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Verlag: Cambridge University Press 19/04/2018, 2018
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Verlag: Artech House, Inc., Norwood, MA, U.S.A., 2000
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ISBN 10: 7121064332 ISBN 13: 9787121064333
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In den Warenkorbpaperback. Zustand: New. Ship out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.Publisher: Electronics Industry Publishing House Pub. Date: 2008-08-01 The book of mobile communication in space-time signal processing. first introduced the concept of space-time signal processing and is closely related with the development of mobile communication. then each channel of the space-time channel estimation and space-time. space-time channel capacity. space-time receiver processing. space-time processing and transport five blind space-time processing. covering the space-time signal processing. the main content and the latest developments. Book is intended for communications. electronics. automation. computer and related graduate students. teachers. researchers and engineers. but also the first semester as a graduate teaching book. Contents: Chapter 1 space-time signal processing concepts 1.1 mobile communication 1.2 One-dimensional communication signal processing limitations of 1.3 space-time signal processing concepts 1.4 book is organized References Chapter 2 space-time channel and signal model 2.1 mobile communication channel 2.1.2 Basic Characteristics 2.1.1 shadow fading effects of multipath fading and small-scale space-time 2.2 channel 2.2.1SISO channel 2.2.2SIMO channel 2.2.3MISO 2.2.5 Channel 2.2.4MIMO channel 2.3-channel multi-user ST-signal model of discrete space-time 2.3.1SISO discrete signal model 2.3.2SIMO discrete signal model 2.3.3MISO discrete signal model 2.3.4MIMO discrete signal model 2.3.5 channel matrix singular value decomposition References Chapter 3 empty 3.1 Overview 3.2 channel capacity to determine the single channel coefficient user space-time channel capacity 3.2.1 transmitter channel state know the channel receiver to ascertain the status 3.2.2 are satisfied that the transmitter and receiver channel state of the channel coefficient of 3.3 when a random space-time single-user channel capacity in M ??3.3.1 HW case large enough channel capacity rate of the statistical description of the information 3.3.2 3.4 single-user frequency-selective space-time channel capacity under the 3.5 space-related capacity of the channel model and transmitter know the channel state 3.5.1 ascertain channel receiver 3.5.2 state the transmitter and receiver do not know the channel state over 3.6 user space-time channel capacity 3.6.1 The transmitter and receiver are known channel state 3.6.2 Transmitter and receiver know the channel state to ascertain the channel state information Literature Chapter 4 4.1 Space-time channel estimation and time domain processing spatial equivalent of the space-time spectrum estimation 4.2 4.3 4.4 delay joint angle-delay estimation and spatial characteristics of DOA estimation with space-time 4.5 channel 4.6 General MIMO channel estimation estimated References Chapter 5 Overview of space-time equalization 5.1 5.3 5.2 Space-time MLSE equalization empty space-time MMSE equalizer 5.4 Performance comparison of ZF equalization and DFE equalization space-time 5.5 5.6 5.7 algorithm based on subspace approach to space-time reference two Chapter 6 space-time RAKE receiver and multi-user detection 6.1 Overview 6.2 based on space-time beamforming RAKE receiver 6.3 space-time matched filter based RAKE receiver based on RLS-Kalman algorithm 6.4 the optimal space-time RAKE receiver 6.5 space 6.6 Linear joint detection when the space-time space-time joint interference cancellation detection 6.7 References Chapter 7 of the blind space-time processing 7.1 Overview 7.2 blind space-time channel estimation 7.2.1 Subspace based blind channel estimation method of color-channel environment 7.2.2 Blind estimation of decorrelation 7.2.3 Linear Prediction based blind channel estimation for blind space-time equalization 7.3.1 7.3 based on space-time constant modulus blind equalization based blind beamforming 7.3.2 blind adaptive equalization based on 7.3.3 sequential Monte Carlo blind adaptive equaliza.