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Advanced Wireless Communications : 4G Technologies.

Author: Savo G Glisic
Publisher: Hoboken : John Wiley & Sons, Incorporated, 2005. ©2004
Edition/Format:   eBook : Document : English : 1st edView all editions and formats
Summary:
The wireless community is on the verge of the standardization of fourth generation (4G) systems. Research has generated a number of solutions for significant improvement of system performance. The development of enabling technologies such as adaptive coding and modulation, iterative (turbo) decoding algorithms and space-time coding, means that industry can now implement these solutions. Advanced Wireless
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Glisic, Savo G.
Advanced Wireless Communications : 4G Technologies.
Hoboken : John Wiley & Sons, Incorporated, ©2005
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Savo G Glisic
ISBN: 9780470867778 0470867779
OCLC Number: 1056937441
Notes: 7.6.11 Single-carrier frequency domain equalized space-time block coding SC FDE STBC.
Description: 1 online resource (879 pages)
Contents: Advanced Wireless Communications --
Contents --
Preface --
PART I ADAPTIVE MODULATION AND CODING --
1 Fundamentals --
1.1 4G and the book layout --
1.2 General structure of 4G signals --
1.2.1 Advanced time division multiple access (ATDMA) --
1.2.2 Code division multiple access (CDMA) --
1.2.3 Orthogonal frequency division multiplexing (OFDM) --
1.2.4 Multicarrier CDMA (MC CDMA) --
1.2.5 Ultra wide band (UWB) signals --
2 Adaptive Coding --
2.1 Adaptive and reconfigurable block coding --
2.2 Adaptive and reconfigurable convolutional codes --
2.2.1 Punctured convolutional codes /code reconfigurability --
2.2.2 Maximum likelihood decoding/Viterbi algorithm --
2.2.3 Systematic recursive convolutional codes --
2.3 Concatenated codes with interleavers --
2.3.1 The iterative decoding algorithm --
2.4 Adaptive coding, practice and prospects --
Appendix 2.1: Maximum a posteriori detection --
The BCJR algorithm --
3 Adaptive and Reconfigurable Modulation --
3.1 Coded modulation --
3.1.1 Euclidean distance --
3.1.2 Examples of TCM schemes --
3.1.3 Set partitioning --
3.1.4 Representation of TCM --
3.1.5 TCM with multidimensional constellation --
3.2 Adaptive coded modulation for fading channels --
3.2.1 Maintaining a fixed distance --
3.2.2 Information rate --
4 Space-Time Coding --
4.1 Diversity gain --
4.1.1 Two branch transmit diversity scheme with one receiver --
4.1.2 Two transmitters and M receivers --
4.2 Space-Time Coding --
4.2.1 The system model --
4.2.2 The case of independent fade coefficients --
4.2.3 Rayleigh fading --
4.2.4 Design criteria for Rayleigh space-time codes --
4.2.5 Code construction --
4.2.6 Reconfiguration efficiency of space-time coding --
4.2.7 Delay diversity --
4.3 Space-time block codes from orthogonal designs --
4.3.1 The channel model and the diversity criterion --
4.3.2 Real orthogonal designs. 4.3.3 Space-time encoder --
4.3.4 The diversity order --
4.3.5 The decoding algorithm --
4.3.6 Linear processing orthogonal designs --
4.3.7 Generalized real orthogonal designs --
4.3.8 Encoding --
4.3.9 The Alamouti scheme --
4.3.10 Complex orthogonal designs --
4.3.11 Generalized complex orthogonal designs --
4.3.12 Special codes --
4.3.13 Performance results --
4.4 Channel estimation imperfections --
4.4.1 Channel estimator --
4.5 Quasi-orthogonal space-time block codes --
4.5.1 Decoding --
4.5.2 Decision metric --
4.6 Space-time convolutional codes --
4.7 Algebraic space-time codes --
4.7.1 Full spatial diversity --
4.7.2 QPSK modulation --
4.8 Differential space-time modulation --
4.8.1 The encoding algorithm --
4.8.2 Differential decoding --
4.9 Multiple transmit antenna differential detection from generalized orthogonal designs --
4.9.1 Differential encoding --
4.9.2 Received signal --
4.9.3 Orthogonality --
4.9.4 Encoding --
4.9.5 Differential decoding --
4.9.6 Received signal --
4.9.7 Demodulation --
4.9.8 Multiple receive antennas --
4.9.9 The number of transmit antennas lower than the number of symbols --
4.9.10 Final result --
4.9.11 Real constellation set --
4.10 Layered space-time coding --
4.10.1 Receiver complexity --
4.10.2 Group interference suppression --
4.10.3 Suppression method --
4.10.4 The null space --
4.10.5 Receiver --
4.10.6 Decision metric --
4.10.7 Multilayered space-time coded modulation --
4.10.8 Diversity gain --
4.10.9 Adaptive reconfigurable transmit power allocation --
4.11 Concatenated space-time block coding --
4.11.1 System model --
4.11.2 Product sum distance --
4.11.3 Error rate bound --
4.11.4 The case of low SNR --
4.11.5 Code design --
4.12 Estimation of MIMO channel --
4.12.1 System model --
4.12.2 Training --
4.12.3 Performance measure --
4.12.4 Definitions --
4.12.5 Channel estimation error. 4.12.6 Error statistic --
4.12.7 Results --
4.13 Space-time codes for frequency selective channels --
4.13.1 Diversity gain properties --
4.13.2 Coding gain properties --
4.13.3 Space-time trellis code design --
4.14 Optimization of a MIMO system --
4.14.1 The channel model --
4.14.2 Gain optimization by singular value decomposition (SVD) --
