three-gpp-channel-test-suite.cc

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/*
 * Copyright (c) 2019 SIGNET Lab, Department of Information Engineering,
 *
 * 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 "ns3/abort.h"
#include "ns3/angles.h"
#include "ns3/channel-condition-model.h"
#include "ns3/config.h"
#include "ns3/constant-position-mobility-model.h"
#include "ns3/double.h"
#include "ns3/isotropic-antenna-model.h"
#include "ns3/log.h"
#include "ns3/node-container.h"
#include "ns3/pointer.h"
#include "ns3/simple-net-device.h"
#include "ns3/simulator.h"
#include "ns3/spectrum-signal-parameters.h"
#include "ns3/string.h"
#include "ns3/test.h"
#include "ns3/three-gpp-channel-model.h"
#include "ns3/three-gpp-spectrum-propagation-loss-model.h"
#include "ns3/uinteger.h"
#include "ns3/uniform-planar-array.h"
#include "ns3/wifi-spectrum-value-helper.h"
 
using namespace ns3;
 
NS_LOG_COMPONENT_DEFINE("ThreeGppChannelTestSuite");
 
class ThreeGppChannelMatrixComputationTest : public TestCase
{
  public:
    ThreeGppChannelMatrixComputationTest();
 
    ~ThreeGppChannelMatrixComputationTest() override;
 
  private:
    void DoRun() override;
 
    void DoComputeNorm(Ptr<ThreeGppChannelModel> channelModel,
                       Ptr<MobilityModel> txMob,
                       Ptr<MobilityModel> rxMob,
                       Ptr<PhasedArrayModel> txAntenna,
                       Ptr<PhasedArrayModel> rxAntenna);
 
    std::vector<double> m_normVector; 
};
 
ThreeGppChannelMatrixComputationTest::ThreeGppChannelMatrixComputationTest()
    : TestCase("Check the dimensions and the norm of the channel matrix")
{
}
 
ThreeGppChannelMatrixComputationTest::~ThreeGppChannelMatrixComputationTest()
{
}
 
void
ThreeGppChannelMatrixComputationTest::DoComputeNorm(Ptr<ThreeGppChannelModel> channelModel,
                                                    Ptr<MobilityModel> txMob,
                                                    Ptr<MobilityModel> rxMob,
                                                    Ptr<PhasedArrayModel> txAntenna,
                                                    Ptr<PhasedArrayModel> rxAntenna)
{
    uint64_t txAntennaElements = txAntenna->GetNumberOfElements();
    uint64_t rxAntennaElements = rxAntenna->GetNumberOfElements();
 
    Ptr<const ThreeGppChannelModel::ChannelMatrix> channelMatrix =
        channelModel->GetChannel(txMob, rxMob, txAntenna, rxAntenna);
 
    double channelNorm = 0;
    uint8_t numTotClusters = channelMatrix->m_channel.at(0).at(0).size();
    for (uint8_t cIndex = 0; cIndex < numTotClusters; cIndex++)
    {
        double clusterNorm = 0;
        for (uint64_t sIndex = 0; sIndex < txAntennaElements; sIndex++)
        {
            for (uint32_t uIndex = 0; uIndex < rxAntennaElements; uIndex++)
            {
                clusterNorm +=
                    std::pow(std::abs(channelMatrix->m_channel.at(uIndex).at(sIndex).at(cIndex)),
                             2);
            }
        }
        channelNorm += clusterNorm;
    }
    m_normVector.push_back(channelNorm);
}
 
void
ThreeGppChannelMatrixComputationTest::DoRun()
{
    // Build the scenario for the test
    uint8_t txAntennaElements[]{2, 2}; // tx antenna dimensions
    uint8_t rxAntennaElements[]{2, 2}; // rx antenna dimensions
    uint32_t updatePeriodMs = 100;     // update period in ms
 
    // create the channel condition model
    Ptr<ChannelConditionModel> channelConditionModel =
        CreateObject<NeverLosChannelConditionModel>();
 
