P P Vaidyanathan, See-May Phoong, Yuan-Pei Lin
Signal Processing and Optimization for Transceiver Systems
P P Vaidyanathan, See-May Phoong, Yuan-Pei Lin
Signal Processing and Optimization for Transceiver Systems
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Provides the first complete treatment of MIMO transceiver optimization, with plenty of examples, important background material, and detailed summaries.
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Provides the first complete treatment of MIMO transceiver optimization, with plenty of examples, important background material, and detailed summaries.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- Seitenzahl: 874
- Erscheinungstermin: 30. April 2010
- Englisch
- Abmessung: 250mm x 175mm x 51mm
- Gewicht: 1659g
- ISBN-13: 9780521760799
- ISBN-10: 0521760798
- Artikelnr.: 28245037
- Verlag: Cambridge University Press
- Seitenzahl: 874
- Erscheinungstermin: 30. April 2010
- Englisch
- Abmessung: 250mm x 175mm x 51mm
- Gewicht: 1659g
- ISBN-13: 9780521760799
- ISBN-10: 0521760798
- Artikelnr.: 28245037
P. P. Vaidyanathan is a Professor of Electrical Engineering at the California Institute of Technology, where he has been a faculty member since 1983. He is an IEEE Fellow and has co-authored over 400 technical papers and two books in the area of signal processing. He has received numerous awards, including the Award for Excellence in Teaching at the California Institute of Technology three times.
Part I. Communication Fundamentals: 1. Introduction
2. Review of basic ideas from digital communication
3. Digital communication systems and filter banks
4. Discrete time representations
5. Classical transceiver techniques
6. Channel capacity
7. Channel equalization with transmitter redundancy
8. The lazy precoder with a zero-forcing equalizer
Part II. Transceiver Optimization: 9. History and outline
10. Single-input single-output transceiver optimization
11. Optimal transceivers for diagonal channels
12. MMSE transceivers with zero-forcing equalizers
13. MMSE transceivers without zero forcing
14. Bit allocation and power minimization
15. Transceivers with orthonormal precoders
16. Minimization of error probability in transceivers
17. Optimization of cyclic prefix transceivers
18. Optimization of zero padded systems
19. Transceivers with decision feedback equalizers
Part III. Mathematical Background: 20. Matrix differentiation
21. Convexity, Schur convexity and majorization theory
22. Optimization with equality and inequality constraints
Part IV. Appendices: A. Inner products, norms, and inequalities
B. Matrices: a brief overview
C. Singular value decomposition
D. Properties of pseudocirculant matrices
E. Random processes
F. Wiener filtering
G. Review of concepts from sampling theory
H. Euclid's algorithm
I. Transceiver optimization
Summary and tables
Glossary and acronyms
Bibliography.
2. Review of basic ideas from digital communication
3. Digital communication systems and filter banks
4. Discrete time representations
5. Classical transceiver techniques
6. Channel capacity
7. Channel equalization with transmitter redundancy
8. The lazy precoder with a zero-forcing equalizer
Part II. Transceiver Optimization: 9. History and outline
10. Single-input single-output transceiver optimization
11. Optimal transceivers for diagonal channels
12. MMSE transceivers with zero-forcing equalizers
13. MMSE transceivers without zero forcing
14. Bit allocation and power minimization
15. Transceivers with orthonormal precoders
16. Minimization of error probability in transceivers
17. Optimization of cyclic prefix transceivers
18. Optimization of zero padded systems
19. Transceivers with decision feedback equalizers
Part III. Mathematical Background: 20. Matrix differentiation
21. Convexity, Schur convexity and majorization theory
22. Optimization with equality and inequality constraints
Part IV. Appendices: A. Inner products, norms, and inequalities
B. Matrices: a brief overview
C. Singular value decomposition
D. Properties of pseudocirculant matrices
E. Random processes
F. Wiener filtering
G. Review of concepts from sampling theory
H. Euclid's algorithm
I. Transceiver optimization
Summary and tables
Glossary and acronyms
Bibliography.
Part I. Communication Fundamentals: 1. Introduction
2. Review of basic ideas from digital communication
3. Digital communication systems and filter banks
4. Discrete time representations
5. Classical transceiver techniques
6. Channel capacity
7. Channel equalization with transmitter redundancy
8. The lazy precoder with a zero-forcing equalizer
Part II. Transceiver Optimization: 9. History and outline
10. Single-input single-output transceiver optimization
11. Optimal transceivers for diagonal channels
12. MMSE transceivers with zero-forcing equalizers
13. MMSE transceivers without zero forcing
14. Bit allocation and power minimization
15. Transceivers with orthonormal precoders
16. Minimization of error probability in transceivers
17. Optimization of cyclic prefix transceivers
18. Optimization of zero padded systems
19. Transceivers with decision feedback equalizers
Part III. Mathematical Background: 20. Matrix differentiation
21. Convexity, Schur convexity and majorization theory
22. Optimization with equality and inequality constraints
Part IV. Appendices: A. Inner products, norms, and inequalities
B. Matrices: a brief overview
C. Singular value decomposition
D. Properties of pseudocirculant matrices
E. Random processes
F. Wiener filtering
G. Review of concepts from sampling theory
H. Euclid's algorithm
I. Transceiver optimization
Summary and tables
Glossary and acronyms
Bibliography.
2. Review of basic ideas from digital communication
3. Digital communication systems and filter banks
4. Discrete time representations
5. Classical transceiver techniques
6. Channel capacity
7. Channel equalization with transmitter redundancy
8. The lazy precoder with a zero-forcing equalizer
Part II. Transceiver Optimization: 9. History and outline
10. Single-input single-output transceiver optimization
11. Optimal transceivers for diagonal channels
12. MMSE transceivers with zero-forcing equalizers
13. MMSE transceivers without zero forcing
14. Bit allocation and power minimization
15. Transceivers with orthonormal precoders
16. Minimization of error probability in transceivers
17. Optimization of cyclic prefix transceivers
18. Optimization of zero padded systems
19. Transceivers with decision feedback equalizers
Part III. Mathematical Background: 20. Matrix differentiation
21. Convexity, Schur convexity and majorization theory
22. Optimization with equality and inequality constraints
Part IV. Appendices: A. Inner products, norms, and inequalities
B. Matrices: a brief overview
C. Singular value decomposition
D. Properties of pseudocirculant matrices
E. Random processes
F. Wiener filtering
G. Review of concepts from sampling theory
H. Euclid's algorithm
I. Transceiver optimization
Summary and tables
Glossary and acronyms
Bibliography.