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MIMO-OFDM Wireless Communications with MATLAB [Kõva köide]

, , , (Chung-Ang University, Korea)
  • Formaat: Hardback, 544 pages, kõrgus x laius x paksus: 252x173x28 mm, kaal: 943 g
  • Sari: IEEE Press
  • Ilmumisaeg: 19-Oct-2010
  • Kirjastus: Wiley-IEEE Press
  • ISBN-10: 0470825618
  • ISBN-13: 9780470825617
Teised raamatud teemal:
  • Formaat: Hardback, 544 pages, kõrgus x laius x paksus: 252x173x28 mm, kaal: 943 g
  • Sari: IEEE Press
  • Ilmumisaeg: 19-Oct-2010
  • Kirjastus: Wiley-IEEE Press
  • ISBN-10: 0470825618
  • ISBN-13: 9780470825617
Teised raamatud teemal:
MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). In MIMO-OFDM Wireless Communications with MATLAB®, the authors provide a comprehensive introduction to the theory and practice of wireless channel modeling, OFDM, and MIMO, using MATLAB® programs to simulate the various techniques on MIMO-OFDM systems.One of the only books in the area dedicated to explaining simulation aspects Covers implementation to help cement the key concepts Uses materials that have been classroom-tested in numerous universities Provides the analytic solutions and practical examples with downloadable MATLAB® codes Simulation examples based on actual industry and research projects Presentation slides with key equations and figures for instructor use MIMO-OFDM Wireless Communications with MATLAB® is a key text for graduate students in wireless communications. Professionals and technicians in wireless communication fields, graduate students in signal processing, as well as senior undergraduates majoring in wireless communications will find this book a practical introduction to the MIMO-OFDM techniques.Instructor materials and MATLAB® code examples available for download at www.wiley.com/go/chomimo
Preface xiii
Limits of Liability and Disclaimer of Warranty of Software xv
1 The Wireless Channel: Propagation and Fading
1(24)
1.1 Large-Scale Fading
4(11)
1.1.1 General Path Loss Model
4(4)
1.1.2 Okumura/Hata Model
8(2)
1.1.3 IEEE 802.16d Model
10(5)
1.2 Small-Scale Fading
15(10)
1.2.1 Parameters for Small-Scale Fading
15(1)
1.2.2 Time-Dispersive vs. Frequency-Dispersive Fading
16(3)
1.2.3 Statistical Characterization and Generation of Fading Channel
19(6)
2 SISO Channel Models
25(46)
2.1 Indoor Channel Models
25(15)
2.1.1 General Indoor Channel Models
26(2)
2.1.2 IEEE 802.11 Channel Model
28(2)
2.1.3 Saleh-Valenzuela (S-V) Channel Model
30(5)
2.1.4 UWB Channel Model
35(5)
2.2 Outdoor Channel Models
40(31)
2.2.1 FWGN Model
41(9)
2.2.2 Jakes Model
50(4)
2.2.3 Ray-Based Channel Model
54(7)
2.2.4 Frequency-Selective Fading Channel Model
61(4)
2.2.5 SUI Channel Model
65(6)
3 MIMO Channel Models
71(40)
3.1 Statistical MIMO Model
71(13)
3.1.1 Spatial Correlation
73(3)
3.1.2 PAS Model
76(8)
3.2 I-METRA MIMO Channel Model
84(13)
3.2.1 Statistical Model of Correlated MIMO Fading Channel
84(4)
3.2.2 Generation of Correlated MIMO Channel Coefficients
88(2)
3.2.3 I-METRA MIMO Channel Model
90(4)
3.2.4 3GPP MIMO Channel Model
