/* -*-  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>

 * Contributions: Timo Bingmann <timo.bingmann@student.kit.edu>

 * Contributions: Gary Pei <guangyu.pei@boeing.com> for fixed RSS

 */

#ifndef PROPAGATION_LOSS_MODEL_H

#define PROPAGATION_LOSS_MODEL_H

#include "ns3/object.h"

#include "ns3/random-variable.h"

namespace ns3 {

class MobilityModel;

/**

 * \brief Modelize the propagation loss through a transmission medium

 *

 * Calculate the receive power (dbm) from a transmit power (dbm)

 * and a mobility model for the source and destination positions.

 */

class PropagationLossModel : public Object

{

public:

  static TypeId GetTypeId (void);

  PropagationLossModel ();

  virtual ~PropagationLossModel ();

  void SetNext (Ptr<PropagationLossModel> next);

  /**

   * \param txPowerDbm current transmission power (in dBm)

   * \param a the mobility model of the source

   * \param b the mobility model of the destination

   * \returns the reception power after adding/multiplying propagation loss (in dBm)

   */

  double CalcRxPower (double txPowerDbm,

                      Ptr<MobilityModel> a,

                      Ptr<MobilityModel> b) const;

private:

  PropagationLossModel (const PropagationLossModel &o);

  PropagationLossModel &operator = (const PropagationLossModel &o);

  virtual double DoCalcRxPower (double txPowerDbm,

                                Ptr<MobilityModel> a,

                                Ptr<MobilityModel> b) const = 0;

  Ptr<PropagationLossModel> m_next;

};

/**

 * \brief The propagation loss follows a random distribution.

 */ 

class RandomPropagationLossModel : public PropagationLossModel

{

public:

  static TypeId GetTypeId (void);

  RandomPropagationLossModel ();

  virtual ~RandomPropagationLossModel ();

private:

  RandomPropagationLossModel (const RandomPropagationLossModel &o);

  RandomPropagationLossModel & operator = (const RandomPropagationLossModel &o);

  virtual double DoCalcRxPower (double txPowerDbm,

                                Ptr<MobilityModel> a,

                                Ptr<MobilityModel> b) const;

  RandomVariable m_variable;

};

/**

 * \brief a Friis propagation loss model

 *

 * The Friis propagation loss model was first described in

 * "A Note on a Simple Transmission Formula", by 

 * "Harald T. Friis".

 * 

 * The original equation was described as:

 *  \f$ \frac{P_r}{P_t} = \frac{A_r A_t}{d^2\lambda^2} \f$

 *  with the following equation for the case of an

 *  isotropic antenna with no heat loss:

 *  \f$ A_{isotr.} = \frac{\lambda^2}{4\pi} \f$

 *

 * The final equation becomes:

 * \f$ \frac{P_r}{P_t} = \frac{\lambda^2}{(4 \pi d)^2} \f$

 *

 * Modern extensions to this original equation are:

 * \f$ P_r = \frac{P_t G_t G_r \lambda^2}{(4 \pi d)^2 L}\f$

 *

 * With:

 *  - \f$ P_r \f$ : reception power (W)

 *  - \f$ P_t \f$ : transmission power (W)

 *  - \f$ G_t \f$ : transmission gain (unit-less)

 *  - \f$ G_r \f$ : reception gain (unit-less)

 *  - \f$ \lambda \f$ : wavelength (m)

 *  - \f$ d \f$ : distance (m)

 *  - \f$ L \f$ : system loss (unit-less)

 *

 *

 * This model is invalid for small distance values.

 * The current implementation returns the txpower as the rxpower

 * for any distance smaller than MinDistance.

 */

class FriisPropagationLossModel : public PropagationLossModel

{

public:

  static TypeId GetTypeId (void);

  FriisPropagationLossModel ();

  /**

   * \param frequency (Hz)

   * \param speed (m/s)

   *

   * Set the main wavelength used in the Friis model 

   * calculation.

   */

  void SetLambda (double frequency, double speed);

  /**

   * \param lambda (m) the wavelength

   *

   * Set the main wavelength used in the Friis model 

   * calculation.

   */

  void SetLambda (double lambda);

  /**

   * \param systemLoss (dimension-less)

   *

   * Set the system loss used by the Friis propagation model.

