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Dr. Tahir Zaidi

Advanced Digital Signal Processing

Lecture 1

Introduction

DSP is Everywhere

Sound applications Compression, special effects, synthesis,

recognition, echo cancellation,

Cell Phones, MP3, Movies, Text-to-speech,

Communication Modulation, coding, detection, equalization, echo

cancellation,

Cell Phones, dial-up modem, DSL modem, Satellite Receiver,

Automotive ABS, Active Noise Cancellation, Cruise Control,

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DSP is Everywhere

Medical Magnetic Resonance, Tomography,

Electrocardiogram,

Military Radar, Sonar, Space photographs, remote

sensing,

Image and Video Applications DVD, JPEG, Movie special effects, video

conferencing,

Mechanical Motor control, process control, oil and mineral

prospecting,

Limitations of Analog Signal Processing

Accuracy limitations due to

Component tolerances

Undesired nonlinearities

Limited repeatability due to

Tolerances

Changes in environmental conditions

Temperature

Vibration

Sensitivity to electrical noise

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Limitations of Analog Signal Processing

Limited dynamic range for voltage and currents

Inflexibility to changes

Difficulty of implementing certain operations

Nonlinear operations

Time-varying operations

Difficulty of storing information

Digital Signal Processing

A/D DSP D/A analog signal

analog signal

digital signal

digital signal

Analog input analog output

Digital recording of music

Analog input digital output

Touch tone phone dialing

Digital input analog output

Text to speech

Digital input digital output

Compression of a file on computer

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Pros of Digital Signal Processing

Accuracy can be controlled by choosing word length

Repeatable

Sensitivity to electrical noise is minimal

Dynamic range can be controlled using floating point numbers

Flexibility can be achieved with software implementations

Non-linear and time-varying operations are easier to implement

Pros of Digital Signal Processing

Digital storage is cheap

Digital information can be encrypted for security

Price/performance and reduced time-to-market

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Cons of Digital Signal Processing

Sampling causes loss of information

A/D and D/A requires mixed-signal hardware

Limited speed of processors

Quantization and round-off errors

DSP Introduction

Application of mathematical operations to digitally represented signals

IN OUT

A/D D/A DSP

-3 -2 -1 0 1 2 3 4

x[0] x[1]

n

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General Introduction Discrete Time Signal

sequence x[n]

- as opposed to continuous-time signals x(t)

- time = independent variable

Examples Discrete in Nature

- stock market indices

NasDaq daily closing value from Aug 1995 to Jan 1996

- population statistics

Birth in Canada from 1995-1996 to 1999-2000

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Example

Sampled continuous-time (analog) signals

- Speech

Digital Images

2-D arrays (matrices) of numbers

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Typical DSP Applications

Digital

RadiographicImaging

Ultrasound MedicalImaging

Spy SatelliteImagingMilitaryAppls

Real Time Video Cameras

& Cell Phones

VideoCommunications

Space

Imaging

Appls

Optical Wearable Computers

Web wirelesstechnologyData Storage

& Transmission

Car Awake warning system

Real

Time DSP

Embedded Systems

Speech

Recognition

Example: Speech Modeling

Impulse

Train

Generator

Noise

Generator

Pitch

Period

u(n)

Time-

varying

digital

filter

Vocal Tract

Parameters

s(n)

G

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An Embedded System

Control Panel

PROGRAMMABLE

DSP

PROGRAMMABLE

DSP

ASIC

FPGA

MICROCONTROLLER

CODEC

Dual Port Memeory

System Bus

Controller Process

User interface

process

DSP

Assembly

Code

Analog

interface

Real Time

Operating

system

Embedded signal

Processing System

Host port

Memory interface

Host port

Memory interface

Example Embedded System

Output

Bitstream

49.152

MHz

Sine wave

clock

Xilinx 4062TMS320C6201

68332

SRAM

FLASH

SBSRAM

DDS

A/D

HSP52014

8-bit DAC &LPF

amplifier &squarer

I/Osquare waveoutput

To RF Board

From RF Board

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SDR Board Design

FPGA

SPARTAN3

XC3S1500FG676I

- XC3S2000FG676I

VCCINT=1.2V/470mA

VCCAUX=2.5V/100mA

VCCO1=3.3V/mA

VCCO2=2.5V/mA

AD9640

DUAL ADC

14BIT, 105 MSPS

AVDD=1.8V/310mA

DVDD=1.8V/34mA

DRVDD=3.3V/35mA

GC5016

Quad Wideband DUC/DDC

VPAD=3.3V/180mA

VCORE=1.8V/420mA

DUAL Channel

14 bit ,

125 MSPS (Max)

DAC,

DAC2904,

VA=3.3V/64mA

VD=3.3V/19.5mA

RS232 Interface DB9

DSP

TMS320DM6446

CVDD 1.2V/767mA

DVDD 1.8V/102mA

DVDD 3.3V/6mA

32

47

IN

AD8352

Differential

Amp

AMP

FILTER

NETWORK

Not

implemente

d

IN

POWER

IN

HPI / VLYNQ

interface

LVCMOS_1.8V

32BIT

JTAG

Title: Tranceiver Board

Size: A Revision: 1.3

Date: 08/04/08 Drawn by: ASK

RSSI

Analog

Interface

8 Channel ADC

MCP3008

VD=3.3V/0.5mA

4-Bit

RS232 TRANSCEIVER

MAX3232EID

I-Input

Q-Input

I-Output

Q-Output

16

7

Clock

Generator

AD9513

3 outputs

GAIN CONTROL (6-BIT)

PA

interface6-Bits Output power control

Filter

Selection3-Bit Rx Filter Selection

HMC610

RSSI

x2

1-Bit T/R Control

5-Bit Frequency controlSythesizer

Interface

T/R Switch

/2

2x MT47H64M16BT-5E

1G DDR SDRAM

64M x 32

1.8VD/mA?

