To implement the Network Inter-Symbol Interference (ISI) mitigation in ns3, we have to reduce or eliminate the effects of ISI to do so we have to simulate the communication system. Because of the multipath propagation, ISI usually takes place in wireless communication in which the signals take various routes to reach the server as the result causes overlapping of symbols.
ISI can implement with the detailed signal processing. However in ns3, we cannot simply simulate the physical layer effects like ISI. So, we use models and its method to emulate its impact and also explain their mitigation strategies includes equalization or error correction.
Below, we provide the step-by-step implementation to create a basic simulation that includes ISI emulation and mitigation:
Step-by-Step Implementation:
Step 1: Setup ns3 Environment
Make sure that ns3 is installed in your computer and verify its configuration.
git clone https://gitlab.com/nsnam/ns-3-dev.git
cd ns-3-dev
./waf configure
./waf build
Step 2: Create the Network ISI Mitigation Simulation Script
After installation, we have to create a script that helps to set up a wireless network which imitates ISI with the help of an error model and executes the mitigation strategy. Below we will provide an sample of the creation for your reference.
#include “ns3/core-module.h”
#include “ns3/network-module.h”
#include “ns3/internet-module.h”
#include “ns3/point-to-point-module.h”
#include “ns3/mobility-module.h”
#include “ns3/applications-module.h”
#include “ns3/wifi-module.h”
#include “ns3/error-model.h”
#include “ns3/flow-monitor-module.h”
using namespace ns3;
NS_LOG_COMPONENT_DEFINE(“NetworkISIMitigationExample”);
class IsiErrorModel : public ErrorModel
{
public:
static TypeId GetTypeId(void)
{
static TypeId tid = TypeId(“ns3::IsiErrorModel”)
.SetParent<ErrorModel>()
.SetGroupName(“Network”)
.AddConstructor<IsiErrorModel>()
.AddAttribute(“ErrorRate”,
“The rate of errors (0.0 to 1.0) due to ISI”,
DoubleValue(0.05),
MakeDoubleAccessor(&IsiErrorModel::m_errorRate),
MakeDoubleChecker<double>());
return tid;
}
IsiErrorModel() : m_errorRate(0.05) {}
private:
virtual bool DoCorrupt(Ptr<Packet> p)
{
return (m_errorRate > 0 && (UniformVariable().GetValue() < m_errorRate));
}
virtual void DoReset(void) {}
double m_errorRate;
};
class IsiMitigationApplication : public Application
{
public:
IsiMitigationApplication() {}
virtual ~IsiMitigationApplication() {}
void Setup(Ptr<Socket> socket, Address address, uint32_t packetSize, uint32_t nPackets, Time interPacketInterval)
{
m_socket = socket;
m_peer = address;
m_packetSize = packetSize;
m_nPackets = nPackets;
m_interPacketInterval = interPacketInterval;
m_packetsSent = 0;
}
protected:
virtual void StartApplication(void)
{
m_socket->Bind();
m_socket->Connect(m_peer);
SendPacket();
}
virtual void StopApplication(void)
{
if (m_socket)
{
m_socket->Close();
}
}
private:
void SendPacket()
{
Ptr<Packet> packet = Create<Packet>(m_packetSize);
m_socket->Send(packet);
if (++m_packetsSent < m_nPackets)
{
Simulator::Schedule(m_interPacketInterval, &IsiMitigationApplication::SendPacket, this);
}
}
Ptr<Socket> m_socket;
Address m_peer;
uint32_t m_packetSize;
uint32_t m_nPackets;
Time m_interPacketInterval;
uint32_t m_packetsSent;
};
int main(int argc, char *argv[])
{
CommandLine cmd;
cmd.Parse(argc, argv);
// Create nodes
NodeContainer nodes;
nodes.Create(10); // Ten nodes in total
// Set up mobility model
MobilityHelper mobility;
mobility.SetPositionAllocator(“ns3::GridPositionAllocator”,
“MinX”, DoubleValue(0.0),
“MinY”, DoubleValue(0.0),
“DeltaX”, DoubleValue(10.0),
“DeltaY”, DoubleValue(10.0),
“GridWidth”, UintegerValue(5),
“LayoutType”, StringValue(“RowFirst”));
mobility.SetMobilityModel(“ns3::ConstantPositionMobilityModel”);
mobility.Install(nodes);
// Set up WiFi
WifiHelper wifi;
wifi.SetRemoteStationManager(“ns3::AarfWifiManager”);
WifiMacHelper mac;
Ssid ssid = Ssid(“ns-3-ssid”);
mac.SetType(“ns3::StaWifiMac”,
“Ssid”, SsidValue(ssid),
“ActiveProbing”, BooleanValue(false));
YansWifiPhyHelper phy = YansWifiPhyHelper::Default();
YansWifiChannelHelper channel = YansWifiChannelHelper::Default();
phy.SetChannel(channel.Create());
NetDeviceContainer devices = wifi.Install(phy, mac, nodes);
mac.SetType(“ns3::ApWifiMac”,
“Ssid”, SsidValue(ssid));
NetDeviceContainer apDevices = wifi.Install(phy, mac, nodes.Get(0));
// Apply ISI error model to emulate ISI effects
