrength = measureSignalStrength();

if (signalStrength < signalThreshold) {

EV << “Blockage detected, initiating mitigation\n”;

mitigateBlockage();

}

}

void MobileNode::mitigateBlockage() {

// Simple mitigation by rerouting

if (currentPath == 1) {

EV << “Switching to alternative path 2\n”;

currentPath = 2;  // Switch to an alternative path

// Adjust antenna or change routing path

} else {

EV << “Switching to alternative path 1\n”;

currentPath = 1;  // Switch back to the original path

}

adjustBeamDirection();

}

void MobileNode::adjustBeamDirection() {

// Adjust the beam direction to avoid blockage

auto antenna = check_and_cast<SteerableAntenna*>(getParentModule()->getSubmodule(“wlan”)->getSubmodule(“radio”)->getSubmodule(“antenna”));

antenna->setOrientation(newAzimuth, newElevation);

 

EV << “Antenna adjusted to new direction to avoid blockage\n”;

}

double MobileNode::measureSignalStrength() {

// Placeholder for actual signal strength measurement

return uniform(0, 1);  // Random value for this example

}

In this example:

• checkForBlockage(): Periodically verifies if the signal strength drops below a threshold, specifying a blockage.
• mitigateBlockage(): Switches to an another communication path or modifies the beam direction to avoid the obstacle.

5. Simulate and Monitor Blockage Mitigation:

Run the simulation and monitor how the network manages blockages. Display the metrics like signal strength, packet delivery success, and the time taken to reroute or adjust the beam.

Example Configuration for Monitoring Metrics:

[General]

network = BlockageNetwork

**.mobileNode.app[0].signalStrength.recordScalar = true

**.mobileNode.app[0].reroutingTime.recordScalar = true

This configuration records the signal strength and the time taken to reroute or modify the beam direction.

6. Analyse and Optimize the Mitigation Process:

Examine the results to determine the efficiency of the blockage mitigation strategy, after running the simulation. Consider factors like:

• Rerouting time: How quickly the network adapts to blockages.
• Signal recovery: The development in signal strength after mitigation.
• Impact on communication: The effect of blockages and mitigation on packet delivery and complete communication quality.

7. Extend the Blockage Mitigation Strategy:

We can improve the elementary blockage mitigation strategy with extra features like:

• Predictive Mitigation: Use machine learning or historical data to guess blockages and pre-emptively modify the communication path.
• Multi-hop Relays: Set up relay nodes to bypass obstacles when direct communication is blocked.
• Adaptive Beamforming: Endlessly modify the beam direction in real-time based on feedback from signal quality measurements.

Example: Predictive Mitigation

void MobileNode::predictAndMitigateBlockage() {

// Use historical data or machine learning to predict a blockage

if (predictBlockage()) {

EV << “Blockage predicted, preemptively adjusting path\n”;

mitigateBlockage();

}

}

bool MobileNode::predictBlockage() {

// Placeholder for predictive algorithm

return uniform(0, 1) < 0.2;  // 20% chance of predicting a blockage

}

8. Document and Report Findings:

After finishing the simulations, document the blockage mitigation strategies verified, the results obtained, and any optimizations made. It will support in understanding how efficiently the network can manage blockages and maintain communication quality.

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