Digital Signal Processing II `Advanced Topics’

Digital Signal Processing II

Àdvanced Topics’

Marc Moonen

Dept. E.E./ESAT, K.U.Leuven

[email protected]

www.esat.kuleuven.be/scd/

DSP-IIVersion 2009-2010 Lecture-1 Introduction p. 2

Lecture-1 : Introduction

• Aims/Scope Why study DSP ? DSP in applications : GSM, ADSL,…

• Overview

• ActivitiesLectures - Course Notes/LiteratureHomeworks/Exercise sessionsProjectExam


Why study DSP ?

• Analog Systems vs. Digital Systems

- translate analog (e.g. filter) design into digital

- going `digital’ allows to expand functionality/flexibility/…

(e.g. how would you do analog speech recognition ? analog audio compression ? …? )

IN OUT IN OUTA/D D/A

2+2

=4


DSP in applications : GSM

Cellular mobile telephony (e.g. GSM)

• Basic network architecture :

-country covered by a grid of cells

-each cell has a base station

-base station connected to land telephone network and

communicates with mobiles via a radio interface

-digital communication format



• DSP for digital communications (`physical layer’ ) :

– a common misunderstanding is that digital communications is `simple’….

– While in practice…

Transmitter

1,0,1,1,0,…

Channel

x +

a noise1/a

x

Receiver

dec

isio

n

.99,.01,.96,.95,.07,…

1,0,1,1,0,…



• DSP for digital communications (`physical layer’ ) :

– In practice…

– This calls for channel modeling + compensation (equalization)

Transmitter

1,0,1,1,0,…+

Receiver

1,0,1,1,0,…??noise

`Multipath’

Channel

.59,.41,.76,.05,.37,… !!



• GSM Channel Estimation/Compensation– Multi-path channel is modeled with short (3…5 taps) FIR filter

H(z)= a+b.z^-1+c.z^-2+d.z-3+e.z^-4 (interpretation?)

– Channel coefficients (cfr. a,b,c,d,e) are identified in receiver based on

transmission of pre-defined training sequences, in between data bits

(problem to be solved at receiver is: `given channel input and channel

output, compute channel coefficients’).

This leads to a least-squares parameter estimation procedure

(see Linear Algebra course!).

– Channel model is then used to design suitable equalizer (`channel

inversion’), or (better) for reconstructing transmitted data bits based on

Maximum-likelihood sequence estimation (`Viterbi decoding’).

– Channel is highly time-varying (e.g. terminal speed 120 km/hr !)

=> All this is done at `burst-rate’ (+- 100 times per sec).

= SPECTACULAR !!



• GSM Channel Estimation/Compensation

• GSM Speech Coding– Original `PCM’-signal has 64kbits/sec = 8 ksamples/sec * 8bits/sample.

– How to reduce this to <11kbits/sec, while preserving quality ?

– Coding based on speech generation model (vocal tract,…), where model

coefficient are identified for each new speech segment (e.g. 20 msec).

– This leads to a least-squares parameter estimation (again), executed +- 50

times per second). Fast algorithm is used, e.g. `Levinson-Durbin’ algorithm

(see (Advanced) Linear Algebra course).

– Then transmit model coefficients instead of signal samples.

– Synthesize speech segment at receiver

(that `sounds like’ original speech segment).

= SPECTACULAR !!



• GSM Channel Estimation/Compensation

• GSM Speech Coding

• GSM Multiple Access Schemes – Capacity increase by time & frequency `multiplexing’

– FDMA : e.g. 125 frequency channels for GSM/900MHz

– TDMA : 8 time slots(=users) per channel, `burst mode’ communication

(PS: in practice, capacity per cell << 8*125 ! )

• Etc..

= BOX FULL OF DSP/MATHEMATICS !!


