Files
unison/examples/wireless/wifi-error-models-comparison.cc
2022-10-14 14:13:12 +00:00

190 lines
6.4 KiB
C++

/*
* Copyright (c) 2020 University of Washington
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License version 2 as
* published by the Free Software Foundation;
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
* Authors: Sébastien Deronne <sebastien.deronne@gmail.com>
* Rohan Patidar <rpatidar@uw.edu>
*/
// This example is to show difference among Nist, Yans and Table-based error rate models.
//
// It outputs plots of the Frame Error Rate versus the Signal-to-noise ratio for
// Nist, Yans and Table-based error rate models and for MCS 0, 4 and 7 value.
#include "ns3/command-line.h"
#include "ns3/gnuplot.h"
#include "ns3/nist-error-rate-model.h"
#include "ns3/table-based-error-rate-model.h"
#include "ns3/wifi-tx-vector.h"
#include "ns3/yans-error-rate-model.h"
#include <cmath>
#include <fstream>
using namespace ns3;
int
main(int argc, char* argv[])
{
uint32_t size = 1500 * 8; // bits
bool tableErrorModelEnabled = true;
bool yansErrorModelEnabled = true;
bool nistErrorModelEnabled = true;
uint8_t beginMcs = 0;
uint8_t endMcs = 7;
uint8_t stepMcs = 4;
std::string format("Ht");
CommandLine cmd(__FILE__);
cmd.AddValue("size", "The size in bits", size);
cmd.AddValue("frameFormat", "The frame format to use: Ht, Vht or He", format);
cmd.AddValue("beginMcs", "The first MCS to test", beginMcs);
cmd.AddValue("endMcs", "The last MCS to test", endMcs);
cmd.AddValue("stepMcs", "The step between two MCSs to test", stepMcs);
cmd.AddValue("includeTableErrorModel",
"Flag to include/exclude Table-based error model",
tableErrorModelEnabled);
cmd.AddValue("includeYansErrorModel",
"Flag to include/exclude Yans error model",
yansErrorModelEnabled);
cmd.AddValue("includeNistErrorModel",
"Flag to include/exclude Nist error model",
nistErrorModelEnabled);
cmd.Parse(argc, argv);
std::ofstream errormodelfile("wifi-error-rate-models.plt");
Gnuplot plot = Gnuplot("wifi-error-rate-models.eps");
Ptr<YansErrorRateModel> yans = CreateObject<YansErrorRateModel>();
Ptr<NistErrorRateModel> nist = CreateObject<NistErrorRateModel>();
Ptr<TableBasedErrorRateModel> table = CreateObject<TableBasedErrorRateModel>();
WifiTxVector txVector;
std::vector<std::string> modes;
std::stringstream mode;
mode << format << "Mcs" << +beginMcs;
modes.push_back(mode.str());
for (uint8_t mcs = (beginMcs + stepMcs); mcs < endMcs; mcs += stepMcs)
{
mode.str("");
mode << format << "Mcs" << +mcs;
modes.push_back(mode.str());
}
mode.str("");
mode << format << "Mcs" << +endMcs;
modes.push_back(mode.str());
for (uint32_t i = 0; i < modes.size(); i++)
{
std::cout << modes[i] << std::endl;
Gnuplot2dDataset yansdataset(modes[i]);
Gnuplot2dDataset nistdataset(modes[i]);
Gnuplot2dDataset tabledataset(modes[i]);
txVector.SetMode(modes[i]);
for (double snr = -5.0; snr <= (endMcs * 5); snr += 0.1)
{
double ps = yans->GetChunkSuccessRate(WifiMode(modes[i]),
txVector,
std::pow(10.0, snr / 10.0),
size);
if (ps < 0 || ps > 1)
{
// error
exit(1);
}
yansdataset.Add(snr, 1 - ps);
ps = nist->GetChunkSuccessRate(WifiMode(modes[i]),
txVector,
std::pow(10.0, snr / 10.0),
size);
if (ps < 0 || ps > 1)
{
// error
exit(1);
}
nistdataset.Add(snr, 1 - ps);
ps = table->GetChunkSuccessRate(WifiMode(modes[i]),
txVector,
std::pow(10.0, snr / 10.0),
size);
if (ps < 0 || ps > 1)
{
// error
exit(1);
}
tabledataset.Add(snr, 1 - ps);
}
if (tableErrorModelEnabled)
{
std::stringstream ss;
ss << "Table-" << modes[i];
tabledataset.SetTitle(ss.str());
plot.AddDataset(tabledataset);
}
if (yansErrorModelEnabled)
{
std::stringstream ss;
ss << "Yans-" << modes[i];
yansdataset.SetTitle(ss.str());
plot.AddDataset(yansdataset);
}
if (nistErrorModelEnabled)
{
std::stringstream ss;
ss << "Nist-" << modes[i];
nistdataset.SetTitle(ss.str());
plot.AddDataset(nistdataset);
}
}
plot.SetTerminal("postscript eps color enh \"Times-BoldItalic\"");
plot.SetLegend("SNR(dB)", "Frame Error Rate");
std::stringstream plotExtra;
plotExtra << "set xrange [-5:" << endMcs * 5 << "]\n\
set log y\n\
set yrange [0.0001:1]\n";
uint8_t lineNumber = 1;
for (uint32_t i = 0; i < modes.size(); i++)
{
if (tableErrorModelEnabled)
{
plotExtra << "set style line " << +lineNumber++
<< " linewidth 5 linecolor rgb \"red\" \n";
}
if (yansErrorModelEnabled)
{
plotExtra << "set style line " << +lineNumber++
<< " linewidth 5 linecolor rgb \"green\" \n";
}
if (nistErrorModelEnabled)
{
plotExtra << "set style line " << +lineNumber++
<< " linewidth 5 linecolor rgb \"blue\" \n";
}
}
plotExtra << "set style increment user";
plot.SetExtra(plotExtra.str());
plot.GenerateOutput(errormodelfile);
errormodelfile.close();
return 0;
}