# Coding in digital communications

This is a grouped course. It consists of several seperate subjects that share learning materials, assignments, tests etc. Below you can see information about the individual subjects that make up this subject.
##### Coding in digital communications (Main course) A2M37KDK
 Credits 5 Semesters Summer Completion Assessment + Examination Language of teaching Czech Extent of teaching 3+1c
Annotation
The course extends and deepens the topics of the basic DKM course in the following main areas. 1) The information theory builds a fundamental framework for thorough understanding the principles of the channel coding, adaptation, sharing, and diversity/multiplexing of the MIMO systems. 2) We develop advanced coding techique, particularly turbo-codes, LDPC codes and space-time codes for MIMO. 3) We explain essential principles of iterative decoding methods for turbo and LDPC codes.
Study targets
Course outlines
1. Information theory, basic definitions, entropy, mutual information.
2. Channel capacity (ergodic, nonergodic, discrete, AWGN, MIMO), coding theorems.
3. Multiuser systems, MAC and BC channel, capacity region. Channel sharing CDMA, FDMA, TDMA, SDMA. Coding and decoding strategies for MAC and BC channels (DPC codes, MU decoding).
5. Space-Time MIMO systems. Diversity, multiplexing gain, capacity. Sufficient statistic, MRC.
6. Codes on the GF(m). Polynomial representation. Properties, structures.
7. Coding/decoding algorithms for linear and cyclic codes (Hamming, BCH, RS, ...). Decoding error rate.
8. Convolutional codes (recursive, nonrecursive). Properties, structures. Polynomial representation. Transfer function.
9. Coding/decoding algorithms for convolutional codes. Decoding error rate.
10. Constellation space codes. Trellis codes TCM. Differential codes.
11. Turbo-codes, LDPC codes. Codes on graphs.
12. Iterative decoding algorithms. FBA algorithm and Soft-In Soft-Out blocks.
13. SPA algorithm on the Factor Graph.
14. Space-Time codes for MIMO (block, trellis, layered).
Exercises outlines
1. Capacity and capacity region evaluation for example channels.
2. Implementation of the adaptive modulation and coding (water-filling).
3. Implementation of the diversity reception with MRC.
4. Transfer function of the FSM code. Free distance spectrum.
5. Implementation of the turbo and LDPC code.
6. Iterative decoder (FBA, SPA/FG).
7. Evaluation of the projects.
Literature
1. J. G. Proakis: Digital Communications. McGraw-Hill. 2001
2. D. Tse, P. Viswanath: Fundamentals of Wireless Communications, Cambridge University Press, 2005
3. E. Biglieri: Coding for Wireless Channels, Springer, 2005
4. B. Vucetic, J. Yuan: Space-Time Coding, John Wiley & Sons, 2003
5. Goldsmith: Wireless communications, Cambridge University Press, 2005
6. B. Vucetic, J. Yuan: Turbo codes - principles and applications, Kluwer academic publishers, 2000
7. Oppermann I., Hamalainen M., Iinatti J.: UWB theory and applications, John Wiley & Sons, 2004
8. Meyr, H., Moeneclaey, M., Fechtel, S. A.: Digital Communication Receivers-Synchronization, Channel Estimation and Signal Processing. John Wiley. 1998
9. Mengali, U., D'Andrea, A. N.: Synchronization Techniques for Digital Receivers. Plenum Press. 1997
10. R. E. Blahut: Algebraic codes for data transmission, Cambridge University Press, 2006
11. T. M. Cover, J. A. Thomas: Elements of Information Theory, John Wiley & Sons, 1991
12. S. M. Kay: Fundamentals of statistical signal processing-estimation theory, Prentice-Hall 1993
13. S. M. Kay: Fundamentals of statistical signal processing-detection theory, Prentice-Hall 1998
Requirements
see moodle.fel.cvut.cz
##### Coding in digital communications AD2M37KDK
 Credits 5 Semesters Summer Completion Assessment + Examination Language of teaching Czech Extent of teaching 21+3c
Annotation
The course extends and deepens the topics of the basic DKM course in the following main areas. 1) The information theory builds a fundamental framework for thorough understanding the principles of the channel coding, adaptation, sharing, and diversity/multiplexing of the MIMO systems. 2) We develop advanced coding techique, particularly turbo-codes, LDPC codes and space-time codes for MIMO. 3) We explain essential principles of iterative decoding methods for turbo and LDPC codes.
Study targets
Course outlines
1. Information theory, basic definitions, entropy, mutual information.
2. Channel capacity (ergodic, nonergodic, discrete, AWGN, MIMO), coding theorems.
3. Multiuser systems, MAC and BC channel, capacity region. Channel sharing CDMA, FDMA, TDMA, SDMA. Coding and decoding strategies for MAC and BC channels (DPC codes, MU decoding).
5. Space-Time MIMO systems. Diversity, multiplexing gain, capacity. Sufficient statistic, MRC.
6. Codes on the GF(m). Polynomial representation. Properties, structures.
7. Coding/decoding algorithms for linear and cyclic codes (Hamming, BCH, RS, ...). Decoding error rate.
8. Convolutional codes (recursive, nonrecursive). Properties, structures. Polynomial representation. Transfer function.
9. Coding/decoding algorithms for convolutional codes. Decoding error rate.
10. Constellation space codes. Trellis codes TCM. Differential codes.
11. Turbo-codes, LDPC codes. Codes on graphs.
12. Iterative decoding algorithms. FBA algorithm and Soft-In Soft-Out blocks.
13. SPA algorithm on the Factor Graph.
14. Space-Time codes for MIMO (block, trellis, layered).
Exercises outlines
1. Capacity and capacity region evaluation for example channels.
2. Implementation of the adaptive modulation and coding (water-filling).
3. Implementation of the diversity reception with MRC.
4. Transfer function of the FSM code. Free distance spectrum.
5. Implementation of the turbo and LDPC code.
6. Iterative decoder (FBA, SPA/FG).
7. Evaluation of the projects.
Literature
1. J. G. Proakis: Digital Communications. McGraw-Hill. 2001
2. D. Tse, P. Viswanath: Fundamentals of Wireless Communications, Cambridge University Press, 2005
3. E. Biglieri: Coding for Wireless Channels, Springer, 2005
4. B. Vucetic, J. Yuan: Space-Time Coding, John Wiley & Sons, 2003
5. Goldsmith: Wireless communications, Cambridge University Press, 2005
6. B. Vucetic, J. Yuan: Turbo codes - principles and applications, Kluwer academic publishers, 2000
7. Oppermann I., Hamalainen M., Iinatti J.: UWB theory and applications, John Wiley & Sons, 2004
8. Meyr, H., Moeneclaey, M., Fechtel, S. A.: Digital Communication Receivers-Synchronization, Channel Estimation and Signal Processing. John Wiley. 1998
9. Mengali, U., D'Andrea, A. N.: Synchronization Techniques for Digital Receivers. Plenum Press. 1997
10. R. E. Blahut: Algebraic codes for data transmission, Cambridge University Press, 2006
11. T. M. Cover, J. A. Thomas: Elements of Information Theory, John Wiley & Sons, 1991
12. S. M. Kay: Fundamentals of statistical signal processing-estimation theory, Prentice-Hall 1993
13. S. M. Kay: Fundamentals of statistical signal processing-detection theory, Prentice-Hall 1998
Requirements
see moodle.fel.cvut.cz