CTU FEE Moodle
Synchronization and Equalization in Digital Communications
B232 - Summer 23/24
This is a grouped Moodle course. It consists of several separate courses that share learning materials, assignments, tests etc. Below you can see information about the individual courses that make up this Moodle course.
Synchronization and Equalization in Digital Communications - AE0M37SEK
Main course
| Credits | 4 |
| Semesters | Winter |
| Completion | Assessment + Examination |
| Language of teaching | English |
| Extent of teaching | 3P+1S |
Annotation
We explain principles of the receiver signal processing (synchronization and equalization) for the parametric channel including variety of the implementation possibilities. We focus on the essential particular forms of the channel phase, frequency and timing parameterization, channels with multipath propagation and MIMO channels. We develop the ideas of synchronization and equalization in the context of the data decoding in the parametric channel. All basic categories of the CSE algorithms are targeted: feed-forward, feed-back, iterative and recursive, including the theoretical background of the parameter estimation theory, and theory of the feed-back and iterative systems.
Study targets
Students learn principles of signal processing in data reception in digital communication.
Course outlines
1. Synchronization and equalization in the context of the data decoding in the parametric channel.
2. Suboptimal methods of demodulation - differential, non-coherent.
3. General principles, structures, and properties of the channel state estimation.
4. Elements of the parameter estimation theory and optimal filtration (ML, MAP, MSE, LS, Kalman, RLS). Performance properties. Sufficient statistics.
5. Application of the parameter estimation theory on the synchronization-equalization problem.
6. Theory of the feed-back systems - equivalent model
7. Theory of the feed-back systems -linear analysis.
8. Theory of the feed-back systems -nonlinear analysis.
9. Iterative channel state estimators with the decoder soft-information measure aid (turbo synchronization).
10. Carrier (phase, frequency) synchronization algorithms.
11. Symbol timing synchronization algorithms.
12. Frame synchronization.
13. Equalization algorithms (linear / MSE, LMS, Kalman, RLS, nonlinear - DFE) for the multipath
14. Channel state estimators for MIMO systems.
2. Suboptimal methods of demodulation - differential, non-coherent.
3. General principles, structures, and properties of the channel state estimation.
4. Elements of the parameter estimation theory and optimal filtration (ML, MAP, MSE, LS, Kalman, RLS). Performance properties. Sufficient statistics.