    // create the ThreeGppChannelModel object used to generate the channel matrix
    Ptr<ThreeGppChannelModel> channelModel = CreateObject<ThreeGppChannelModel>();
    channelModel->SetAttribute("Frequency", DoubleValue(60.0e9));
    channelModel->SetAttribute("Scenario", StringValue("RMa"));
    channelModel->SetAttribute("ChannelConditionModel", PointerValue(channelConditionModel));
    channelModel->SetAttribute("UpdatePeriod", TimeValue(MilliSeconds(updatePeriodMs - 1)));
 
    // create the tx and rx nodes
    NodeContainer nodes;
    nodes.Create(2);
 
    // create the tx and rx devices
    Ptr<SimpleNetDevice> txDev = CreateObject<SimpleNetDevice>();
    Ptr<SimpleNetDevice> rxDev = CreateObject<SimpleNetDevice>();
 
    // associate the nodes and the devices
    nodes.Get(0)->AddDevice(txDev);
    txDev->SetNode(nodes.Get(0));
    nodes.Get(1)->AddDevice(rxDev);
    rxDev->SetNode(nodes.Get(1));
 
    // create the tx and rx mobility models and set their positions
    Ptr<MobilityModel> txMob = CreateObject<ConstantPositionMobilityModel>();
    txMob->SetPosition(Vector(0.0, 0.0, 10.0));
    Ptr<MobilityModel> rxMob = CreateObject<ConstantPositionMobilityModel>();
    rxMob->SetPosition(Vector(100.0, 0.0, 10.0));
 
    // associate the nodes and the mobility models
    nodes.Get(0)->AggregateObject(txMob);
    nodes.Get(1)->AggregateObject(rxMob);
 
    // create the tx and rx antennas and set the their dimensions
    Ptr<PhasedArrayModel> txAntenna = CreateObjectWithAttributes<UniformPlanarArray>(
        "NumColumns",
        UintegerValue(txAntennaElements[0]),
        "NumRows",
        UintegerValue(txAntennaElements[1]),
        "AntennaElement",
        PointerValue(CreateObject<IsotropicAntennaModel>()));
    Ptr<PhasedArrayModel> rxAntenna = CreateObjectWithAttributes<UniformPlanarArray>(
        "NumColumns",
        UintegerValue(rxAntennaElements[0]),
        "NumRows",
        UintegerValue(rxAntennaElements[1]),
        "AntennaElement",
        PointerValue(CreateObject<IsotropicAntennaModel>()));
 
    // generate the channel matrix
    Ptr<const ThreeGppChannelModel::ChannelMatrix> channelMatrix =
        channelModel->GetChannel(txMob, rxMob, txAntenna, rxAntenna);
 
    // check the channel matrix dimensions
    NS_TEST_ASSERT_MSG_EQ(
        channelMatrix->m_channel.at(0).size(),
        txAntennaElements[0] * txAntennaElements[1],
        "The second dimension of H should be equal to the number of tx antenna elements");
    NS_TEST_ASSERT_MSG_EQ(
        channelMatrix->m_channel.size(),
        rxAntennaElements[0] * rxAntennaElements[1],
        "The first dimension of H should be equal to the number of rx antenna elements");
 
    // test if the channel matrix is correctly generated
    uint16_t numIt = 1000;
    for (uint16_t i = 0; i < numIt; i++)
    {
        Simulator::Schedule(MilliSeconds(updatePeriodMs * i),
                            &ThreeGppChannelMatrixComputationTest::DoComputeNorm,
                            this,
                            channelModel,
                            txMob,
                            rxMob,
                            txAntenna,
                            rxAntenna);
    }
 
    Simulator::Run();
 
    // compute the sample mean
    double sampleMean = 0;
    for (auto i : m_normVector)
    {
        sampleMean += i;
    }
    sampleMean /= numIt;
 
    // compute the sample standard deviation
    double sampleStd = 0;
    for (auto i : m_normVector)
    {
        sampleStd += ((i - sampleMean) * (i - sampleMean));
    }
    sampleStd = std::sqrt(sampleStd / (numIt - 1));
 
    // perform the one sample t-test with a significance level of 0.05 to test
    // the hypothesis "E [|H|^2] = M*N, where |H| indicates the Frobenius norm of
    // H, M is the number of transmit antenna elements, and N is the number of
    // the receive antenna elements"
    double t = (sampleMean - txAntennaElements[0] * txAntennaElements[1] * rxAntennaElements[0] *
                                 rxAntennaElements[1]) /
               (sampleMean / std::sqrt(numIt));
 
