/* -*- Mode: C++; c-file-style: "gnu"; indent-tabs-mode:nil; -*- */
/*
* Copyright (c) 2005,2006,2007 INRIA
*
* 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: Mathieu Lacage <mathieu.lacage@sophia.inria.fr>
*/
#include "propagation-loss-model.h"
#include "ns3/default-value.h"
#include "ns3/random-variable-default-value.h"
#include "ns3/log.h"
#include "ns3/mobility-model.h"
#include "ns3/static-mobility-model.h"
#include <math.h>
NS_LOG_COMPONENT_DEFINE ("PropagationLossModel");
namespace ns3 {
enum ModelType {
FRIIS,
RANDOM,
LOG_DISTANCE
};
static EnumDefaultValue<enum ModelType> g_modelType
("PropagationLossModelType",
"The type of propagation loss model.",
LOG_DISTANCE, "LogDistance",
FRIIS, "Friis",
RANDOM, "Random",
0, (void *)0);
static NumericDefaultValue<double> g_friisLambda
("FriisPropagationLossLambda",
"The wavelength to use by default for every FriisPropagationLossModel (default is 5.15 GHz at 300 000 km/s).",
300000000.0 / 5.150e9);
static NumericDefaultValue<double> g_friisSystemLoss
("FriisPropagationLossSystemLoss",
"The system loss to use by default for every FriisPropagationLossModel",
1.0);
static NumericDefaultValue<double> g_friisPropagationLossMinDistance
("FriisPropagationLossMinDistance",
"The distance under which the propagation model refuses to give results (m)",
0.5);
static RandomVariableDefaultValue g_random
("RandomPropagationLossDistribution",
"The distribution (in dbm) to choose the propagation loss.",
"Constant:1.0");
static NumericDefaultValue<double> g_logDistanceExponent
("LogDistancePropagationLossExponent",
"The exponent of the Path Loss propagation model",
3.0);
static NumericDefaultValue<double> g_logDistanceReferenceDistance
("LogDistancePropagationLossReferenceDistance",
"The distance at which the reference loss is calculated (m)",
1.0);
static EnumDefaultValue<enum ModelType> g_logDistanceReferenceType
("LogDistancePropagationLossReferenceType",
"The type of reference propagation model.",
FRIIS, "Friis",
RANDOM, "Random",
0, (void *)0);
const double FriisPropagationLossModel::PI = 3.1415;
PropagationLossModel::~PropagationLossModel ()
{}
Ptr<PropagationLossModel>
PropagationLossModel::CreateDefault (void)
{
switch (g_modelType.GetValue ()) {
case FRIIS:
return Create<FriisPropagationLossModel> ();
break;
case RANDOM:
return Create<RandomPropagationLossModel> ();
break;
case LOG_DISTANCE:
return Create<LogDistancePropagationLossModel> ();
break;
default:
NS_ASSERT (false);
return 0;
break;
}
}
RandomPropagationLossModel::RandomPropagationLossModel ()
: m_variable (g_random.GetCopy ())
{}
RandomPropagationLossModel::RandomPropagationLossModel (const RandomVariable &variable)
: m_variable (variable.Copy ())
{}
RandomPropagationLossModel::~RandomPropagationLossModel ()
{
delete m_variable;
}
double
RandomPropagationLossModel::GetRxPower (double txPowerDbm,
Ptr<MobilityModel> a,
Ptr<MobilityModel> b) const
{
double rxPower = txPowerDbm - m_variable->GetValue ();
NS_LOG_DEBUG ("tx power="<<txPowerDbm<<"dbm, rx power="<<rxPower<<"Dbm");
return rxPower;
}
FriisPropagationLossModel::FriisPropagationLossModel ()
: m_lambda (g_friisLambda.GetValue ()),
m_systemLoss (g_friisSystemLoss.GetValue ()),
m_minDistance (g_friisPropagationLossMinDistance.GetValue ())
{}
void
FriisPropagationLossModel::SetSystemLoss (double systemLoss)
{
m_systemLoss = systemLoss;
}
double
FriisPropagationLossModel::GetSystemLoss (void) const
{
return m_systemLoss;
}
void
FriisPropagationLossModel::SetLambda (double frequency, double speed)
{
m_lambda = speed / frequency;
}
void
FriisPropagationLossModel::SetLambda (double lambda)
{
m_lambda = lambda;
}
double
FriisPropagationLossModel::GetLambda (void) const
{
return m_lambda;
}
double
FriisPropagationLossModel::DbmToW (double dbm) const
{
double mw = pow(10.0,dbm/10.0);
return mw / 1000.0;
}
double
FriisPropagationLossModel::DbmFromW (double w) const
{
double dbm = log10 (w * 1000.0) * 10.0;
return dbm;
}
double
FriisPropagationLossModel::GetRxPower (double txPowerDbm,
Ptr<MobilityModel> a,
Ptr<MobilityModel> b) const
{
/*
* Friis free space equation:
* where Pt, Gr, Gr and P are in Watt units
* L is in meter units.