5. Application of the parameter estimation theory on the synchronization-equalization problem.
6. Theory of the feed-back systems - equivalent model
7. Theory of the feed-back systems -linear analysis.
8. Theory of the feed-back systems -nonlinear analysis.
9. Iterative channel state estimators with the decoder soft-information measure aid (turbo synchronization).
10. Carrier (phase, frequency) synchronization algorithms.
11. Symbol timing synchronization algorithms.
12. Frame synchronization.
13. Equalization algorithms (linear / MSE, LMS, Kalman, RLS, nonlinear - DFE) for the multipath
14. Channel state estimators for MIMO systems.
Exercises outlines
1. Decoder in the parametric channel - marginalization of the channel parameter. Differential demodulator.
2. Implementation and performance properties of ML, MSE, LS estimators.
3. Equivalent model of the feed-back system (verification by the simulation).
4. Performance of the feed-back synchronizer (linear/nonlinear).
5. Implementation of the carrier (phase-frequency) synchronizer.
6. Implementation of the symbol timing synchronizer.
7. Evaluation of the projects.
2. Implementation and performance properties of ML, MSE, LS estimators.
3. Equivalent model of the feed-back system (verification by the simulation).
4. Performance of the feed-back synchronizer (linear/nonlinear).
5. Implementation of the carrier (phase-frequency) synchronizer.
6. Implementation of the symbol timing synchronizer.
7. Evaluation of the projects.
Literature
1. Mengali, U., D'Andrea, A. N.: Synchronization Techniques for Digital Receivers. Plenum Press. 2013
2. S. M. Kay: Fundamentals of statistical signal processing-estimation theory, Prentice-Hall 1993
3. S. M. Kay: Fundamentals of statistical signal processing-detection theory, Prentice-Hall 1998
2. S. M. Kay: Fundamentals of statistical signal processing-estimation theory, Prentice-Hall 1993
3. S. M. Kay: Fundamentals of statistical signal processing-detection theory, Prentice-Hall 1998
Requirements
moodle.kme.fel.cvut.cz
Synchronization and equalization in digital communications - A0M37SEK
| Credits | 4 |
| Semesters | Winter |
| Completion | Assessment + Examination |
| Language of teaching | Czech |
| Extent of teaching | 3P+1S |
Annotation
We explain principles of the receiver signal processing (synchronization and equalization) for the parametric channel including variety of the implementation possibilities. We focus on the essential particular forms of the channel phase, frequency and timing parameterization, channels with multipath propagation and MIMO channels. We develop the ideas of synchronization and equalization in the context of the data decoding in the parametric channel. All basic categories of the CSE algorithms are targeted: feed-forward, feed-back, iterative and recursive, including the theoretical background of the parameter estimation theory, and theory of the feed-back and iterative systems.
Study targets
Students learn principles of signal processing in data reception in digital communication.
Course outlines
1. Synchronization and equalization in the context of the data decoding in the parametric channel.
2. Suboptimal methods of demodulation - differential, non-coherent.
3. General principles, structures, and properties of the channel state estimation.
4. Elements of the parameter estimation theory and optimal filtration (ML, MAP, MSE, LS, Kalman, RLS). Performance properties. Sufficient statistics.
5. Application of the parameter estimation theory on the synchronization-equalization problem.
6. Theory of the feed-back systems - equivalent model
7. Theory of the feed-back systems -linear analysis.
8. Theory of the feed-back systems -nonlinear analysis.
9. Iterative channel state estimators with the decoder soft-information measure aid (turbo synchronization).
10. Carrier (phase, frequency) synchronization algorithms.
11. Symbol timing synchronization algorithms.
12. Frame synchronization.
13. Equalization algorithms (linear / MSE, LMS, Kalman, RLS, nonlinear - DFE) for the multipath
14. Channel state estimators for MIMO systems.
2. Suboptimal methods of demodulation - differential, non-coherent.
3. General principles, structures, and properties of the channel state estimation.
4. Elements of the parameter estimation theory and optimal filtration (ML, MAP, MSE, LS, Kalman, RLS). Performance properties. Sufficient statistics.
5. Application of the parameter estimation theory on the synchronization-equalization problem.
6. Theory of the feed-back systems - equivalent model
7. Theory of the feed-back systems -linear analysis.
8. Theory of the feed-back systems -nonlinear analysis.
9. Iterative channel state estimators with the decoder soft-information measure aid (turbo synchronization).
10. Carrier (phase, frequency) synchronization algorithms.
11. Symbol timing synchronization algorithms.
12. Frame synchronization.
13. Equalization algorithms (linear / MSE, LMS, Kalman, RLS, nonlinear - DFE) for the multipath
14. Channel state estimators for MIMO systems.
Exercises outlines
1. Decoder in the parametric channel - marginalization of the channel parameter. Differential demodulator.
2. Implementation and performance properties of ML, MSE, LS estimators.
3. Equivalent model of the feed-back system (verification by the simulation).
4. Performance of the feed-back synchronizer (linear/nonlinear).
5. Implementation of the carrier (phase-frequency) synchronizer.
6. Implementation of the symbol timing synchronizer.
7. Evaluation of the projects.
2. Implementation and performance properties of ML, MSE, LS estimators.
3. Equivalent model of the feed-back system (verification by the simulation).
4. Performance of the feed-back synchronizer (linear/nonlinear).
5. Implementation of the carrier (phase-frequency) synchronizer.
6. Implementation of the symbol timing synchronizer.
7. Evaluation of the projects.
Literature
1. Mengali, U., D'Andrea, A. N.: Synchronization Techniques for Digital Receivers. Plenum Press. 2013
2. S. M. Kay: Fundamentals of statistical signal processing-estimation theory, Prentice-Hall 1993
3. S. M. Kay: Fundamentals of statistical signal processing-detection theory, Prentice-Hall 1998
2. S. M. Kay: Fundamentals of statistical signal processing-estimation theory, Prentice-Hall 1993
3. S. M. Kay: Fundamentals of statistical signal processing-detection theory, Prentice-Hall 1998
Requirements
moodle.kme.fel.cvut.cz