    // Using a significance level of 0.05, we reject the null hypothesis if |t| is
    // greater than the critical value from a t-distribution with df = numIt-1
    NS_TEST_ASSERT_MSG_EQ_TOL(
        std::abs(t),
        0,
        1.65,
        "We reject the hypothesis E[|H|^2] = M*N with a significance level of 0.05");
 
    Simulator::Destroy();
}
 
class ThreeGppChannelMatrixUpdateTest : public TestCase
{
  public:
    ThreeGppChannelMatrixUpdateTest();
 
    ~ThreeGppChannelMatrixUpdateTest() override;
 
  private:
    void DoRun() override;
 
    void DoGetChannel(Ptr<ThreeGppChannelModel> channelModel,
                      Ptr<MobilityModel> txMob,
                      Ptr<MobilityModel> rxMob,
                      Ptr<PhasedArrayModel> txAntenna,
                      Ptr<PhasedArrayModel> rxAntenna,
                      bool update);
 
    Ptr<const ThreeGppChannelModel::ChannelMatrix>
        m_currentChannel; 
};
 
ThreeGppChannelMatrixUpdateTest::ThreeGppChannelMatrixUpdateTest()
    : TestCase("Check if the channel realizations are correctly updated during the simulation")
{
}
 
ThreeGppChannelMatrixUpdateTest::~ThreeGppChannelMatrixUpdateTest()
{
}
 
void
ThreeGppChannelMatrixUpdateTest::DoGetChannel(Ptr<ThreeGppChannelModel> channelModel,
                                              Ptr<MobilityModel> txMob,
                                              Ptr<MobilityModel> rxMob,
                                              Ptr<PhasedArrayModel> txAntenna,
                                              Ptr<PhasedArrayModel> rxAntenna,
                                              bool update)
{
    // retrieve the channel matrix
    Ptr<const ThreeGppChannelModel::ChannelMatrix> channelMatrix =
        channelModel->GetChannel(txMob, rxMob, txAntenna, rxAntenna);
 
    if (!m_currentChannel)
    {
        // this is the first time we compute the channel matrix, we initialize
        // m_currentChannel
        m_currentChannel = channelMatrix;
    }
    else
    {
        // compare the old and the new channel matrices
        NS_TEST_ASSERT_MSG_EQ((m_currentChannel != channelMatrix),
                              update,
                              Simulator::Now().GetMilliSeconds()
                                  << " The channel matrix is not correctly updated");
    }
}
 
void
ThreeGppChannelMatrixUpdateTest::DoRun()
{
    // Build the scenario for the test
 
    uint8_t txAntennaElements[]{2, 2}; // tx antenna dimensions
    uint8_t rxAntennaElements[]{4, 4}; // rx antenna dimensions
    uint32_t updatePeriodMs = 100;     // update period in ms
 
    // create the channel condition model
    Ptr<ChannelConditionModel> channelConditionModel =
        CreateObject<AlwaysLosChannelConditionModel>();
 
    // create the ThreeGppChannelModel object used to generate the channel matrix
    Ptr<ThreeGppChannelModel> channelModel = CreateObject<ThreeGppChannelModel>();
    channelModel->SetAttribute("Frequency", DoubleValue(60.0e9));
    channelModel->SetAttribute("Scenario", StringValue("UMa"));
    channelModel->SetAttribute("ChannelConditionModel", PointerValue(channelConditionModel));
    channelModel->SetAttribute("UpdatePeriod", TimeValue(MilliSeconds(updatePeriodMs)));
 
    // create the tx and rx nodes
    NodeContainer nodes;
    nodes.Create(2);
 
    // create the tx and rx devices
    Ptr<SimpleNetDevice> txDev = CreateObject<SimpleNetDevice>();
    Ptr<SimpleNetDevice> rxDev = CreateObject<SimpleNetDevice>();
 
    // associate the nodes and the devices
    nodes.Get(0)->AddDevice(txDev);
    txDev->SetNode(nodes.Get(0));
    nodes.Get(1)->AddDevice(rxDev);
    rxDev->SetNode(nodes.Get(1));
 