   */

  void SetSystemLoss (double systemLoss);

  /**

   * \param minDistance the minimum distance

   *

   * Below this distance, the txpower is returned

   * unmodified as the rxpower.

   */

  void SetMinDistance (double minDistance);

  /**

   * \returns the minimum distance.

   */

  double GetMinDistance (void) const;

  /**

   * \returns the current wavelength (m)

   */

  double GetLambda (void) const;

  /**

   * \returns the current system loss (dimention-less)

   */

  double GetSystemLoss (void) const;

private:

  FriisPropagationLossModel (const FriisPropagationLossModel &o);

  FriisPropagationLossModel & operator = (const FriisPropagationLossModel &o);

  virtual double DoCalcRxPower (double txPowerDbm,

                                Ptr<MobilityModel> a,

                                Ptr<MobilityModel> b) const;

  double DbmToW (double dbm) const;

  double DbmFromW (double w) const;

  static const double PI;

  double m_lambda;

  double m_systemLoss;

  double m_minDistance;

};

/**

 * \brief a log distance propagation model.

 *

 * This model calculates the reception power with a so-called

 * log-distance propagation model:

 * \f$ L = L_0 + 10 n log_{10}(\frac{d}{d_0})\f$

 *

 * where:

 *  - \f$ n \f$ : the path loss distance exponent

 *  - \f$ d_0 \f$ : reference distance (m)

 *  - \f$ L_0 \f$ : path loss at reference distance (dB)

 *  - \f$ d \f$ : distance (m)

 *  - \f$ L \f$ : path loss (dB)

 *

 * When the path loss is requested at a distance smaller than

 * the reference distance, the tx power is returned.

 *

 */

class LogDistancePropagationLossModel : public PropagationLossModel

{

public:

  static TypeId GetTypeId (void);

  LogDistancePropagationLossModel ();

  /**

   * \param n the path loss exponent.

   * Set the path loss exponent.

   */

  void SetPathLossExponent (double n);

  /** 

   * \returns the current path loss exponent.

   */

  double GetPathLossExponent (void) const;

  void SetReference (double referenceDistance, double referenceLoss);

private:

  LogDistancePropagationLossModel (const LogDistancePropagationLossModel &o);

  LogDistancePropagationLossModel & operator = (const LogDistancePropagationLossModel &o);

  virtual double DoCalcRxPower (double txPowerDbm,

                                Ptr<MobilityModel> a,

                                Ptr<MobilityModel> b) const;

  static Ptr<PropagationLossModel> CreateDefaultReference (void);

  double m_exponent;

  double m_referenceDistance;

  double m_referenceLoss;

};

/**

 * \brief A log distance path loss propagation model with three distance

 * fields. This model is the same as ns3::LogDistancePropagationLossModel

 * except that it has three distance fields: near, middle and far with

 * different exponents.

 *

 * Within each field the reception power is calculated using the log-distance

 * propagation equation:

 * \f[ L = L_0 + 10 \cdot n_0 log_{10}(\frac{d}{d_0})\f]

 * Each field begins where the previous ends and all together form a continuous function.

 *

 * There are three valid distance fields: near, middle, far. Actually four: the

 * first from 0 to the reference distance is invalid and returns txPowerDbm.

 *

 * \f[ \underbrace{0 \cdots\cdots}_{=0} \underbrace{d_0 \cdots\cdots}_{n_0} \underbrace{d_1 \cdots\cdots}_{n_1} \underbrace{d_2 \cdots\cdots}_{n_2} \infty \f]

 *

 * Complete formula for the path loss in dB:

 *

 * \f[\displaystyle L =

\begin{cases}

0 & d < d_0 \\

L_0 + 10 \cdot n_0 \log_{10}(\frac{d}{d_0}) & d_0 \leq d < d_1 \\

L_0 + 10 \cdot n_0 \log_{10}(\frac{d_1}{d_0}) + 10 \cdot n_1 \log_{10}(\frac{d}{d_1}) & d_1 \leq d < d_2 \\

L_0 + 10 \cdot n_0 \log_{10}(\frac{d_1}{d_0}) + 10 \cdot n_1 \log_{10}(\frac{d_2}{d_1}) + 10 \cdot n_2 \log_{10}(\frac{d}{d_2})& d_2 \leq d