DSP in applications : ADSL

Telephone Line Modems

– voice-band modems : up to 56kbits/sec in 0..4kHz band

– ADSL modems : up to 8Mbits/sec in 30kHz…1MHz band

(3,5…5km)– VDSL modems : up to 52Mbits/sec in …12MHz band

(0.3…1.5km)

How has this been made possible?

X 1000



Communication Impairments :• Channel attenuation

– Received signal may be attenuated by more than 60dB

(attenuation increases with line length & larger at high (MHz) frequencies)

PS: this is why for a long time, only the voiceband (up to 4kHz) was used

– Frequency-dependent attenuation introduces `ìnter-symbol interference’’ (ISI). ISI channel can (again) be modeled with an FIR filter. Number of taps will be much larger here (>500!)



Communication Impairments :• Coupling between wires in same or adjacent binders introduces `crosstalk’

– Near-end Xtalk (NEXT) (=upstream in downstream, downstream in upstream)

– Far-end Xtalk (FEXT) (=upstream in upstream, downstream in downstream)

Meaning that a useful signal may be drowned in (much larger) signals from other users..

…leading to signal separation and spectrum management problems

• Other :

– Radio Frequency Interference (AM broadcast, amateur radio)– Echo due to impedance mismatch– Etc..

Conclusion: Need advanced modulation, DSP,etc. !



• ADSL spectrum : divide available transmission band in 256 narrow bands (`tones’), transmit different sub-streams over different sub-channels (tones) (=DMT, `Discrete Multi-tone Modulation’)



ADSL-DMT Transmission block scheme :

DFT/IDFT (FFT/IFFT) based modulation/demodulation scheme

pointer : www.adslforum.com PS: do not try to understand details here...



ADSL specs• 512-point (I)FFT’s (or `similar’) for DMT-modulation FFT-rate = 4.3215 kHz (i.e. >4000 512-point FFTs per second !!!!)• basic sampling rate is 2.21 MHz (=512*4.3215k) 8.84 MHz A/D or D/A (multi-rate structure)• fixed HP/LP/BP front-end filtering for frequency duplex • adjustable time-domain equalization filter (TEQ) e.g. 32 taps @ 2.21 MHz filter initialization via least-squares/eigenvalue procedure• adaptive frequency-domain equalization filters (FEQ)

VDSL specs • e.g. 4096-point (I)FFT’s, etc….

= BOX FULL OF DSP/MATHEMATICS !!


DSP in applications : Other…

• Speech Speech coding (GSM, DECT, ..), Speech synthesis (text-to-speech),

Speech recognition

• Audio Signal Processing Audio Coding (MP3, AAC, ..), Audio synthesis Editing, Automatic transcription, Dolby/Surround, 3D-audio,.

• Image/Video• Digital Communications Wireline (xDSL,Powerline), Wireless (GSM, 3G, Wi-Fi, WiMax CDMA, MIMO-transmission,..)

• …


DSP in applications

Enabling Technology is• Signal Processing

1G-SP: analog filters

2G-SP: digital filters, FFT’s, etc.

3G-SP: full of mathematics, linear algebra,

statistics, etc... • VLSI• etc...

Signals&Systems course (JVDW)

DSP-I (PW)

DSP-II


DSP-II Aims/Scope

• Basic signal processing theory/principles

filter design, filter banks, optimal filters & adaptive filters

• Recent/advanced topics robust filter realization, perfect reconstruction filter banks,

fast adaptive algorithms, ...

• Often `bird’s-eye view’ skip many mathematical details (if possible… )

selection of topics (non-exhaustive)


0 0.5 1 1.5 2 2.5 30

0.2

0.4

0.6

0.8

1

1.2

Passband Ripple

Stopband Ripple

Passband Cutoff -> <- Stopband Cutoff

Overview (I)

• INTRO : Lecture-1

Lecture-2 : Signals and Systems Review

• Part I : Filter Design & ImplementationLecture-3 : IIR & FIR Filter Design

Lecture-4 : Filter Realization

Lecture-5 : Filter Implementation


Overview (II)

• Part II : Filter Banks & Subband SystemsLecture-6 : Filter Banks Intro/Applications (audio coding/CDMA/…)

Lecture-7/8 : Filter Banks Theory

Lecture-9 : Special Topics

(Frequency-domain processing, Wavelets,…)

.

