Transcript Introduction

Introduction
Analog and Digital Communications
Autumn 2005-2006
Sep 06, 2005
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Communications
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Communications = Information transfer
This course is about communications
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Limited to information in electrical form
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We will not consider delivering newspapers
We will primarily cover information transfer
at systems level
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Sep 06, 2005
We will not deal [too much] with circuits, chips,
signal processing, microprocessors, protocols,
and networks
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What exactly is information?
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Information is a word that is too generic
for our purposes
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We will use the word message
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A physical manifestation of information
What do communication systems have
to do with messages?
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Communication systems are responsible for
producing an “acceptable” replica of
message at the destination
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Is Signal = Message?
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Just like information, signal is also a generic
word
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Derived directly from information
Scientists and Engineers use signal to denote
information in electrical form
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We will use signal and message interchangeably
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Can we classify signals?
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Messages or signals can be classified:
Analog
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A physical quantity that varies with “time”, usually in a
smooth or continuous fashion
Fidelity describes how close is the received signal to the
original signal. Fidelity defines acceptability
Digital
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An ordered sequence of symbols selected from a finite set of
discrete elements
When digital signals are sent through a communication
system, degree of accuracy within a given time defines the
acceptability
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Examples
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Analog Signals
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t
Digital Signals
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Values are taken from an
infinite set
Values are taken from a
discrete set
t
Binary Signals
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Digital signals with just
two discrete values
1
0
1
0 0
1
0
t
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Elements of Communication Systems
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Transmitter
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Channel
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Modulation
Coding
Attenuation
Noise
Distortion
Interference
Receiver
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Detection (Demodulation+Decoding)
Filtering (Equalization)
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Elements of Communication Systems
Text
Images
Video
Audio
b1b2 ...
Source
Encoder
m(t )
Transmitter
bˆ1bˆ2 ...
mˆ (t )
sˆ(t )
s (t )
Channel
Receiver
Source
Decoder
Encoder: Message  Message Signal or bits
 Transmitter: Message signal  Transmitted signal
 Channel: Introduces noise, distortion, interference
 Receiver: Received Signal  Message Signal
 Decoder: Message Signal  Original Message
Example: Microphone ---------------> Speaker
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What do we cover in CS477?
b1b2 ...
m (t )
n(t)
Analog or Digital
“Modulator”
Transmitter
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s(t )
h(t)
+
sˆ(t )  n(t )
Analog or Digital
“Demodulator”
Channel
bˆ1bˆ2 ...
ˆ (t )
m
Receiver
Modulation converts message signal or bits into amplitude,
phase, or frequency of a sinusoidal carrier (Am, FM, QPSK)
Modulation may make the transmitted signal robust to channel
impairments
Channel introduces noise, distortion, and interference
Demodulator tries to mitigate the channel impairments
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Fundamental Limitations
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If practical implementation is not a concern and we
don’t worry about feasibility, is there something else
that limits acceptable communications?
Bandwidth
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Noise
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Channel must be able to allow signal to pass through
Channels usually have limited bandwidth
Can we reduce signal bandwidth? Do “something” at source
Can we reduce it?
Can we reduce its effects?
Do something at the transmitter and receiver
Signal to Noise Ratio
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Block Diagram
n( t )
m( t )
(Modulator)
Analog
or Digital
Transmitter
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s( t )
h( t )
Channel
Demodulator
ê (t )
m
Receiver
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Performance Criterion
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How a “good” communication system can be
differentiated from a “sloppy” one?
For analog communications
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How close is m
ê ( t ) to m( t )? Fidelity!
SNR is typically used as a performance metric
For digital communications
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Data rate and probability of error
No channel impairments, no error
With noise, error probability depends upon data
rate, signal and noise powers, modulation scheme
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Limits on data rates
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Shannon obtained formulas that provide
fundamental limits on data rates (1948)
Without channel impairments, an
infinite data rate is achievable with
probability of error approaching zero
For bandlimited AWGN channels, the
“capacity” of a channel is:
C = B log(1 + SNR)
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