94(3)
3.3 SCM MIMO Channel Model
97(14)
3.3.1 SCM Link-Level Channel Parameters
98(4)
3.3.2 SCM Link-Level Channel Modeling
102(3)
3.3.3 Spatial Correlation of Ray-Based Channel Model
105(6)
4 Introduction to OFDM
111(42)
4.1 Single-Carrier vs. Multi-Carrier Transmission
111(10)
4.1.1 Single-Carrier Transmission
111(4)
4.1.2 Multi-Carrier Transmission
115(5)
4.1.3 Single-Carrier vs. Multi-Carrier Transmission
120(1)
4.2 Basic Principle of OFDM
121(21)
4.2.1 OFDM Modulation and Demodulation
121(5)
4.2.2 OFDM Guard Interval
126(6)
4.2.3 OFDM Guard Band
132(4)
4.2.4 BER of OFDM Scheme
136(3)
4.2.5 Water-Filling Algorithm for Frequency-Domain Link Adaptation
139(3)
4.3 Coded OFDM
142(1)
4.4 OFDMA: Multiple Access Extensions of OFDM
143(7)
4.4.1 Resource Allocation - Subchannel Allocation Types
145(1)
4.4.2 Resource Allocation - Subchannelization
146(4)
4.5 Duplexing
150(3)
5 Synchronization for OFDM
153(34)
5.1 Effect of STO
153(3)
5.2 Effect of CFO
156(6)
5.2.1 Effect of Integer Carrier Frequency Offset (IFO)
159(1)
5.2.2 Effect of Fractional Carrier Frequency Offset (FFO)
160(2)
5.3 Estimation Techniques for STO
162(8)
5.3.1 Time-Domain Estimation Techniques for STO
162(6)
5.3.2 Frequency-Domain Estimation Techniques for STO
168(2)
5.4 Estimation Techniques for CFO
170(7)
5.4.1 Time-Domain Estimation Techniques for CFO
170(3)
5.4.2 Frequency-Domain Estimation Techniques for CFO
173(4)
5.5 Effect of Sampling Clock Offset
177(1)
5.5.1 Effect of Phase Offset in Sampling Clocks
177(1)
5.5.2 Effect of Frequency Offset in Sampling Clocks
178(1)
5.6 Compensation for Sampling Clock Offset
178(2)
5.7 Synchronization in Cellular Systems
180(7)
5.7.1 Downlink Synchronization
180(3)
5.7.2 Uplink Synchronization
183(4)
6 Channel Estimation
187(22)
6.1 Pilot Structure
187(3)
6.1.1 Block Type
187(1)
6.1.2 Comb Type
188(1)
6.1.3 Lattice Type
189(1)
6.2 Training Symbol-Based Channel Estimation
190(5)
6.2.1 LS Channel Estimation
190(1)
6.2.2 MMSE Channel Estimation
191(4)
6.3 DFT-Based Channel Estimation
195(4)
6.4 Decision-Directed Channel Estimation
199(1)
6.5 Advanced Channel Estimation Techniques
199(10)
6.5.1 Channel Estimation Using a Superimposed Signal
199(2)
6.5.2 Channel Estimation in Fast Time-Varying Channels
201(3)
6.5.3 EM Algorithm-Based Channel Estimation
204(2)
6.5.4 Blind Channel Estimation
206(3)
7 PAPR Reduction
209(42)
7.1 Introduction to PAPR
209(15)
7.1.1 Definition of PAPR
210(6)
7.1.2 Distribution of OFDM Signal
216(2)
7.1.3 PAPR and Oversampling
218(4)
7.1.4 Clipping and SQNR
222(2)
7.2 PAPR Reduction Techniques
224(27)
7.2.1 Clipping and Filtering
224(7)
7.2.2 PAPR Reduction Code
231(2)
7.2.3 Selective Mapping
233(1)
7.2.4 Partial Transmit Sequence
234(4)
7.2.5 Tone Reservation
238(1)
7.2.6 Tone Injection
239(2)
7.2.7 DFT Spreading
241(10)
8 Inter-Cell Interference Mitigation Techniques
251(12)
8.1 Inter-Cell Interference Coordination Technique
251(6)
8.1.1 Fractional Frequency Reuse
251(3)
8.1.2 Soft Frequency Reuse
254(1)
8.1.3 Flexible Fractional Frequency Reuse
255(1)
