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Wireless Multi-Antenna Channels Modeling and Simulation

ISBN-10: 0470697202

ISBN-13: 9780470697207

Edition: 2010

Authors: Serguei Primak, Valeri Kontorovich

List price: $90.95
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Description:

Wireless MultiAntenna Channels: Modeling and Simulation focuses on modeling and simulation of multiple antennas channels, including multiple input multiple output (MIMO) communication channels and impact of such models on channel estimation and system performance. Both narrowband and wideband models are discussed. The book covers topics related to modeling of MIMO channel, their numerical simulation, estimation and prediction, as well as applications to receive diversity and spacetime coding techniques. Contains significant fundamental/background material, as well as novel research coverage, which make the book suitable for both graduate students and researchers Addresses issues such as keyhole, correlated and non i.i.d. channels in the frame of the Generalized Gaussian approach Provides a unique treatment of generalized Gaussian channels and orthogonal channel representation Reviews different interpretations of scattering environment, including geometrical models
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Book details

List price: $90.95
Copyright year: 2010
Publisher: John Wiley & Sons, Limited
Publication date: 10/21/2011
Binding: Hardcover
Pages: 272
Size: 6.40" wide x 9.52" long x 0.86" tall
Weight: 1.232
Language: English

About the Series Editors
Introduction
General remarks
Signals, interference, and types of parallel channels
Four-parametric model of a SISO channel
Multipath propagation
Random walk approach to modeling of scattering field
Random walk in two dimensions as a model for scattering field
Phase distribution and scattering strength
Distribution of intensity
Distribution of the random phase
Gaussian case
Four-parametric distribution family
Distribution of the magnitude
Distribution of the phase
Moment generating function, moments and cumulants of four-parametric distribution
Some aspects of multiple scattering propagation
Models of MIMO channels
General classification of MIMO channel models
Physical models
Deterministic models
Geometry-based stochastic models
Analytical models
Channel matrix model
Geometrical phenomenological models
Scattering from rough surfaces
On the role of trigonometric polynomials in analysis and simulation of MIMO channels
Measures of dependency
Non-negative trigonometric polynomials and their use in estimation of AoD and AoA distribution
Approximation of marginal PDF using non-negative polynomials
Canonical expansions of bivariate distributions and the structure MIMO channel covariance matrix
Canonical variables and expansion
General structure of the full covariance matrix
Relationship to other models
Bivariate von Mises distribution with correlated transmit and receive sides
Single cluster scenario
Multiple clusters scenario
Bivariate uniform distributions
Harmonic coupling
Markov-type bivariate density
Analytical expression for the diversity measure of an antenna array
Relation of the shape of the spatial covariance function to trigonometric moments
Approximation of the diversity measure for a large number of antennas
Examples
Leading term analysis of degrees of freedom
Effect of AoA/AoD dependency on the SDoF
Space-time covariance function
Basic equation
Approximations
Examples: synthetic data and uniform linear array
Approximation of a matrix by a Toeplitz matrix
Asymptotic expansions of diversity measure
Distributed scattering model
Modeling of wideband multiple channels
Standard models of channels
COST 259/273
3GPPSCM
WINNER channel models
MDPSS based wideband channel simulator
Geometry of the problem
Statistical description
Multi-cluster environment
Simulation of dynamically changing environment
Measurement based simulator
Examples
Two cluster model
Environment specified by joint A0A/A0D/T0A distribution
Measurement based simulator
Appendix A: simulation parameters
Capacity of communication channels
Introduction
Ergodic capacity of MIMO channel
Capacity of a constant (static) MIMO channel
Alternative normalization
Capacity of a static MIMO channel under different operation modes
Ergodic capacity of a random channel
Ergodic capacity of MIMO channels
Asymptotic analysis of capacity and outage capacity
Effects of MIMO models and their parameters on the predicted capacity of MIMO channels
Channel estimation and effective SNR
Achievable rates in Rayleigh channels with partial CSI
Examples
Time evolution of capacity
Time evolution of capacity in SISO channels
SISO channel capacity evolution
Sparse MIMO channel model
Statistical properties of capacity
Some mathematical expressions
Time-varying statistics
Unordered eigenvalues
Single cluster capacity LCR and AFD
Approximation of multi-cluster capacity LCR and AFD
Statistical simulation results
Estimation and prediction of communication channels
General remarks on estimation of time-varying channels
Velocity estimation
Velocity estimation based on the covariance function approximation
Estimation based on reflection coefficients
K-factor estimation
Moment matching estimation
I/Q based methods
Estimation of four-parametric distributions
Estimation of narrowband MIMO channels
Superimposed pilot estimation scheme
LS estimation
Scaled least-square (SLS) estimation
Minimum MSE
Relaxed MMSE estimators
Using frames for channel state estimation
Properties of the spectrum of a mobile channel
Frames based on DPSS
Discrete prolate spheroidal sequences
Numerical simulation
Effects of prediction and estimation errors on performance of communication systems
Kolmogorov-Szeg�-Krein formula
Prediction error for different antennas and scattering characteristics
SISO channel
SIMO channel
MISO channel
MIMO channel
Summary of infinite horizon prediction results
Eigenstructure of two cluster correlation matrix
Preliminary comments on finite horizon prediction
SISO channel prediction
Wiener filter
Single pilot prediction in a two cluster environment
Single cluster prediction with multiple past samples
Two cluster prediction with multiple past samples
Role of oversampling
What is the narrowband signal for a rectangular array?
Prediction using the UIU model
Separable covariance matrix
1 � 2 unseparable example
Large number of antennas: no noise
Large number of antennas: estimation in noise
Effects of the number of antennas, scattering geometry, and observation time on the quality of prediction
Numerical simulations
SISO channel single cluster
Two cluster prediction
Wiener estimator
Approximation of the Wiener filter
Zero order approximation
Perturbation solution
Element-wise prediction of separable process
Effect of prediction and estimation errors on capacity calculations
Channel estimation and effective SNR
System model
Estimation error
Effective SNR
Achievable rates in Rayleigh channels with partial CSI
No CSI at the transmitter
Partial CSI at the transmitter
Optimization of the frame length
Examples
P(0, 0) Estimation
Effect of non-uniform scattering
Conclusions
Appendix A: Szeg� summation formula
Appendix B: matrix inversion lemma
Coding, modulation, and signaling over multiple channels
Signal constellations and their characteristics
Performance of OSTBC in generalized Gaussian channels and hardening effect
Introduction
Channel representation
Probability of error
Hardening effect
Differential time-space modulation (DTSM) and an effective solution for the non-coherent MIMO channel
Introduction to DTSM
Performance of autocorrelation receiver of DSTM in generalized Gaussian channels
Comments on MIMO channel model
Differential space-time modulation
Performance of DTSM
Numerical results and discussions
Some comments
Bibliography
Index