4.14.3 The general (M, N) case --
4.14.4 Gain optimization by iteration for a reciprocal channel --
4.14.5 Spectral efficiency of parallel channels --
4.14.6 Capacity of the (M, N) array --
PART II MULTIPLE ACCESS --
5 Code Division Multiple Access --
CDMA --
5.1 Pseudorandom sequences --
5.1.1 Binary shift register sequences --
5.1.2 Properties of binary maximal length sequences --
5.1.3 Crosscorrelation spectra --
5.1.4 Maximal connected sets of m-sequences --
5.1.5 Gold sequences --
5.1.6 Gold-like and dual-BCH sequences --
5.1.7 Kasami sequences --
5.1.8 JPL sequences --
5.1.9 Kronecker sequences --
5.1.10 Walsh functions --
5.1.11 Optimum PN sequences --
5.1.12 Golay code --
5.2 Multiuser CDMA receivers --
5.2.1 Synchronous CDMA channels --
5.2.2 The decorrelating detector --
5.2.3 The optimum linear multiuser detector --
5.2.4 Multistage detection in asynchronous CDMA [400] --
5.2.5 Non-coherent detector --
5.2.6 Non-coherent detection in asynchronous multiuser channels [402] --
5.2.7 Multiuser detection in frequency non-selective Rayleigh fading channels --
5.2.8 Multiuser detection in frequency selective Rayleigh fading channels --
5.3 Minimum mean square error (MMSE) linear multiuser detection --
5.3.1 System model in multipath fading channels --
5.3.2 MMSE detector structures --
5.3.3 Spatial processing --
5.4 Single user LMMSE receivers for frequency selective fading channels --
5.4.1 Adaptive precombining LMMSE receivers --
5.4.2 Blind least squares receivers --
5.4.3 Least squares (LS) receiver. 5.4.4 Method based on the matrix inversion lemma --
5.5 Signal subspace-based channel estimation for CDMA systems --
5.5.1 Estimating the signal subspace --
5.5.2 Channel estimation --
Appendix 5.1: Linear and matrix algebra --
Definitions --
Special matrices --
Matrix manipulation and formulas --
Theorems --
Eigendecomposition of matrices --
Calculation of eigenvalues and eigenvectors --
6 Time Division Multiple Access --
TDMA --
6.1 Equalization in the digital data transmission system --
6.1.1 Zero-forcing equalizers --
6.2 LMS equalizer --
6.2.1 Signal model --
6.2.2 Adaptive weight adjustment --
6.2.3 Automatic systems --
6.2.4 Iterative algorithm --
6.2.5 The LMS algorithm --
6.2.6 Decision feedback equalizer (DFE) --
6.2.7 Blind equalizers --
6.3 Detection for a statistically known, time varying channel --
6.3.1 Signal model --
6.3.2 Channel model --
6.3.3 Statistical description of the received sequence --
6.3.4 The ML sequence (block) estimator for a statistically known channel --
6.4 LMS-adaptive MLSE equalization on multipath fading channels --
6.4.1 System and channel models --
6.4.2 Adaptive channel estimator and LMS estimator model --
6.4.3 The channel prediction algorithm --
6.5 Adaptive channel identification and data demodulation --
6.5.1 System model --
6.5.2 Joint channel and data estimation --
6.5.3 Data estimation and tracking for a fading channel --
6.5.4 The static channel environment --
6.5.5 The time varying channel environment --
6.6 Turbo equalization --
6.6.1 Signal format --
6.6.2 Equivalent discrete time channel model --
6.6.3 Equivalent system state representations --
6.6.4 Turbo equalization --
6.6.5 Viterbi algorithm --
6.6.6 Iterative implementation of turbo equalization --
6.6.7 Performance --
6.7 Kalman filter based joint channel estimation and data detection over fading channels --
6.7.1 Channel model. 6.7.2 The received signal --
6.7.3 Channel estimation alternatives --
6.7.4 Implementing the estimator --
6.7.5 The Kalman filter --
6.7.6 Implementation issues --
6.8 Equalization using higher order signal statistics --
6.8.1 Problem statement --
6.8.2 Signal model --
6.8.3 Derivation of algorithms for DFE --
6.8.4 The equalizer coefficients --
6.8.5 Stochastic gradient DFE adaptive algorithms --
6.8.6 Convergence analysis --
6.8.7 Kurtosis-based algorithm --
6.8.8 Performance results --
7 Orthogonal Frequency Divison Multiplexing --
OFDM and Multicarrier CDMA --
7.1 Timing and frequency offset in OFDM --
7.1.1 Robust frequency and timing synchronization for OFDM --
7.2 Fading channel estimation for OFDM systems --
7.2.1 Statistics of mobile radio channels --
7.2.2 Diversity receiver --
7.2.3 MMSE channel estimation --
7.2.4 FIR channel estimator --
7.2.5 System performance --
7.2.6 Reference generation --
7.3 64 DAPSK and 64 QAM modulated OFDM signals --
7.4 Space-time coding with OFDM signals --
7.4.1 Signal and channel parameters --
7.4.2 The wireless asynchronous transfer mode system --
7.4.3 Space-time coded adaptive modulation for OFDM --
7.4.4 Turbo and space-time coded adaptive OFDM --
7.5 Layered space-time coding for MIMO OFDM --
7.5.1 System model (two times two transmit antennas) --
7.5.2 Interference cancellation --
7.5.3 Four transmit antennas --
7.6 Space-time coded TDMA/OFDM reconfiguration efficiency --
7.6.1 Frequency selective channel model --
7.6.2 Front end prefilter --
7.6.3 Time-invariant channel --
7.6.4 Optimization problem --
7.6.5 Average channel --
7.6.6 Prefiltered M-BCJR equalizer --
7.6.7 Decision --
7.6.8 Prefiltered MLSE/DDFSE equalizer complexity --
7.6.9 Delayed decision feedback sequence estimation (DDFSE) --
7.6.10 Equalization schemes for STBC.

