Summary

MIMO-OFDM Wireless Communications with MATLAB is comprised of three main sections. The first introduces wireless channel modeling with MATLAB, covering the characteristics of wireless channels, SISO and MIMO channel modeling. The second section discusses OFDM with MATLAB, explaining the basics before going over synchronization, channel estimation, peak-to-average power ratio, and then major techniques using MATLAB: PAPR Reduction, intercell interference coordination, randomization, and cancellation. The last section covers the application of MIMO to MATLAB, including MIMO channel capacity, space diversity and space-time codes, signal detection for spatially-multiplexed MIMO systems, space-time block codes for diversity-multiplexing trade-off, and multiuser MIMO.

Author Biography

Yong Soo Cho is a Professor of Electronic Engineering at Chung-Ang University in Seoul, Korea. He has taught OFDM for 10 years and MIMO for 5. His research interests are in the areas of digital communication, digital signal processing, and FPGA Implementation. Cho has held positions at LG Electronics, the ETRI Mobile Communication Group, the WiBro Project Group, and was Chairman of the Wireless Access Working Group in Korea. He holds a BS from Chung-Ang University, an MS from Yonsei University, and a PhD from the University of Texas at Austin, all in electronic engineering.

Jaekwon Kim is an Assistant Professor of Computer and Telecommunications Engineering at Yonsei University. Prior to that he worked at Samsung Advanced Institute of Technology with the 4G System Team. He holds a BS and MS from Chung-Ang University and a PhD from the University of Texas at Austin, all in electronic engineering.

Won Y. Yang is a Professor of Electronic Engineering at Chung-Ang University. He has written two books on MATLAB in English, and two in Korean. Yang holds a BS and MS in Electrical Engineering from Seoul National University, an MS in Applied Math and a PhD in Electrical Engineering from the University of Southern California.

Chung Gu Kang is a Professor of Radio Communication and Engineering at Korea University. Previous work experience inlcudes time in the US spent at the Aerospace Corporation and Rockwell International, where he worked on telecommunications systems development. He was also a Visiting Associate Professor at the UC San Diego. His research interests are focesed on the cross layer design issues for MIMO/multiple access schemes for mobile broadband wireless access systems and MAC/routing protocols for mobile ad hoc networks. Kang holds a BS from UC San Diego and an MS and PhD in Electrical Engineering and Computer Engineering from UC Irvine.