    // create the tx and rx mobility models and set their positions
    Ptr<MobilityModel> txMob = CreateObject<ConstantPositionMobilityModel>();
    txMob->SetPosition(Vector(0.0, 0.0, 10.0));
    Ptr<MobilityModel> rxMob = CreateObject<ConstantPositionMobilityModel>();
    rxMob->SetPosition(Vector(100.0, 0.0, 1.6));
 
    // associate the nodes and the mobility models
    nodes.Get(0)->AggregateObject(txMob);
    nodes.Get(1)->AggregateObject(rxMob);
 
    // create the tx and rx antennas and set the their dimensions
    Ptr<PhasedArrayModel> txAntenna = CreateObjectWithAttributes<UniformPlanarArray>(
        "NumColumns",
        UintegerValue(txAntennaElements[0]),
        "NumRows",
        UintegerValue(txAntennaElements[1]),
        "AntennaElement",
        PointerValue(CreateObject<IsotropicAntennaModel>()));
    Ptr<PhasedArrayModel> rxAntenna = CreateObjectWithAttributes<UniformPlanarArray>(
        "NumColumns",
        UintegerValue(rxAntennaElements[0]),
        "NumRows",
        UintegerValue(rxAntennaElements[1]),
        "AntennaElement",
        PointerValue(CreateObject<IsotropicAntennaModel>()));
 
    // check if the channel matrix is correctly updated
 
    // compute the channel matrix for the first time
    uint32_t firstTimeMs =
        1; // time instant at which the channel matrix is generated for the first time
    Simulator::Schedule(MilliSeconds(firstTimeMs),
                        &ThreeGppChannelMatrixUpdateTest::DoGetChannel,
                        this,
                        channelModel,
                        txMob,
                        rxMob,
                        txAntenna,
                        rxAntenna,
                        true);
 
    // call GetChannel before the update period is exceeded, the channel matrix
    // should not be updated
    Simulator::Schedule(MilliSeconds(firstTimeMs + updatePeriodMs / 2),
                        &ThreeGppChannelMatrixUpdateTest::DoGetChannel,
                        this,
                        channelModel,
                        txMob,
                        rxMob,
                        txAntenna,
                        rxAntenna,
                        false);
 
    // call GetChannel when the update period is exceeded, the channel matrix
    // should be recomputed
    Simulator::Schedule(MilliSeconds(firstTimeMs + updatePeriodMs + 1),
                        &ThreeGppChannelMatrixUpdateTest::DoGetChannel,
                        this,
                        channelModel,
                        txMob,
                        rxMob,
                        txAntenna,
                        rxAntenna,
                        true);
 
    Simulator::Run();
    Simulator::Destroy();
}
 
struct CheckLongTermUpdateParams
{
    Ptr<ThreeGppSpectrumPropagationLossModel>
        lossModel; 
    Ptr<SpectrumSignalParameters> txParams; 
    Ptr<MobilityModel> txMob;               
    Ptr<MobilityModel> rxMob;               
    Ptr<SpectrumValue> rxPsdOld;            
    Ptr<PhasedArrayModel> txAntenna;        
    Ptr<PhasedArrayModel> rxAntenna;        
};
 
class ThreeGppSpectrumPropagationLossModelTest : public TestCase
{
  public:
    ThreeGppSpectrumPropagationLossModelTest();
 
    ~ThreeGppSpectrumPropagationLossModelTest() override;
 
  private:
    void DoRun() override;
 
    void DoBeamforming(Ptr<NetDevice> thisDevice,
                       Ptr<PhasedArrayModel> thisAntenna,
                       Ptr<NetDevice> otherDevice,
                       Ptr<PhasedArrayModel> otherAntenna);
 
    void CheckLongTermUpdate(const CheckLongTermUpdateParams& params);
 
    static bool ArePsdEqual(Ptr<SpectrumValue> first, Ptr<SpectrumValue> second);
};
 
ThreeGppSpectrumPropagationLossModelTest::ThreeGppSpectrumPropagationLossModelTest()
    : TestCase("Test case for the ThreeGppSpectrumPropagationLossModel class")
{
}
 