8.1.4 Dynamic Channel Allocation
256(1)
8.2 Inter-Cell Interference Randomization Technique
257(3)
8.2.1 Cell-Specific Scrambling
257(1)
8.2.2 Cell-Specific Interleaving
258(1)
8.2.3 Frequency-Hopping OFDMA
258(2)
8.2.4 Random Subcarrier Allocation
260(1)
8.3 Inter-Cell Interference Cancellation Technique
260(3)
8.3.1 Interference Rejection Combining Technique
260(2)
8.3.2 IDMA Multiuser Detection
262(1)
9 MIMO: Channel Capacity
263(18)
9.1 Useful Matrix Theory
263(2)
9.2 Deterministic MIMO Channel Capacity
265(7)
9.2.1 Channel Capacity when CSI is Known to the Transmitter Side
266(4)
9.2.2 Channel Capacity when CSI is Not Available at the Transmitter Side
270(1)
9.2.3 Channel Capacity of SIMO and MISO Channels
271(1)
9.3 Channel Capacity of Random MIMO Channels
272(9)
10 Antenna Diversity and Space-Time Coding Techniques
281(38)
10.1 Antenna Diversity
281(6)
10.1.1 Receive Diversity
283(4)
10.1.2 Transmit Diversity
287(1)
10.2 Space-Time Coding (STC): Overview
287(7)
10.2.1 System Model
287(2)
10.2.2 Pairwise Error Probability
289(3)
10.2.3 Space-Time Code Design
292(2)
10.3 Space-Time Block Code (STBC)
294(25)
10.3.1 Alamouti Space-Time Code
294(4)
10.3.2 Generalization of Space-Time Block Coding
298(4)
10.3.3 Decoding for Space-Time Block Codes
302(5)
10.3.4 Space-Time Trellis Code
307(12)
11 Signal Detection for Spatially Multiplexed MIMO Systems
319(54)
11.1 Linear Signal Detection
319(3)
11.1.1 ZF Signal Detection
320(1)
11.1.2 MMSE Signal Detection
321(1)
11.2 OSIC Signal Detection
322(5)
11.3 ML Signal Detection
327(2)
11.4 Sphere Decoding Method
329(10)
11.5 QRM-MLD Method
339(5)
11.6 Lattice Reduction-Aided Detection
344(8)
11.6.1 Lenstra-Lenstra-Lovasz (LLL) Algorithm
345(4)
11.6.2 Application of Lattice Reduction
349(3)
11.7 Soft Decision for MIMO Systems
352(21)
11.7.1 Log-Likelihood-Ratio (LLR) for SISO Systems
353(5)
11.7.2 LLR for Linear Detector-Based MIMO System
358(3)
11.7.3 LLR for MIMO System with a Candidate Vector Set
361(3)
11.7.4 LLR for MIMO System Using a Limited Candidate Vector Set
364(6)
Appendix 11 A Derivation of Equation (11.23)
370(3)
12 Exploiting Channel State Information at the Transmitter Side
373(22)
12.1 Channel Estimation on the Transmitter Side
373(2)
12.1.1 Using Channel Reciprocity
374(1)
12.1.2 CSI Feedback
374(1)
12.2 Precoded OSTBC
375(6)
12.3 Precoded Spatial-Multiplexing System
381(2)
12.4 Antenna Selection Techniques
383(12)
12.4.1 Optimum Antenna Selection Technique
384(2)
12.4.2 Complexity-Reduced Antenna Selection
386(4)
12.4.3 Antenna Selection for OSTBC
390(5)
13 Multi-User MIMO
395(24)
13.1 Mathematical Model for Multi-User MIMO System
396(1)
13.2 Channel Capacity of Multi-User MIMO System
397(4)
13.2.1 Capacity of MAC
398(1)
13.2.2 Capacity of BC
399(2)
13.3 Transmission Methods for Broadcast Channel
401(18)
13.3.1 Channel Inversion
401(3)
13.3.2 Block Diagonalization
404(4)
13.3.3 Dirty Paper Coding (DPC)
408(4)
13.3.4 Tomlinson-Harashima Precoding
412(7)
References 419(12)
Index 431
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.