# Coursebooks 2016-2017

## Signal processing for communications

Prandoni Paolo

English

#### Summary

Students learn digital signal processing theory, including discrete time, Fourier analysis, filter design, sampling, interpolation and quantization; they are introduced to image processing and data communication system design.

#### Content

1. Basic discrete-time signals and systems: signal classes and operations on discrete-time signals, signals as vectors in Hilbert space
2. Fourier Analysis: properties of Fourier transforms, DFT, DTFT; FFT.
3. Discrete-Time Systems: LTI filters, convolution and modulation; difference equations; FIR vs IIR, stability issues.
4. Z-transform: properties and regions of convergence, applications to linear systems.
5. Filter Design: FIR design methods, IIR design methods, filter structures.
6. Stochastic Signal Processing: random processes, spectral representation.
7. Interpolation and Sampling: the continuous-time paradigm, interpolationthe sampling theorem, aliasing.
8. Quantization: A/D and D/A converters.
9. Multi-rate signal processing: upsampling and downsampling, oversampling.
10. Multi-dimensional signals and processing: introduction to Image Processing.
11. Practical applications: digital communication system design, ADSL.

#### Keywords

signal processing, discrete-time, continuous-time, filter, filter design, sampling, aliasing, DSP, Fourier transform, FFT, modem, ADSL

#### Learning Prerequisites

##### Required courses

calculus, linear algebra

##### Recommended courses

Circuits and systems, basic probability theory

##### Important concepts to start the course

vectors and vector spaces, functions and sequences, infinite series

#### Learning Outcomes

By the end of the course, the student must be able to:
• Identify signals and signal types
• Recognize signal processing problems
• Apply the correct analysis tools to specific signals
• Check system stability
• Manipulate rational transfer functions
• Implement signal processing algorithms
• Design digital filters
• Interpret complex signal processing systems

#### Transversal skills

• Use a work methodology appropriate to the task.
• Assess one's own level of skill acquisition, and plan their on-going learning goals.
• Use both general and domain specific IT resources and tools

#### Teaching methods

Course with exercises in class and on the computer

#### Expected student activities

complete weekly homework, write numerical routines to implement core concepts

#### Assessment methods

midterm exam for bonus points and final exam for final grade.

#### Resources

##### Bibliography

Signal processing for Communications, EPFL Press, 2008, by P. Prandoni and M. Vetterli. The book is available for sale in printed form online and in bookstores; in iBook format on the Apple store and is also available as a free pdf file at http://www.sp4comm.org/

### In the programs

• Auditeurs en ligne, 2016-2017, Spring semester
• Semester
Spring
• Exam form
Written
• Credits
6
• Subject examined
Signal processing for communications
• Lecture
4 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Semester
Spring
• Exam form
Written
• Credits
6
• Subject examined
Signal processing for communications
• Lecture
4 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Passerelle HES - SC, 2016-2017, Spring semester
• Semester
Spring
• Exam form
Written
• Credits
6
• Subject examined
Signal processing for communications
• Lecture
4 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Semester
Spring
• Exam form
Written
• Credits
6
• Subject examined
Signal processing for communications
• Lecture
4 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Semester
Spring
• Exam form
Written
• Credits
6
• Subject examined
Signal processing for communications
• Lecture
4 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Semester
Spring
• Exam form
Written
• Credits
6
• Subject examined
Signal processing for communications
• Lecture
4 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks

### Reference week

MoTuWeThFr
8-9
9-10
10-11 CE2
11-12
12-13
13-14
14-15INM200  ELD120
ELG116
INM11
INM201

15-16
16-17
17-18
18-19
19-20
20-21
21-22

Lecture
Exercise, TP
Project, other

### legend

• Autumn semester
• Winter sessions
• Spring semester
• Summer sessions
• Lecture in French
• Lecture in English
• Lecture in German