dsss-error-rate-model.cc

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/*
 * Copyright (c) 2010 The Boeing Company
 *
 * 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
 *
 * Author: Gary Pei <guangyu.pei@boeing.com>
 */
 
#include "dsss-error-rate-model.h"
 
#include "ns3/log.h"
 
#include <cmath>
 
namespace ns3
{
 
NS_LOG_COMPONENT_DEFINE("DsssErrorRateModel");
 
#ifndef HAVE_GSL
const double DsssErrorRateModel::WLAN_SIR_PERFECT = 10.0;
const double DsssErrorRateModel::WLAN_SIR_IMPOSSIBLE = 0.1;
#endif
 
double
DsssErrorRateModel::DqpskFunction(double x)
{
    NS_LOG_FUNCTION_NOARGS();
    return ((std::sqrt(2.0) + 1.0) / std::sqrt(8.0 * M_PI * std::sqrt(2.0))) *
           (1.0 / std::sqrt(x)) * std::exp(-(2.0 - std::sqrt(2.0)) * x);
}
 
double
DsssErrorRateModel::GetDsssDbpskSuccessRate(double sinr, uint64_t nbits)
{
    NS_LOG_FUNCTION_NOARGS();
    double EbN0 = sinr * 22000000.0 / 1000000.0; // 1 bit per symbol with 1 MSPS
    double ber = 0.5 * std::exp(-EbN0);
    return std::pow((1.0 - ber), static_cast<double>(nbits));
}
 
double
DsssErrorRateModel::GetDsssDqpskSuccessRate(double sinr, uint64_t nbits)
{
    NS_LOG_FUNCTION_NOARGS();
    double EbN0 = sinr * 22000000.0 / 1000000.0 / 2.0; // 2 bits per symbol, 1 MSPS
    double ber = DqpskFunction(EbN0);
    return std::pow((1.0 - ber), static_cast<double>(nbits));
}
 
double
DsssErrorRateModel::GetDsssDqpskCck5_5SuccessRate(double sinr, uint64_t nbits)
{
    NS_LOG_FUNCTION_NOARGS();
#ifdef HAVE_GSL
    // symbol error probability
    double EbN0 = sinr * 22000000.0 / 1375000.0 / 4.0;
    double sep = SymbolErrorProb16Cck(4.0 * EbN0 / 2.0);
    return std::min(1.0, std::pow(1.0 - sep, nbits / 4.0));
#else
    NS_LOG_WARN("Running a 802.11b CCK Matlab model less accurate than GSL model");
    // The Matlab model
    double ber;
    if (sinr > WLAN_SIR_PERFECT)
    {
        ber = 0.0;
    }
    else if (sinr < WLAN_SIR_IMPOSSIBLE)
    {
        ber = 0.5;
    }
    else
    {
        // fitprops.coeff from Matlab berfit
        double a1 = 5.3681634344056195e-001;
        double a2 = 3.3092430025608586e-003;
        double a3 = 4.1654372361004000e-001;
        double a4 = 1.0288981434358866e+000;
        ber = a1 * std::exp(-std::pow((sinr - a2) / a3, a4));
    }
    return std::min(1.0, std::pow((1.0 - ber), static_cast<double>(nbits)));
#endif
}
 
double
DsssErrorRateModel::GetDsssDqpskCck11SuccessRate(double sinr, uint64_t nbits)
{
    NS_LOG_FUNCTION_NOARGS();
#ifdef HAVE_GSL
    NS_LOG_DEBUG("GSL enabled ");
    // symbol error probability
    double EbN0 = sinr * 22000000.0 / 1375000.0 / 8.0;
    double sep = SymbolErrorProb256Cck(8.0 * EbN0 / 2.0);
    return std::min(1.0, std::pow(1.0 - sep, nbits / 8.0));
#else
    NS_LOG_WARN("Running a 802.11b CCK Matlab model less accurate than GSL model");
    // The Matlab model
    double ber;
    if (sinr > WLAN_SIR_PERFECT)
    {
        ber = 0.0;
    }
    else if (sinr < WLAN_SIR_IMPOSSIBLE)
    {
        ber = 0.5;
    }
    else
    {
        // fitprops.coeff from Matlab berfit
        double a1 = 7.9056742265333456e-003;
        double a2 = -1.8397449399176360e-001;
        double a3 = 1.0740689468707241e+000;
        double a4 = 1.0523316904502553e+000;
        double a5 = 3.0552298746496687e-001;
        double a6 = 2.2032715128698435e+000;
        ber = (a1 * sinr * sinr + a2 * sinr + a3) /
              (sinr * sinr * sinr + a4 * sinr * sinr + a5 * sinr + a6);
    }
    return std::min(1.0, std::pow((1.0 - ber), static_cast<double>(nbits)));
#endif
}
 
#ifdef HAVE_GSL
double
IntegralFunction(double x, void* params)
{
    double beta = ((FunctionParameters*)params)->beta;
    double n = ((FunctionParameters*)params)->n;
    double IntegralFunction = std::pow(2 * gsl_cdf_ugaussian_P(x + beta) - 1, n - 1) *
                              std::exp(-x * x / 2.0) / std::sqrt(2.0 * M_PI);
    return IntegralFunction;
}
 
double
DsssErrorRateModel::SymbolErrorProb16Cck(double e2)
{
    double sep;
    double error;
 
    FunctionParameters params;
    params.beta = std::sqrt(2.0 * e2);
    params.n = 8.0;
 
    gsl_integration_workspace* w = gsl_integration_workspace_alloc(1000);
 
    gsl_function F;
    F.function = &IntegralFunction;
    F.params = &params;
 
    gsl_integration_qagiu(&F, -params.beta, 0, 1e-7, 1000, w, &sep, &error);
    gsl_integration_workspace_free(w);
    if (error == 0.0)
    {
        sep = 1.0;
    }
 
    return 1.0 - sep;
}
 
double
DsssErrorRateModel::SymbolErrorProb256Cck(double e1)
{
    return 1.0 - std::pow(1.0 - SymbolErrorProb16Cck(e1 / 2.0), 2.0);
}
 
#endif
 
} // namespace ns3