ThreeGppSpectrumPropagationLossModelTest::~ThreeGppSpectrumPropagationLossModelTest()
{
}
 
void
ThreeGppSpectrumPropagationLossModelTest::DoBeamforming(Ptr<NetDevice> thisDevice,
                                                        Ptr<PhasedArrayModel> thisAntenna,
                                                        Ptr<NetDevice> otherDevice,
                                                        Ptr<PhasedArrayModel> otherAntenna)
{
    Vector aPos = thisDevice->GetNode()->GetObject<MobilityModel>()->GetPosition();
    Vector bPos = otherDevice->GetNode()->GetObject<MobilityModel>()->GetPosition();
 
    // compute the azimuth and the elevation angles
    Angles completeAngle(bPos, aPos);
 
    PhasedArrayModel::ComplexVector antennaWeights =
        thisAntenna->GetBeamformingVector(completeAngle);
    thisAntenna->SetBeamformingVector(antennaWeights);
}
 
bool
ThreeGppSpectrumPropagationLossModelTest::ArePsdEqual(Ptr<SpectrumValue> first,
                                                      Ptr<SpectrumValue> second)
{
    bool ret = true;
    for (uint8_t i = 0; i < first->GetSpectrumModel()->GetNumBands(); i++)
    {
        if ((*first)[i] != (*second)[i])
        {
            ret = false;
            continue;
        }
    }
    return ret;
}
 
void
ThreeGppSpectrumPropagationLossModelTest::CheckLongTermUpdate(
    const CheckLongTermUpdateParams& params)
{
    Ptr<SpectrumValue> rxPsdNew = params.lossModel->DoCalcRxPowerSpectralDensity(params.txParams,
                                                                                 params.txMob,
                                                                                 params.rxMob,
                                                                                 params.txAntenna,
                                                                                 params.rxAntenna);
    NS_TEST_ASSERT_MSG_EQ(ArePsdEqual(params.rxPsdOld, rxPsdNew),
                          false,
                          "The long term is not updated when the channel matrix is recomputed");
}
 
void
ThreeGppSpectrumPropagationLossModelTest::DoRun()
{
    // Build the scenario for the test
    Config::SetDefault("ns3::ThreeGppChannelModel::UpdatePeriod", TimeValue(MilliSeconds(100)));
 
    uint8_t txAntennaElements[]{4, 4}; // tx antenna dimensions
    uint8_t rxAntennaElements[]{4, 4}; // rx antenna dimensions
 
    // create the ChannelConditionModel object to be used to retrieve the
    // channel condition
    Ptr<ChannelConditionModel> condModel = CreateObject<AlwaysLosChannelConditionModel>();
 
    // create the ThreeGppSpectrumPropagationLossModel object, set frequency,
    // scenario and channel condition model to be used
    Ptr<ThreeGppSpectrumPropagationLossModel> lossModel =
        CreateObject<ThreeGppSpectrumPropagationLossModel>();
    lossModel->SetChannelModelAttribute("Frequency", DoubleValue(2.4e9));
    lossModel->SetChannelModelAttribute("Scenario", StringValue("UMa"));
    lossModel->SetChannelModelAttribute(
        "ChannelConditionModel",
        PointerValue(condModel)); // create the ThreeGppChannelModel object used to generate the
                                  // channel matrix
 
    // create the tx and rx nodes
    NodeContainer nodes;
    nodes.Create(2);
 
    // create the tx and rx devices
    Ptr<SimpleNetDevice> txDev = CreateObject<SimpleNetDevice>();
    Ptr<SimpleNetDevice> rxDev = CreateObject<SimpleNetDevice>();
 
    // associate the nodes and the devices
    nodes.Get(0)->AddDevice(txDev);
    txDev->SetNode(nodes.Get(0));
    nodes.Get(1)->AddDevice(rxDev);
    rxDev->SetNode(nodes.Get(1));
 
    // create the tx and rx mobility models and set their positions
    Ptr<MobilityModel> txMob = CreateObject<ConstantPositionMobilityModel>();
    txMob->SetPosition(Vector(0.0, 0.0, 10.0));
    Ptr<MobilityModel> rxMob = CreateObject<ConstantPositionMobilityModel>();
    rxMob->SetPosition(
        Vector(15.0, 0.0, 10.0)); // in this position the channel condition is always LOS
 
