128 lines
4.2 KiB
C++
128 lines
4.2 KiB
C++
/*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License version 2 as
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* published by the Free Software Foundation;
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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*
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* Author: Sébastien Deronne <sebastien.deronne@gmail.com>
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*/
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// This example is used to validate error rate models for DSSS rates.
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//
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// It outputs plots of the Frame Success Rate versus the Signal-to-noise ratio
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// for the DSSS error rate models and for every DSSS mode.
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#include "ns3/command-line.h"
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#include "ns3/gnuplot.h"
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#include "ns3/nist-error-rate-model.h"
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#include "ns3/table-based-error-rate-model.h"
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#include "ns3/wifi-tx-vector.h"
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#include "ns3/yans-error-rate-model.h"
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#include <cmath>
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#include <fstream>
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using namespace ns3;
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int
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main(int argc, char* argv[])
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{
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uint32_t FrameSize = 1500; // bytes
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std::ofstream file("frame-success-rate-dsss.plt");
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const std::vector<std::string> modes{
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"DsssRate1Mbps",
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"DsssRate2Mbps",
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"DsssRate5_5Mbps",
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"DsssRate11Mbps",
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};
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CommandLine cmd(__FILE__);
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cmd.AddValue("FrameSize", "The frame size in bytes", FrameSize);
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cmd.Parse(argc, argv);
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Gnuplot plot = Gnuplot("frame-success-rate-dsss.eps");
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Ptr<YansErrorRateModel> yans = CreateObject<YansErrorRateModel>();
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Ptr<NistErrorRateModel> nist = CreateObject<NistErrorRateModel>();
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Ptr<TableBasedErrorRateModel> table = CreateObject<TableBasedErrorRateModel>();
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WifiTxVector txVector;
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for (uint32_t i = 0; i < modes.size(); i++)
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{
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std::cout << modes[i] << std::endl;
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Gnuplot2dDataset dataset(modes[i]);
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txVector.SetMode(modes[i]);
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for (double snr = -10.0; snr <= 20.0; snr += 0.1)
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{
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double psYans = yans->GetChunkSuccessRate(WifiMode(modes[i]),
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txVector,
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std::pow(10.0, snr / 10.0),
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FrameSize * 8);
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if (psYans < 0.0 || psYans > 1.0)
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{
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// error
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exit(1);
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}
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double psNist = nist->GetChunkSuccessRate(WifiMode(modes[i]),
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txVector,
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std::pow(10.0, snr / 10.0),
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FrameSize * 8);
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if (psNist < 0.0 || psNist > 1.0)
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{
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std::cout << psNist << std::endl;
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// error
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exit(1);
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}
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if (psNist != psYans)
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{
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exit(1);
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}
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double psTable = table->GetChunkSuccessRate(WifiMode(modes[i]),
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txVector,
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std::pow(10.0, snr / 10.0),
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FrameSize * 8);
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if (psTable < 0.0 || psTable > 1.0)
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{
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std::cout << psTable << std::endl;
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// error
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exit(1);
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}
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if (psTable != psYans)
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{
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exit(1);
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}
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dataset.Add(snr, psYans);
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}
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plot.AddDataset(dataset);
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}
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plot.SetTerminal("postscript eps color enh \"Times-BoldItalic\"");
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plot.SetLegend("SNR(dB)", "Frame Success Rate");
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plot.SetExtra("set xrange [-10:20]\n\
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set yrange [0:1.2]\n\
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set style line 1 linewidth 5\n\
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set style line 2 linewidth 5\n\
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set style line 3 linewidth 5\n\
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set style line 4 linewidth 5\n\
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set style line 5 linewidth 5\n\
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set style line 6 linewidth 5\n\
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set style line 7 linewidth 5\n\
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set style line 8 linewidth 5\n\
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set style increment user");
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plot.GenerateOutput(file);
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file.close();
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return 0;
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}
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