\end{cases}\f]

 *

 * where:

 *  - \f$ L \f$ : resulting path loss (dB)

 *  - \f$ d \f$ : distance (m)

 *  - \f$ d_0, d_1, d_2 \f$ : three distance fields (m)

 *  - \f$ n_0, n_1, n_2 \f$ : path loss distance exponent for each field (unitless)

 *  - \f$ L_0 \f$ : path loss at reference distance (dB)

 *

 * When the path loss is requested at a distance smaller than the reference

 * distance \f$ d_0 \f$, the tx power (with no path loss) is returned. The

 * reference distance defaults to 1m and reference loss defaults to

 * ns3::FriisPropagationLossModel with 5.15 GHz and is thus \f$ L_0 \f$ = 46.67 dB.

 */

class ThreeLogDistancePropagationLossModel : public PropagationLossModel

{

public:

  static TypeId GetTypeId (void);

  ThreeLogDistancePropagationLossModel ();

  // Parameters are all accessible via attributes.

private:

  ThreeLogDistancePropagationLossModel (const ThreeLogDistancePropagationLossModel& o);

  ThreeLogDistancePropagationLossModel& operator= (const ThreeLogDistancePropagationLossModel& o);

  virtual double DoCalcRxPower (double txPowerDbm,

                                Ptr<MobilityModel> a,

                                Ptr<MobilityModel> b) const;

  double m_distance0;

  double m_distance1;

  double m_distance2;

  double m_exponent0;

  double m_exponent1;

  double m_exponent2;

  double m_referenceLoss;

};

/**

 * \brief Nakagami-m fast fading propagation loss model.

 *

 * The Nakagami-m distribution is applied to the power level. The probability

 * density function is defined as

 * \f[ p(x; m, \omega) = \frac{2 m^m}{\Gamma(m) \omega^m} x^{2m - 1} e^{-\frac{m}{\omega} x^2} = 2 x \cdot p_{\text{Gamma}}(x^2, m, \frac{m}{\omega}) \f]

 * with \f$ m \f$ the fading depth parameter and \f$ \omega \f$ the average received power.

 *

 * It is implemented by either a ns3::GammaVariable or a ns3::ErlangVariable

 * random variable.

 *

 * Like in ns3::ThreeLogDistancePropagationLossModel, the m parameter is varied

 * over three distance fields:

 * \f[ \underbrace{0 \cdots\cdots}_{m_0} \underbrace{d_1 \cdots\cdots}_{m_1} \underbrace{d_2 \cdots\cdots}_{m_2} \infty \f]

 *

 * For m = 1 the Nakagami-m distribution equals the Rayleigh distribution. Thus

 * this model also implements Rayleigh distribution based fast fading.

 */

class NakagamiPropagationLossModel : public PropagationLossModel

{

public:

  static TypeId GetTypeId (void);

  NakagamiPropagationLossModel ();

  // Parameters are all accessible via attributes.

private:

  NakagamiPropagationLossModel (const NakagamiPropagationLossModel& o);

  NakagamiPropagationLossModel& operator= (const NakagamiPropagationLossModel& o);

  virtual double DoCalcRxPower (double txPowerDbm,

                                Ptr<MobilityModel> a,

                                Ptr<MobilityModel> b) const;

  double m_distance1;

  double m_distance2;

  double m_m0;

  double m_m1;

  double m_m2;

  ErlangVariable        m_erlangRandomVariable;

  GammaVariable         m_gammaRandomVariable;

};

/**

 * \brief The propagation loss is fixed. The user can set received power level.

 */ 

class FixedRssLossModel : public PropagationLossModel

{

public:

  static TypeId GetTypeId (void);

  FixedRssLossModel ();

  virtual ~FixedRssLossModel ();

  /**

   * \param rss (dBm) the received signal strength

   *

   * Set the RSS.

   */

  void SetRss (double rss);

private:

  FixedRssLossModel (const FixedRssLossModel &o);

  FixedRssLossModel & operator = (const FixedRssLossModel &o);

  virtual double DoCalcRxPower (double txPowerDbm,

                                Ptr<MobilityModel> a,

                                Ptr<MobilityModel> b) const;

  double m_rss;

};

} // namespace ns3

#endif /* PROPAGATION_LOSS_MODEL_H */