Preface
Limits of Liability and Disclaimer of Warranty of Software
The Wireless Channel: Propagation and Fading
Large-Scale Fading
General Path Loss Model
Okumura/Hata Model
IEEE 802.16d Model
Small-Scale Fading
Parameters for Small-Scale Fading
Time-Dispersive vs. Frequency-Dispersive Fading
Statistical Characterization and Generation of Fading Channel
SISO Channel Models
Indoor Channel Models
General Indoor Channel Models
IEEE 802.11 Channel Model
Saleh-Valenzuela (S-V) Channel Model
UWB Channel Model
Outdoor Channel Models
FWGN Model
Jakes Model
Ray-Based Channel Model
Frequency-Selective Fading Channel Model
SUI Channel Model
MIMO Channel Models
Statistical MIMO Model
Spatial Correlation
PAS Model
I-METRA MIMO Channel Model
Statistical Model of Correlated MIMO Fading Channel
Generation of Correlated MIMO Channel Coefficients
I-METRA MIMO Channel Model
3GPP MIMO Channel Model
SCM MIMO Channel Model
SCM Link-Level Channel Parameters
SCM Link-Level Channel Modeling
Spatial Correlation of Ray-Based Channel Model
Introduction to OFDM
Single-Carrier vs. Multi-Carrier Transmission
Single-Carrier Transmission
Multi-Carrier Transmission
Single-Carrier vs. Multi-Carrier Transmission
Basic Principle of OFDM
OFDM Modulation and Demodulation
OFDM Guard Interval
OFDM Guard Band
BER of OFDM Scheme
Water-Filling Algorithm for Frequency-Domain Link Adaptation
Coded OFDM
OFDMA: Multiple Access Extensions of OFDM
Resource Allocation - Subchannel Allocation Types
Resource Allocation - Subchannelization
Duplexing
Synchronization for OFDM
Effect of STO
Effect of CFO
Effect of Integer Carrier Frequency Offset (IFO)
Effect of Fractional Carrier Frequency Offset (FFO)
Estimation Techniques for STO
Time-Domain Estimation Techniques for STO
Frequency-Domain Estimation Techniques for STO
Estimation Techniques for CFO
Time-Domain Estimation Techniques for CFO
Frequency-Domain Estimation Techniques for CFO
Effect of Sampling Clock Offset
Effect of Phase Offset in Sampling Clocks
Effect of Frequency Offset in Sampling Clocks
Compensation for Sampling Clock Offset
Synchronization in Cellular Systems
Downlink Synchronization
Uplink Synchronization
Channel Estimation
Pilot Structure
Block Type
Comb Type
Lattice Type
Training Symbol-Based Channel Estimation
LS Channel Estimation
MMSE Channel Estimation
DFT-Based Channel Estimation
Decision-Directed Channel Estimation
Advanced Channel Estimation Techniques
Channel Estimation Using a Superimposed Signal
Channel Estimation in Fast Time-Varying Channels
EM Algorithm-Based Channel Estimation
Blind Channel Estimation
PAPR Reduction
Introduction to PAPR
Definition of PAPR
Distribution of OFDM Signal
PAPR and Oversampling
Clipping and SQNR
PAPR Reduction Techniques
Clipping and Filtering
PAPR Reduction Code
Selective Mapping
Partial Transmit Sequence
Tone Reservation
Tone Injection
DFT Spreading
Inter-Cell Interference Mitigation Techniques
Inter-Cell Interference Coordination Technique
Fractional Frequency Reuse
Soft Frequency Reuse
Flexible Fractional Frequency Reuse
Dynamic Channel Allocation
Inter-Cell Interference Randomization Technique
Cell-Specific Scrambling
Cell-Specific Interleaving
Frequency-Hopping OFDMA
Random Subcarrier Allocation
Inter-Cell Interference Cancellation Technique
Interference Rejection Combining Technique
IDMA Multiuser Detection
MIMO: Channel Capacity
Useful Matrix Theory
Deterministic MIMO Channel Capacity
Channel Capacity when CSI is Known to the Transmitter Side
Channel Capacity when CSI is Not Available at the Transmitter Side
Channel Capacity of SIMO and MISO Channels
Channel Capacity of Random MIMO Channels
Antenna Diversity and Space-Time Coding Techniques
Antenna Diversity
Receive Diversity
Transmit Diversity
Space-Time Coding (STC): Overview
System Model
Pairwise Error Probability
Space-Time Code Design
Space-Time Block Code (STBC)
Alamouti Space-Time Code
Generalization of Space-Time Block Coding
Decoding for Space-Time Block Codes
Space-Time Trellis Code
Signal Detection for Spatially Multiplexed MIMO Systems
Linear Signal Detection
ZF Signal Detection
MMSE Signal Detection
OSIC Signal Detection
ML Signal Detection
Sphere Decoding Method
QRM-MLD Method
Lattice Reduction-Aided Detection
Lenstra-Lenstra-Lovasz (LLL) Algorithm
Application of Lattice Reduction
Soft Decision for MIMO Systems
Log-Likelihood-Ratio (LLR) for SISO Systems
LLR for Linear Detector-Based MIMO System
LLR for MIMO System with a Candidate Vector Set
LLR for MIMO System Using a Limited Candidate Vector Set
Derivation of Equation (11.23)
Exploiting Channel State Information at the Transmitter Side
Channel Estimation on the Transmitter Side
Using Channel Reciprocity
CSI Feedback
Precoded OSTBC
Precoded Spatial-Multiplexing System
Antenna Selection Techniques
Optimum Antenna Selection Technique
Complexity-Reduced Antenna Selection
Antenna Selection for OSTBC
Multi-User MIMO
Mathematical Model for Multi-User MIMO System
Channel Capacity of Multi-User MIMO System
Capacity of MAC
Capacity of BC
Transmission Methods for Broadcast Channel
Channel Inversion
Block Diagonalization
Dirty Paper Coding (DPC)
Tomlinson-Harashima Precoding
References
Index.
Table of Contents provided by Publisher. All Rights Reserved.

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