Abstract:

The wireless community is on the verge of the standardization of fourth generation (4G) systems. Research has generated a number of solutions for significant improvement of system performance. The development of enabling technologies such as adaptive coding and modulation, iterative (turbo) decoding algorithms and space-time coding, means that industry can now implement these solutions. Advanced Wireless Communications: 4G Technologies focuses on the system elements that provide adaptability and reconfigurability and discusses how these features can improve 4G system performance. There are several different systems comprising 4G, including adaptive WCDMA (Wideband Code Division Multiple Access), ATDMA (Adaptive Time Division Multiple Access), Multicarrier (OFDMA) and Ultra Wide Band (UWB) receiver elements. This book provides a comparative study of these technologies and focuses on their future co-existence. Topics covered include: Space Time Coding, including discussions on diversity gain, the encoding and transmission sequence, the combining s cheme and ML decision rule for two-branch transmit diversity scheme with one and M receivers. Ultra Wide Band Radio, UWB multiple access in Gaussian channels, the UWB channel, UWB system with M-ary modulation, M-ary PPM UWB multiple access, coded UWB schemes, multi-user detection in UWB radio, UWB with space time processing and beam forming for UWB radio. Antenna array signal processing with focus on Space-Time receivers for CDMA communications, MUSIC and ESPRIT DOA estimation, joint array combining and MLSE receivers, joint combiner and channel response estimation and complexity reduction in the wide-band beam forming Channel modeling and measurement, adaptive MAC, adaptive routing and TCP layer are also addressed. This book will supply the reader with a comprehensive understanding of the relationship.

Between the systems performance, its complexity/reliability and cost-effectiveness. It gives an insight into the impact of existing and new technologies on the receiver structure and provides an understanding of current approaches and evolving directions for personal and indoor communication.

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