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EECS 555: Digital Communications Theory
Winter 2009
Instructor: Prof. Wayne Stark
Course Time: Tuesday and Thursday: 10:40-12:00
Ofce Hours: Monday and Wednesday: 11:00-12:00 or by appointment.
Ofce: 4242 EECS
Course Notes: Available on line
E-mail: s

EECS 452
Digital Signal Processing Lab
Lecture 12
Course Surveys, Course Overview,
Project stuff
Finite Impulse Response Filters
2/4/09
1
Course Surveys
Some things largely
consistent
Learning a lot in lab
Lab takes more time
than homework
Some not

EECS 452
Digital Signal Processing Lab
Lecture 12
HW5
Finite Impulse Response Filters
2/4/09
1
Homework 5
Homework 5 will due on Wednesday the 11th.
Project proposal
One per project group
Coverage
Define the project goal
What needs to be done to a

EECS 452
Digital Signal Processing Lab
Lecture 14
More FIR filters
Start on IIR
2/9/09
1
Admin:
Lab 5
Lab 5 split in half
Partly because too long
Partly because I need to cover some more stuff
Effects
Lab 6 will be the week after break
It is relat

EECS 452
Digital Signal Processing Lab
Lecture 15
More FIR filters
Start on IIR
2/11/09
Last time:
Due to fire, we fled
Pick up from there.
Internal overflow
It is possible for an internal addition to be
outside of the range -1 to 1 even if output
i

EECS 452
Digital Signal Processing Lab
Lecture 16
IIR filter basics
Overflow
range of terms?
Biquads
2/13/09
1
Group meetings and presentations
Anyone else willing to volunteer to go this
Wednesday?
Need to meet with C2T2Z today if possible
Weekend

EECS 452
Digital Signal Processing Lab
Lecture 17
Designing a low pass IIR filter the 452 way
And why we do it.
2/16/09
Todays lecture
Is a bit different
My major goal is to provide intuition about
filter design.
lowpass biquad IIR filters specifical

EECS 452 Digital Signal Processing Lab
Lecture 2: C, and C5510
Handouts: Lecture notes Handin: HW1
Computers are good at following instructions, but not at reading your mind. D. Knuth
Agenda
C programming (continued) C5510 pointers and memory Programming

EECS 452 Digital Signal Processing Lab
Lecture 3: Number representation
Handouts: Lecture notes HW2
"One, two, three, many, many-one" Trolls of Discworld
From: http:/courses.ece.uiuc.edu/ece390/lecture/lockwood/l1.html
1
Agenda
Radix number schemes
Deci

EECS 452 Digital Signal Processing Lab
Lecture 10 ADC/DAC basics PMod (in lab)
Handouts: Lecture notes HW4
1 1/30/09
Stuff
HW regrades
If you want something regraded you must:
Staple a sheet of paper on to the front with a clear explanation of what pro

EECS 452 Digital Signal Processing Lab
Lecture 11 Bit serial communication Lab 4 stuff Course survey
Handouts: Lecture notes
1 2/2/09
Agenda
2
Condenser Microphone
In a condenser microphone, the diaphragm acts as one plate of a capacitor and the vibratio

EECS 452
Digital Signal Processing Lab
Lecture 9
DFT
ADC/DAC basics
Handouts:
Lecture notes
The DFT part of the lecture comes from
Understanding Digital Signal Processing
by Richard Lyons.
Many figures in this presentation are from the
same book as abo

EECS 452
Digital Signal Processing Lab
Lecture 8
Yet More VHDL
Start on signals review
Handouts:
Lecture notes
1
Bureaucracy
Homework/labs/handouts/office
hours
Lab 3 posted last night.
Removed some stuff from the original
Added some stuff
Tried to

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Lecture Notes 2: Detection Theory
Goals:
Optimum Detection in AWGN
Optimum Detection with Nusiance (Unwanted) Parameters
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II-1
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M -ary Detection Problem
Consider the problem of deciding which of M hypothesis is true based on
observing a random

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Error Probability for M signals
Goals
1. Exact analysis of M -ary orthogonal signals in AWGN channels.
2. Gallager bound for arbitrary signals, arbitrary channel.
3. Random Coding Bound.
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III-1
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Error Probability
Problem: Determine the error pro

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Lecture Notes 4: Asymptotic Performance
In this lecture we discuss the asymptotic performance of signals. First we
consider the case of M signals in N dimension when transmitted over the
additive white Gaussian noise channel. We let M and N become lar

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Lecture Notes 5: Noncoherent Receivers
Goals
Derive optimum receiver for arbitrary signals in Gaussian noise with a
random phase.
Determine performance of two signals in white Gaussian noise.
Determine performance of M -orthogonal signals in white

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Lecture Notes 6: Basic Modulation Schemes
In this lecture we examine a number of different simple modulation schemes.
We examine the implementation of the optimum receiver, the error probability
and the bandwidth occupancy. We would like the simplest

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Lecture 7
Goals
Be able to encode using a linear block code
Be able to decode a linear block code received over a binary symmetric
channel or an additive white Gaussian channel
Be able to decode a turbo product code for an additive white Gaussian
c

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Lecture Notes 8: Trellis Codes
In this lecture we discuss construction of signals via a trellis. That is, signals
are constructed by labeling the branches of an innite trellis with signals from
a small set. Because the trellis is of innite length this

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In this lecture we examine optimum demodulation when the transmitted signal
is ltered by the channel and there is additive white Gaussian noise. The
optimum demodulator chooses the possible transmitted vector that would
result in the received vector (

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Lecture Notes 10: Fading Channels Models
In this lecture we examine models of fading channels and the performance of
coding and modulation for fading channels. Fading occurs due to multiple
paths between the transmitter and receiver. For example, two

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Lecture Notes 11:
Direct-Sequence Spread-Spectrum Modulation
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In this lecture we consider direct-sequence spread-spectrum systems. Unlike
frequency-hopping, a direct-sequence signal occupies the entire bandwidth
continuously. The signal is obtained by

EECS 452 Digital Signal Processing Lab
Lecture 18 DFT and FFT
2/16/09
Admin
Admin stuff
Directions for ordering parts posted.
Will need Google account.
Talk to one (or both) of Dr. Brehob or Dr. Metzger about what you want and why. Make a copy of the f