OSC

Ethernet

Interface

RJ45

Ethernet PHY

DP83848I

IOVDD=3.3V/150mA

AVDD=3.3V/100mA?

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Digital Power

(SMPS)

1.2VD

1.8VD

2.5VD

3.3VD

Analog

(LDO Linear PSU)

1.8VA

3.3VA

PLATFORM

FLASH

XCF08P 3.3VD/20mA

28F256J3, 128Mb

16MB Intel Strata flash

3.3V/80mA

JTAGEXP

HEADER16-32 IO

64-LFCSP_VQ

SOIC-16

TQFP-48

PBGA-252

FG-676 (BGA) FSG-48 (BGA)

PBGA-N361

LQFP-48

SPI

IN

IN

IN

16-LFCSP_VQ

SOIC-16

Spartan3

SUPPORTS

LVCMOS-1.8

AUDIO SERIAL PORT

ASP HEADER

SSN

Silicon Serial Number

Device 0

Data Data

Waveform 1

Software Defined Radio All configurable HW

FPGA

Device 4

Device 1

DSP

General Purpose Processor

Algo4 Proprietary

FEC Framer 1 V.35

16 QAM

OFDM

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SDR Platform

Key Features 1. DSP core from TI 2. FPGA from Xilinx 3. Dual-channel analog-to-digital

converter 4. Dual-channel digital-to-analog

converter 5. Bandwidth (5 MHz or 20 MHz) 6. RF module operating between 360

MHz and 960 MHz 7. Ethernet remote access capabilities 8. ARM Processor

Design Options 1. Tactical military communications 2. Military communication gateways 3. Handset and man pack systems 4. Vehicular systems

Course Objectives

To establish the idea of using computing techniques to alter the properties of a signal for desired effects, via understanding of Fundamentals of discrete-time, linear, shift-

invariant signals and systems in Representation and Analysis: sampling, quantization,

Fourier and z-transform;

Implementation: filtering and transform techniques;

System Design: filter & processing algorithm design.

Efficient computational algorithms and their implementation.

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Course Outline

Course Outline

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Prerequisite

A fundamental course in signal and system

Liner System analysis and transform analysis

convolution and filtering

Fourier transforms

Laplace and z transforms

Textbooks

Oppenheim, Schafer and Buck, Discrete-Time Signal Processing, 2nd edition (Prentice-Hall, 1999)

Mathematics of DSP

Refrences: McClellan, Schafer, & Yoder, DSP First

Ifeachor Jervis Digital Signal Processing- A Practical Approach, Prentice Hall

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Historical Perspective

Who is who of DSP

Cooley and Tuckey

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Inventors: Oppenhiam, Schaffer ...

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Inventors: Parks & McCllelan

Inventors: Gold and Rader

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Inventor: J. Kaiser

Inventor: Haskell

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Original Speech

Analysis:

Voiced/Unvoiced decision

Pitch Period (voiced only)

Signal power (Gain)

G

Pulse Train

Random Noise

Vocal Tract

Model

V/U

Synthesized Speech

Decoder Signal Power

Pitch

Period

Encoder

Linear Predictive Coding

Inventor: James G. Dunn

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DSP Components

Microprocessor

Any CPU that is contained on a single chip

Little chip is the heart of a computer. Often referred to as just the processor

Does all the computations like adding, subtracting, multiplying, and dividing

In PCs, most popular Intel Pentium chip

In Macs, the PowerPC chip (Motorola, IBM, and Apple)

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Digital Signal Processor

A DSP is a general purpose processor with features specifically designed to make Signal processing applications fast and efficient

DSP, RISC, CISC Processor

A processor is frequently categorized based on the width of its busses (4,8,16,32,64)

Clock Rate (i.e. at what rate does the processor execute instructions)

Complexity of Instruction Set

CISC : Complex Instruction Set Computer

RISC : Reduced Instruction Set Computer

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Embedded Systems Characteristics

Real-Time

Real, defined timing requirements for particular actions to be accomplished

Event Driven

Actions of the system are in response to events, not a predefined sequence.

Resource constrained

Memory Size, speed, power constrained

Special purpose

Device must only perform certain well defined tasks

Embedded System Example

Events :

Button Press

Knob Turned

New Sample needed

by D/A converter

Data block available

from CD drive

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Design Options for Digital Systems

Special Purpose Hardware

Custom ICs / ASICs

Software Programmable Processor

Pentium, PowerPC, etc

FPGA (possibly with embedded general purpose microprocessor)

Xilinx, Altera, etc

DSP

TI, ADSP, etc

Comparison of Options

Specific HW Gen Purpose HW

NRE/Dev Cost

Speed

Flexibility

Time to Market

Production Cost

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Embedded SW Design Flow

Develop Code for a Target processor

Since target is minimal (not much memory, I/Oetc. Code development done on a separate machine. (e.g a PC)

Cross Compiler / Assembler

Simulator

Code then run in the target system and observed. Debug support programmed into the software

Emulation / Debugging

In-Circuit Emulator

Debug Kernel BIOS

JTAG Emulation

Interactively Run Code

Breakpoints

Single Step

Watch Variables

Observe interaction with rest of system

Development environment is frequently processor specific

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TI TMS320C6713 DSP

TI TMS320C6713 DSP Features

DMA Controller

Serial Ports (I/O)

Multiple Computation Units

Cache

On-chip PLL

Host Port Interface

Timers

Floating Point Units

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Basic Numbering Formats

Three main numbering formats:

unsigned representation

2s complement representation (signed)

floating point representations

Fixed point representations of fractions

Saturating arithmetic

Multiplication of fractions

Basic Numbering Formats

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