    // associate the nodes and the mobility models
    nodes.Get(0)->AggregateObject(txMob);
    nodes.Get(1)->AggregateObject(rxMob);
 
    // create the tx and rx antennas and set the their dimensions
    Ptr<PhasedArrayModel> txAntenna = CreateObjectWithAttributes<UniformPlanarArray>(
        "NumColumns",
        UintegerValue(txAntennaElements[0]),
        "NumRows",
        UintegerValue(txAntennaElements[1]),
        "AntennaElement",
        PointerValue(CreateObject<IsotropicAntennaModel>()));
    Ptr<PhasedArrayModel> rxAntenna = CreateObjectWithAttributes<UniformPlanarArray>(
        "NumColumns",
        UintegerValue(rxAntennaElements[0]),
        "NumRows",
        UintegerValue(rxAntennaElements[1]),
        "AntennaElement",
        PointerValue(CreateObject<IsotropicAntennaModel>()));
 
    // set the beamforming vectors
    DoBeamforming(txDev, txAntenna, rxDev, rxAntenna);
    DoBeamforming(rxDev, rxAntenna, txDev, txAntenna);
 
    // create the tx psd
    WifiSpectrumValue5MhzFactory sf;
    double txPower = 0.1; // Watts
    uint32_t channelNumber = 1;
    Ptr<SpectrumValue> txPsd = sf.CreateTxPowerSpectralDensity(txPower, channelNumber);
    Ptr<SpectrumSignalParameters> txParams = Create<SpectrumSignalParameters>();
    txParams->psd = txPsd->Copy();
 
    // compute the rx psd
    Ptr<SpectrumValue> rxPsdOld =
        lossModel->DoCalcRxPowerSpectralDensity(txParams, txMob, rxMob, txAntenna, rxAntenna);
 
    // 1) check that the rx PSD is equal for both the direct and the reverse channel
    Ptr<SpectrumValue> rxPsdNew =
        lossModel->DoCalcRxPowerSpectralDensity(txParams, rxMob, txMob, rxAntenna, txAntenna);
    NS_TEST_ASSERT_MSG_EQ(ArePsdEqual(rxPsdOld, rxPsdNew),
                          true,
                          "The long term for the direct and the reverse channel are different");
 
    // 2) check if the long term is updated when changing the BF vector
    // change the position of the rx device and recompute the beamforming vectors
    rxMob->SetPosition(Vector(10.0, 5.0, 10.0));
    PhasedArrayModel::ComplexVector txBfVector = txAntenna->GetBeamformingVector();
    txBfVector[0] = std::complex<double>(0.0, 0.0);
    txAntenna->SetBeamformingVector(txBfVector);
 
    rxPsdNew =
        lossModel->DoCalcRxPowerSpectralDensity(txParams, rxMob, txMob, rxAntenna, txAntenna);
    NS_TEST_ASSERT_MSG_EQ(ArePsdEqual(rxPsdOld, rxPsdNew),
                          false,
                          "Changing the BF vectors the rx PSD does not change");
 
    // update rxPsdOld
    rxPsdOld = rxPsdNew;
 
    // 3) check if the long term is updated when the channel matrix is recomputed
    CheckLongTermUpdateParams
        params{lossModel, txParams, txMob, rxMob, rxPsdOld, txAntenna, rxAntenna};
    Simulator::Schedule(MilliSeconds(101),
                        &ThreeGppSpectrumPropagationLossModelTest::CheckLongTermUpdate,
                        this,
                        params);
 
    Simulator::Run();
    Simulator::Destroy();
}
 
class ThreeGppChannelTestSuite : public TestSuite
{
  public:
    ThreeGppChannelTestSuite();
};
 
ThreeGppChannelTestSuite::ThreeGppChannelTestSuite()
    : TestSuite("three-gpp-channel", UNIT)
{
    AddTestCase(new ThreeGppChannelMatrixComputationTest, TestCase::QUICK);
    AddTestCase(new ThreeGppChannelMatrixUpdateTest, TestCase::QUICK);
    AddTestCase(new ThreeGppSpectrumPropagationLossModelTest, TestCase::QUICK);
}
 
static ThreeGppChannelTestSuite myTestSuite;