*
* Pt * Gt * Gr * (lambda^2)
* P = --------------------------
* (4 * pi * d)^2 * L
*
* Gt: tx gain (W)
* Gr: rx gain (W)
* Pt: tx power (W)
* d: distance (m)
* L: system loss
* lambda: wavelength (m)
*
* Here, we ignore tx and rx gain and the input and output values
* are in dbm
* So, the formula looks like this:
*
* 10 lambda^2
* rx = tx + ------- * ln (-------------------)
* ln (10) (4 * pi * d)^2 * L
*
* rx: rx power (dbm)
* tx: tx power (dbm)
* d: distance (m)
* L: system loss
* lambda: wavelength (m)
*/
double distance = a->GetDistanceFrom (b);
if (distance <= m_minDistance)
{
return txPowerDbm;
}
double numerator = m_lambda * m_lambda;
double denominator = 16 * PI * PI * distance * distance * m_systemLoss;
double pr = log (numerator / denominator) * 10 / log (10);
double rxPowerDbm = txPowerDbm + pr;
NS_LOG_DEBUG ("distance="<<distance<<"m, tx power="<<txPowerDbm<<"dbm, rx power="<<rxPowerDbm<<"dbm");
return rxPowerDbm;
}
LogDistancePropagationLossModel::LogDistancePropagationLossModel ()
: m_exponent (g_logDistanceExponent.GetValue ()),
m_referenceDistance (g_logDistanceReferenceDistance.GetValue ()),
m_reference (CreateDefaultReference ())
{}
void
LogDistancePropagationLossModel::SetPathLossExponent (double n)
{
m_exponent = n;
}
void
LogDistancePropagationLossModel::SetReferenceDistance (double referenceDistance)
{
m_referenceDistance = referenceDistance;
}
void
LogDistancePropagationLossModel::SetReferenceModel (Ptr<PropagationLossModel> model)
{
m_reference = model;
}
double
LogDistancePropagationLossModel::GetPathLossExponent (void) const
{
return m_exponent;
}
Ptr<PropagationLossModel>
LogDistancePropagationLossModel::CreateDefaultReference (void)
{
switch (g_logDistanceReferenceType.GetValue ()) {
case RANDOM:
return Create<RandomPropagationLossModel> ();
break;
case FRIIS:
return Create<FriisPropagationLossModel> ();
break;
case LOG_DISTANCE:
default:
NS_ASSERT (false);
return 0;
break;
}
}
double
LogDistancePropagationLossModel::DbToW (double db) const
{
return pow(10.0,db/10.0);
}
double
LogDistancePropagationLossModel::GetRxPower (double txPowerDbm,
Ptr<MobilityModel> a,
Ptr<MobilityModel> b) const
{
double distance = a->GetDistanceFrom (b);
if (distance <= 1.0)
{
return txPowerDbm;
}
/**
* The formula is:
* rx = 10 * ln (Pr0(tx)) / ln (10) + n * 10 * ln (d/d0) / ln (10)
*
* Pr0: rx power at reference distance d0 (W)
* d0: reference distance: 1.0 (m)
* d: distance (m)
* tx: tx power (db)
* rx: db
*
* Since we use dbm instead of db, we have:
*
* rx = rx0 + 10 / ln (10) * (n * ln (d/d0) - ln (1000))
*/
static Ptr<StaticMobilityModel> zero = Create<StaticMobilityModel> (Position (0.0, 0.0, 0.0));
static Ptr<StaticMobilityModel> one = Create<StaticMobilityModel> (Position (1.0, 1.0, 1.0));
double rx0 = m_reference->GetRxPower (txPowerDbm, zero, one);
double rxPowerDbm = rx0 + 10 / log (10) * (m_exponent * log (distance) - log (1000));
NS_LOG_DEBUG ("distance="<<distance<<"m, tx power="<<txPowerDbm<<"dbm, "<<
"reference rx power="<<rx0<<"dbm, "<<
"rx power="<<rxPowerDbm<<"dbm");
return rxPowerDbm;
}
} // namespace ns3