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Low Complexity MIMO Detection 2012 [Kõva köide]

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  • Formaat: Hardback, 230 pages, kõrgus x laius: 235x155 mm, kaal: 553 g, XXVI, 230 p., 1 Hardback
  • Ilmumisaeg: 07-Jan-2012
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1441985824
  • ISBN-13: 9781441985828
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Low Complexity MIMO Detection 2012Suurem pilt
  • Formaat: Hardback, 230 pages, kõrgus x laius: 235x155 mm, kaal: 553 g, XXVI, 230 p., 1 Hardback
  • Ilmumisaeg: 07-Jan-2012
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1441985824
  • ISBN-13: 9781441985828
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781441985828.html
Märksõnad:
Low Complexity MIMO Detection introduces the principle of MIMO systems and signal detection via MIMO channels. This book systematically introduces the symbol detection in MIMO systems. Includes the fundamental knowledge of MIMO detection and recent research outcomes for low complexity MIMO detection.

This book systematically introduces the principle of MIMO systems and signal detection via MIMO channels. Coverage includes symbol detection in MIMO systems, fundamental knowledge of MIMO detection and recent research outcomes on low complexity MIMO detection.
1 Introduction
1(14)
1.1 MIMO Systems
1(3)
1.2 Point to Point MIMO
4(4)
1.3 Multiuser MIMO
8(2)
1.4 Outline
10(5)
Part I Point to Point MIMO
2 Background of MIMO Detection
15(28)
2.1 System Model
15(1)
2.2 ML Detection
16(4)
2.2.1 Exhaustive Search Approach
16(1)
2.2.2 Performance Analysis
17(3)
2.3 Linear Detection
20(3)
2.3.1 ZF Detection
20(1)
2.3.2 MMSE Detection
21(1)
2.3.3 Performance Analysis
22(1)
2.4 SIC Detection
23(13)
2.4.1 QR Factorization
24(1)
2.4.2 ZF-SIC
24(4)
2.4.3 MMSE-SIC
28(1)
2.4.4 Ordering
29(2)
2.4.5 Performance Analysis
31(5)
2.5 BER Versus SNR Simulation Results
36(6)
2.6 Conclusion and Remarks
42(1)
3 List and Lattice Reduction-Based Methods
43(48)
3.1 List-Based Detection
43(13)
3.1.1 Detection Algorithms
43(3)
3.1.2 Ordering
46(2)
3.1.3 Subdetectors
48(4)
3.1.4 Performance Analysis
52(2)
3.1.5 Simulation Results
54(2)
3.2 Lattice Reduction-Based Detection
56(34)
3.2.1 MIMO Systems with Lattice
56(2)
3.2.2 Lattice Reduction-Based MIMO Detection
58(6)
3.2.3 Lattice Reduction Schemes for Two Basis Systems
64(5)
3.2.4 Gaussian Lattice Reduction for Two Basis Systems
69(5)
3.2.5 LLL and CLLL Algorithms
74(5)
3.2.6 Performance Evaluation
79(7)
3.2.7 Simulation Results
86(4)
3.3 Conclusion and Remarks
90(1)
4 Partial MAP-Based Detection
91(22)
4.1 MAP Detection
91(1)
4.2 Partial MAP Detection
92(7)
4.2.1 The Case of 2 × 2 MIMO
92(1)
4.2.2 General Case
93(4)
4.2.3 Theoretical Analysis
97(2)
4.3 Partial MAP-Based List Detection
99(13)
4.3.1 System Model
100(1)
4.3.2 The Case of List Length Q = 1
101(2)
4.3.3 General Case
103(4)
4.3.4 Algorithm of the Partial MAP-Based List Detection
107(3)
4.3.5 Simulation Results
110(2)
4.4 Conclusion and Remarks
112(1)
5 Lattice Reduction-Based List Detection
113(28)
5.1 Lattice Reduction-Based List Detection
114(17)
5.1.1 Algorithm Description
114(2)
5.1.2 Lattice Reduction-Based Detection
116(1)
5.1.3 List Generation in the LR Domain
117(1)
5.1.4 Impact of List Length
118(4)
5.1.5 Complexity Analysis
122(1)
5.1.6 Components of the LR-Based List Detection
122(8)
5.1.7 Simulation Results
130(1)
5.2 Error Probability-Based Column Reordering Criteria
131(8)
5.2.1 System Model with CRIS
133(1)
5.2.2 Detection Algorithm with CRIS
134(1)
5.2.3 OD-CRC
135(1)
5.2.4 EP-CRC
136(1)
5.2.5 Simulation Results
137(2)
5.3 Conclusion and Remarks
139(2)
6 Detection for Underdetermined MIMO Systems
141(28)
6.1 Joint Detection for Underdetermined MIMO Systems
143(4)
6.1.1 System Model
143(1)
6.1.2 Existing Approaches
144(2)
6.1.3 Prevoting Cancellation-Based MIMO Detection
146(1)
6.2 Selection for Prevoting Vectors Depending on SubDetectors
147(3)
6.2.1 Selection Criterion with Linear Detector
148(1)
6.2.2 Selection Criteria with LR-Based Linear and SIC Detectors
148(2)
6.3 Performance Analysis
150(8)
6.3.1 Diversity Analysis
150(7)
6.3.2 Complexity Analysis
157(1)
6.4 Simulation Results and Discussions
158(7)
6.4.1 Simulation Results
158(3)
6.4.2 Discussion
161(4)
6.5 Conclusion and Remarks
165(4)
Part II Multiuser MIMO
7 Selection Criteria of Single User
169(16)
7.1 System Model
169(1)
7.2 User Selection Criteria
170(11)
7.2.1 Maximum Mutual Information Criterion
171(1)
7.2.2 User Selection Criteria for ML Detector
172(3)
7.2.3 User Selection Criterion for Linear Detectors
175(2)
7.2.4 User Selection Criteria for LR-Based Detectors
177(4)
7.3 Simulation Results
181(2)
7.4 Conclusion and Remarks
183(2)
8 Selection Criteria of Multiple Users
185(32)
8.1 System Model
187(2)
8.2 User Selection Criteria
189(4)
8.2.1 ML and Linear Selection Criteria
190(1)
8.2.2 LR-Based Linear and SIC Selection Criteria
191(2)
8.3 LR-Based Greedy User Selection Using an Updating Method
193(10)
8.3.1 LR-Based Greedy User Selection
193(4)
8.3.2 A Complexity Efficient Method for LR Updating
197(6)
8.4 Diversity Analysis and Numerical Results
203(12)
8.4.1 Diversity Gain Analysis from Error Probability
204(6)
8.4.2 Numerical Results
210(5)
8.5 Conclusion and Remarks
215(2)
9 Conclusion of the Book
217(2)
References 219(6)
About the Authors 225(2)
Index 227
Prof. Jinho Choi is the chair of wireless in School of Engineering, Swansea University, Swansea, U.K.

Dr. Lin Bai is at the Beijing University of Aeronautics and Astronautics (BUAA), Beijing, China.