three-gpp-v2v-propagation-loss-model.cc

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/*
 * Copyright (c) 2020 SIGNET Lab, Department of Information Engineering,
 * University of Padova
 *
 * 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
 */
 
#include "three-gpp-v2v-propagation-loss-model.h"
 
#include "ns3/double.h"
#include "ns3/log.h"
#include "ns3/string.h"
 
namespace ns3
{
 
NS_LOG_COMPONENT_DEFINE("ThreeGppV2vPropagationLossModel");
 
// ------------------------------------------------------------------------- //
 
NS_OBJECT_ENSURE_REGISTERED(ThreeGppV2vUrbanPropagationLossModel);
 
TypeId
ThreeGppV2vUrbanPropagationLossModel::GetTypeId()
{
    static TypeId tid =
        TypeId("ns3::ThreeGppV2vUrbanPropagationLossModel")
            .SetParent<ThreeGppPropagationLossModel>()
            .SetGroupName("Propagation")
            .AddConstructor<ThreeGppV2vUrbanPropagationLossModel>()
            .AddAttribute(
                "PercType3Vehicles",
                "The percentage of vehicles of type 3 (i.e., trucks) in the scenario",
                DoubleValue(0.0),
                MakeDoubleAccessor(&ThreeGppV2vUrbanPropagationLossModel::m_percType3Vehicles),
                MakeDoubleChecker<double>(0.0, 100.0));
    return tid;
}
 
ThreeGppV2vUrbanPropagationLossModel::ThreeGppV2vUrbanPropagationLossModel()
    : ThreeGppPropagationLossModel()
{
    NS_LOG_FUNCTION(this);
    m_uniformVar = CreateObject<UniformRandomVariable>();
    m_logNorVar = CreateObject<LogNormalRandomVariable>();
 
    // set a default channel condition model
    // TODO the default ccm needs buildings, how to do this?
    // m_channelConditionModel = CreateObject<ThreeGppRmaChannelConditionModel> ();
}
 
ThreeGppV2vUrbanPropagationLossModel::~ThreeGppV2vUrbanPropagationLossModel()
{
    NS_LOG_FUNCTION(this);
}
 
double
ThreeGppV2vUrbanPropagationLossModel::GetLossLos(double /* distance2D */,
                                                 double distance3D,
                                                 double /* hUt */,
                                                 double /* hBs */) const
{
    NS_LOG_FUNCTION(this);
 
    // compute the pathloss (see 3GPP TR 37.885, Table 6.2.1-1)
    double loss = 38.77 + 16.7 * log10(distance3D) + 18.2 * log10(m_frequency / 1e9);
 
    return loss;
}
 
double
ThreeGppV2vUrbanPropagationLossModel::GetO2iDistance2dIn() const
{
    // TODO O2I car penetration loss (TR 38.901 7.4.3.2) not considered
    NS_LOG_WARN("O2I car penetration loss not yet implemented");
    return 0;
}
 
double
ThreeGppV2vUrbanPropagationLossModel::GetLossNlosv(double distance2D,
                                                   double distance3D,
                                                   double hUt,
                                                   double hBs) const
{
    NS_LOG_FUNCTION(this);
 
    // compute the pathloss (see 3GPP TR 37.885, Table 6.2.1-1)
    double loss =
        GetLossLos(distance2D, distance3D, hUt, hBs) + GetAdditionalNlosvLoss(distance3D, hUt, hBs);
 
    return loss;
}
 
double
ThreeGppV2vUrbanPropagationLossModel::GetAdditionalNlosvLoss(double distance3D,
                                                             double hUt,
                                                             double hBs) const
{
    NS_LOG_FUNCTION(this);
    // From TR 37.885 v15.2.0
    // When a V2V link is in NLOSv, additional vehicle blockage loss is
    // added as follows:
    // 1. The blocker height is the vehicle height which is randomly selected
    // out of the three vehicle types according to the portion of the vehicle
    // types in the simulated scenario.
    double additionalLoss = 0;
    double blockerHeight = 0;
    double mu_a = 0;
    double sigma_a = 0;
    double randomValue = m_uniformVar->GetValue() * 100.0;
    if (randomValue < m_percType3Vehicles)
    {
        // vehicles of type 3 have height 3 meters
        blockerHeight = 3.0;
    }
    else
    {
        // vehicles of type 1 and 2 have height 1.6 meters
        blockerHeight = 1.6;
    }
 