3 subband processing 3H1(z) G1(z)




+

IN OUT


Overview (III)

• Part III : Optimal & Adaptive FilteringLecture-10 : Optimal/Wiener Filters

Lecture-11: Adaptive Filters/Recursive Least Squares

Lecture-12: Adaptive Filters/LMS

Lecture-13: `Fast’ Adaptive Filters

Lecture-14: Kalman Filters

.


Prerequisites

`Systeemtheorie en Regeltechniek’ (JVDW)

`Digitale Signaalverwerking I’ (PW) signaaltransformaties, bemonstering, multi-rate, DFT, …

`Toegepaste Algebra en

Analytische Meetkunde’ (JVDW)


Literature / Campus Library Arenberg

• A. Oppenheim & R. Schafer

`Digital Signal Processing’ (Prentice Hall 1977)• L. Jackson

`Digital Filters and Signal Processing’ (Kluwer 1986)• P.P. Vaidyanathan

`Multirate Systems and Filter Banks’ (Prentice Hall 1993)• Simon Haykin

Àdaptive Filter Theory’ (Prentice Hall 1996)• M. Bellanger

`Digital Processing of Signals’ (Kluwer 1986)• etc...

Part-III

Part-II

Part-I


Literature / DSP-II Library

• Collection of books is available to support course material

• List/info/reservation via DSP-II webpage

• contact: beier.li@esat (E/C)


Activities : Lectures

Lectures: 14 * 2 hrs

Course Material:• Part I-II-III : Slides (use version 2009-2010 !!)

...download from DSP-II webpage

• Part III : Ìntroduction to Adaptive Signal Processing’,

Marc Moonen & Ian.K. Proudler

= support material, not mandatory !

…(if needed) download from DSP-II webpage


Activities : Homeworks/Ex. Sessions

• `Homeworks’ …to support course material

• 6 Matlab/Simulink Sessions …to support homeworks …come prepared !

• contact: amir.forouzan@esat (English+Persian)

beier.li@esat (English+Chinese)

prabin.kumarpandey@esat (English+Nepali)

pepe.gilcacho@esat (English+Spanish)


Activities : Project

• Discover DSP technology in present-day systems examples: 3D-audio, music synthesis, automatic

transcription, speech codec, MP3, GSM, ADSL, …• Select topic/paper from list on DSP II webpage (submit 1st/2nd choice by

Oct.5 to pepe.gilcacho@esat) • Study & www surfing• Build demonstration model & experiment in Matlab/Simulink

• Deliverable : – Project Plan: 1 page status report & time plan

(send to marc.moonen@esat by Nov 1st) – Presentation: .ppt or similar, incl. Matlab/Simulink demonstration

(December, 20 mins per group)– Software

• Groups of 2


Activities : Project

Topics/Papers• List available under DSP-II web page• Other topics : subject to approval ! (email 1/2-page description to pepe.gilcacho@esat

before Oct. 5)

Tutoring

10 research assistants/postdocs

All PPT presentations will be made available, for ref.


Activities : Exam

• Oral exam, with preparation time• Open book• Grading : 5 pts for question-1 5 pts for question-2 5 pts for question-3

5 pts for project (software/presentation) ___

= 20 pts


homes.esat.kuleuven.be/~pepe/dspII

• Contact: pepe.gilcacho@esat• Slides• Homeworks • Projects info/schedule• Exams• DSP-II Library• FAQs (send questions to pepe.gilcacho@esat or marc.moonen@esat )

Documents

Digital Signal Processing II `Advanced Topics’