Ptr<IsiErrorModel> errorModel = CreateObject<IsiErrorModel>();
errorModel->SetAttribute(“ErrorRate”, DoubleValue(0.10)); // Example error rate for ISI
devices.Get(1)->SetAttribute(“ReceiveErrorModel”, PointerValue(errorModel));
// Install the internet stack
InternetStackHelper stack;
stack.Install(nodes);
// Assign IP addresses
Ipv4AddressHelper address;
address.SetBase(“10.1.1.0”, “255.255.255.0”);
Ipv4InterfaceContainer interfaces = address.Assign(devices);
address.Assign(apDevices);
// Install applications to generate traffic
uint16_t port = 9;
OnOffHelper onoff(“ns3::UdpSocketFactory”, Address(InetSocketAddress(interfaces.GetAddress(1), port)));
onoff.SetConstantRate(DataRate(“1Mbps”));
ApplicationContainer apps = onoff.Install(nodes.Get(0));
apps.Start(Seconds(1.0));
apps.Stop(Seconds(10.0));
PacketSinkHelper sink(“ns3::UdpSocketFactory”, Address(InetSocketAddress(Ipv4Address::GetAny(), port)));
apps = sink.Install(nodes.Get(1));
apps.Start(Seconds(0.0));
apps.Stop(Seconds(10.0));
// Enable FlowMonitor to measure performance metrics
FlowMonitorHelper flowmon;
Ptr<FlowMonitor> monitor = flowmon.InstallAll();
// Run the simulation
Simulator::Stop(Seconds(15.0));
Simulator::Run();
// Print per-flow statistics
monitor->CheckForLostPackets();
Ptr<Ipv4FlowClassifier> classifier = DynamicCast<Ipv4FlowClassifier>(flowmon.GetClassifier());
std::map<FlowId, FlowMonitor::FlowStats> stats = monitor->GetFlowStats();
for (std::map<FlowId, FlowMonitor::FlowStats>::const_iterator i = stats.begin(); i != stats.end(); ++i)
{
Ipv4FlowClassifier::FiveTuple t = classifier->FindFlow(i->first);
NS_LOG_UNCOND(“Flow ” << i->first << ” (” << t.sourceAddress << ” -> ” << t.destinationAddress << “)”);
NS_LOG_UNCOND(” Tx Packets: ” << i->second.txPackets);
NS_LOG_UNCOND(” Tx Bytes: ” << i->second.txBytes);
NS_LOG_UNCOND(” Rx Packets: ” << i->second.rxPackets);
NS_LOG_UNCOND(” Rx Bytes: ” << i->second.rxBytes);
NS_LOG_UNCOND(” Lost Packets: ” << i->second.lostPackets);
NS_LOG_UNCOND(” Throughput: ” << i->second.rxBytes * 8.0 / (i->second.timeLastRxPacket.GetSeconds() – i->second.timeFirstTxPacket.GetSeconds()) / 1024 / 1024 << ” Mbps”);
}
// Clean up
Simulator::Destroy();
return 0;
}
Step 3: Compile and Run the Simulation
- Compile the Simulation:
./waf configure –enable-examples
./waf build
Run the Simulation:
./waf –run scratch/network-isi-mitigation-example
Step 4: Analyze Results
Once we complete the compilation and running process, to emulate the effects of ISI we have to simulate the script sets up a network topology contains nodes and applies an error model. While we simulating the impact of ISI, the error model presents a specific error rate to the received packets. With the help of FlowMonitor, we can aggregate and print out statistics about the traffic flows like packet loss, throughput, and delay.
Additional Considerations
We can also expand the functionalities of the network ISI mitigation simulation. Take a look at the following below:
1. Advanced Error Models
For the betterment of the emulated effects of ISI that contains the models and their multipath propagation and their channel delay spreads, we have executes more complex error models.
2. Equalization Techniques
To moderate the ISI at the receiver, we have to simulate equalization techniques includes Zero-Forcing (ZF), Minimum Mean Square Error (MMSE), or Decision Feedback Equalization (DFE).
3. Channel Models
To simulate the effects of the wireless environment on ISI, we have to incorporate the realistic channel model that holds responsibilities for factors like fading, shadowing, and path loss.
4. Adaptive Modulation and Coding
As per the requirements of the channel conditions, we have to moderate the impact of ISI by executing the adaptive modulation and coding schemes.
5. Performance Metrics
Next, we have to accumulate and analyze additional metrics such as bit error rate (BER), symbol error rate (SER), and signal-to-noise ratio (SNR) to evaluate the performance of the ISI mitigation techniques.
6. Real-World Scenarios
To examine the efficiency of the ISI mitigation approaches in real world application, we have to simulate real-world scenarios like cellular networks, IoT deployments, or vehicular networks.
In conclusion, we provided the implementation process of the network ISI mitigation in ns3. Depends on your need we can also offer any additional details with implementation support and project performance of ISI mitigation and ns3.