    // The additional blockage loss is max {0 dB, a log-normal random variable}
    if (std::min(hUt, hBs) > blockerHeight)
    {
        // Case 1: Minimum antenna height value of TX and RX > Blocker height
        additionalLoss = 0;
    }
    else if (std::max(hUt, hBs) < blockerHeight)
    {
        // Case 2: Maximum antenna height value of TX and RX < Blocker height
        mu_a = 9.0 + std::max(0.0, 15 * log10(distance3D) - 41.0);
        sigma_a = 4.5;
        m_logNorVar->SetAttribute(
            "Mu",
            DoubleValue(log(pow(mu_a, 2) / sqrt(pow(sigma_a, 2) + pow(mu_a, 2)))));
        m_logNorVar->SetAttribute("Sigma",
                                  DoubleValue(sqrt(log(pow(sigma_a, 2) / pow(mu_a, 2) + 1))));
        additionalLoss = std::max(0.0, m_logNorVar->GetValue());
    }
    else
    {
        // Case 3: Otherwise
        mu_a = 5.0 + std::max(0.0, 15 * log10(distance3D) - 41.0);
        sigma_a = 4.0;
 
        m_logNorVar->SetAttribute(
            "Mu",
            DoubleValue(log(pow(mu_a, 2) / sqrt(pow(sigma_a, 2) + pow(mu_a, 2)))));
        m_logNorVar->SetAttribute("Sigma",
                                  DoubleValue(sqrt(log(pow(sigma_a, 2) / pow(mu_a, 2) + 1))));
        additionalLoss = std::max(0.0, m_logNorVar->GetValue());
    }
 
    return additionalLoss;
}
 
double
ThreeGppV2vUrbanPropagationLossModel::GetLossNlos(double /* distance2D */,
                                                  double distance3D,
                                                  double /* hUt */,
                                                  double /* hBs */) const
{
    NS_LOG_FUNCTION(this);
 
    double loss = 36.85 + 30 * log10(distance3D) + 18.9 * log10(m_frequency / 1e9);
 
    return loss;
}
 
double
ThreeGppV2vUrbanPropagationLossModel::GetShadowingStd(
    Ptr<MobilityModel> /* a */,
    Ptr<MobilityModel> /* b */,
    ChannelCondition::LosConditionValue cond) const
{
    NS_LOG_FUNCTION(this);
    double shadowingStd;
 
    if (cond == ChannelCondition::LosConditionValue::LOS ||
        cond == ChannelCondition::LosConditionValue::NLOSv)
    {
        shadowingStd = 3.0;
    }
    else if (cond == ChannelCondition::LosConditionValue::NLOS)
    {
        shadowingStd = 4.0;
    }
    else
    {
        NS_FATAL_ERROR("Unknown channel condition");
    }
 
    return shadowingStd;
}
 
double
ThreeGppV2vUrbanPropagationLossModel::GetShadowingCorrelationDistance(
    ChannelCondition::LosConditionValue cond) const
{
    NS_LOG_FUNCTION(this);
    double correlationDistance;
 
    // See 3GPP TR 37.885, Table 6.2.3-1
    if (cond == ChannelCondition::LosConditionValue::LOS)
    {
        correlationDistance = 10;
    }
    else if (cond == ChannelCondition::LosConditionValue::NLOSv ||
             cond == ChannelCondition::LosConditionValue::NLOS)
    {
        correlationDistance = 13;
    }
    else
    {
        NS_FATAL_ERROR("Unknown channel condition");
    }
 
    return correlationDistance;
}
 
int64_t
ThreeGppV2vUrbanPropagationLossModel::DoAssignStreams(int64_t stream)
{
    NS_LOG_FUNCTION(this);
 
    m_normRandomVariable->SetStream(stream);
    m_uniformVar->SetStream(stream + 1);
    m_logNorVar->SetStream(stream + 2);
    return 3;
}
 
// ------------------------------------------------------------------------- //
 
NS_OBJECT_ENSURE_REGISTERED(ThreeGppV2vHighwayPropagationLossModel);
 
TypeId
ThreeGppV2vHighwayPropagationLossModel::GetTypeId()
{
    static TypeId tid = TypeId("ns3::ThreeGppV2vHighwayPropagationLossModel")
                            .SetParent<ThreeGppV2vUrbanPropagationLossModel>()
                            .SetGroupName("Propagation")
                            .AddConstructor<ThreeGppV2vHighwayPropagationLossModel>();
    return tid;
}
 
ThreeGppV2vHighwayPropagationLossModel::ThreeGppV2vHighwayPropagationLossModel()
    : ThreeGppV2vUrbanPropagationLossModel()
{
    NS_LOG_FUNCTION(this);
}
 
ThreeGppV2vHighwayPropagationLossModel::~ThreeGppV2vHighwayPropagationLossModel()
{
    NS_LOG_FUNCTION(this);
}
 
double
ThreeGppV2vHighwayPropagationLossModel::GetLossLos(double /* distance2D */,
                                                   double distance3D,
                                                   double /* hUt */,
                                                   double /* hBs */) const
{
    NS_LOG_FUNCTION(this);
 
    // compute the pathloss (see 3GPP TR 37.885, Table 6.2.1-1)
    double loss = 32.4 + 20 * log10(distance3D) + 20 * log10(m_frequency / 1e9);
 
    return loss;
}
 
} // namespace ns3