同济大学：《传播信道特征估计和建模》课程教学资源（课件讲稿）Chapter 1 Introduction - History of Channel Characterization and Modeling

@月海大等 Chapter 1 Introduction History of Channel Characterization and Modeling Graduate course:Propagation Channel Characterization,Parameter Estimation and Modeling 3/199

Graduate course: Propagation Channel Characterization, Parameter Estimation and Modeling 3 / 199 Chapter 1 Introduction : History of Channel Characterization and Modeling

@月命大凳 Course scope ■Motivation Characteristics of the propagation channel is of great importance Fast-growing wireless communications pose more demanding on channel characteristics ■Content of the course Fundamentals for both empirical measurement-based and theoretical scattering-based channel modeling Updated channel models that can be practically used for simulations Highlights the on-going trends with some fresh research results Graduate course:Propagation Channel Characterization,Parameter Estimation and Modeling 4/199

Course scope Graduate course: Propagation Channel Characterization, Parameter Estimation and Modeling 4 / 199 ■ Motivation ◆ Characteristics of the propagation channel is of great importance ◆ Fast-growing wireless communications pose more demanding on channel characteristics ■ Content of the course ◆ Fundamentals for both empirical measurement-based and theoretical scattering-based channel modeling ◆ Updated channel models that can be practically used for simulations ◆ Highlights the on-going trends with some fresh research results

@月冷大学 Importance of channel characterization Application of statistical characteristics of the channels in system design ◆path loss model ◆shadowing models multipath fading models ◆delay spread models Doppler frequency spread models cluster-based bidirectional models Usage of instantaneous knowledge of the channel Equalization during communications Channel maps for deterministic channel playback Fingerprinting for localization Graduate course:Propagation Channel Characterization,Parameter Estimation and Modeling 5/199

Importance of channel characterization Graduate course: Propagation Channel Characterization, Parameter Estimation and Modeling 5 / 199 ■ Application of statistical characteristics of the channels in system design ◆ path loss model ◆ shadowing models ◆ multipath fading models ◆ delay spread models ◆ Doppler frequency spread models ◆ cluster-based bidirectional models ■ Usage of instantaneous knowledge of the channel ◆ Equalization during communications ◆ Channel maps for deterministic channel playback ◆ Fingerprinting for localization

@月命大凳 SISO channel models ■ Fading in frequency(FDMA),1968 Okumura Fading in outdoor region,1977 Suzuki SISO in indoor propagation environments,1987 Saleh Discrete models,1975 Cox Indoor manufacturing environments,1991 Yegani Delay and Doppler domain,1973 Cox Polarization characteristics of channel,1970 Lee,2001 Andrews Graduate course:Propagation Channel Characterization,Parameter Estimation and Modeling 6/199

SISO channel models Graduate course: Propagation Channel Characterization, Parameter Estimation and Modeling 6 / 199 ■ Fading in frequency (FDMA), 1968 Okumura ■ Fading in outdoor region, 1977 Suzuki ■ SISO in indoor propagation environments, 1987 Saleh ■ Discrete models, 1975 Cox ■ Indoor manufacturing environments, 1991 Yegani ■ Delay and Doppler domain, 1973 Cox ■ Polarization characteristics of channel, 1970 Lee, 2001 Andrews

@月傍大学 Spatial channel models ■DoA problems,1970's ■MlM0,1990's Geometry-based channel modeling (GBSM),1990's Spatial-spectral analysis methods Periodogra,Schuster1898 Correlogram,Chatfield1989 Subspace-based method,Paulraj1986 Expectation-maximization (EM)algorithm,Moon97, Frenkel1999 Space-alternating generalized expectation-maximization (SAGE)algorithm FeHe94,FITs-99 3GPP TR 25.996 models,2007 WINNER II spatial channel model-enhanced (SCME),2009 ITU IMT-Advanced models,2010 COST 2100 models,2012 Graduate course:Propagation Channel Characterization,Parameter Estimation and Modeling 7/199

Spatial channel models Graduate course: Propagation Channel Characterization, Parameter Estimation and Modeling 7 / 199 ■ DoA problems, 1970’s ■ MIMO, 1990’s ■ Geometry-based channel modeling (GBSM), 1990’s ■ Spatial-spectral analysis methods ◆ Periodogra, Schuster1898 ◆ Correlogram, Chatfield1989 ◆ Subspace-based method, Paulraj1986 ◆ Expectation-maximization (EM) algorithm, Moon97, Frenkel1999 ◆ Space-alternating generalized expectation-maximizatio n (SAGE) algorithm FeHe94, FlTs-99 ■ 3GPP TR 25.996 models, 2007 ■ WINNER II spatial channel model-enhanced (SCME), 2009 ■ ITU IMT-Advanced models, 2010 ■ COST 2100 models, 2012 ■

@月命大凳 Other channel models Multi-link channel model Distributed channel model ■Relay channel model Non-stationary channel model Reciprocity channels model ■Massive MIMO model Graduate course:Propagation Channel Characterization,Parameter Estimation and Modeling 8/199

Other channel models Graduate course: Propagation Channel Characterization, Parameter Estimation and Modeling 8 / 199 ■ Multi-link channel model ■ Distributed channel model ■ Relay channel model ■ Non-stationary channel model ■ Reciprocity channels model ■ Massive MIMO model