Transcript Lecture 1 - Portal UniMAP

CHAPTER 1
Signals and
Spectra
School of Computer and Communication Engineering,
Amir Razif Arief b. Jamil Abdullah
EKT 431: Digital Communications
Coursework Contribution
Coursework:
Lab: 30%
 Project 1
 Project 2
 Project 3
 Assignments, Attendance & Quizzes: 10%
 Assignments; minimum 4.
 Attendance; subjected to university regulation.
 Quizzes; minimum 8.
 Test: 10 %
 Two tests.
Exam: 50%
 Lecturer: Amir Razif Arief b. Jamil Abdullah
 Office: Grnd Floor, House #8A, KKF, Kuala Perlis
 E-mail: [email protected]
 Office tel#: 04-9854251 @ 019 4659277
 HP#: Upon Request


Teaching Engineer: Mohd Fairuz b. Mohd Fadzil
 Office: House #1, KKF, Kuala Perlis
2006-01-24
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Practical information

Course material
 Course text book:
 “Digital Communications: Fundamentals and
Applications” by Bernard Sklar,Prentice Hall, 2005,
ISBN: 0-13-084788-7

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Reference Books;
 “Introduction to Digital Communications”, by Pursley
M.B, IE Pearson Hall 2005
 “Information Transmission, Modulation and Noise”, by
M.Schwartz, Mc Graw Hill 2005
 “Digital Communications”, by Proakis, John G.
International Eddition, Mc GrawHill 3rd Ed. 1995
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Outcome
• To understand and use various terminologies in Digital
Communications.
• To be able to explain the differences between analog and
digital communications.
• To describe the basic building blocks of a digital
communication system and the performance objectives
for good communication.
• To analyze the signals transmission via channel.
• To study the base band data transmission, digital
modulation and spread spectrum communications.
• To explore the basic principles of telephony system.
Today, we are going to talk
about:


What are the features of a digital communication system?
 Why “digital” instead of “analog”?
What do we need to know before taking off toward
designing a DCS?
 Classification of signals
 Random processes
 Autocorrelation
 Power and energy spectral densities
 Noise in communication systems
 Signal transmission through linear systems
 Bandwidth of a signal
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Introduction


Deal with transformation of information; voice, video or
data, over a channel that consists of wire, waveguide and
space.
Digital communication systems are becoming attractive
because of the growing demand for data communication
and digital transmission offers data processing options.
Revision
• Signals & Systems
Fourier transform, signal analysis
• Communications Systems
PAM, PWM, PPM, PCM, ASK, FSK, PSK, line coding
• Communication Network
LAN, wireless network, circuit switching, multiple
access
Scope of the course
• Communications is a process by which information is
exchanged between individuals through a common system
of symbols, signs, or behaviour.
• Communication systems are reliable, economical and
efficient means of communications
• Public switched telephone network (PSTN), mobile
telephone communication (GSM, 3G, ...), broadcast radio
or television, navigation systems, ...
• The course is aiming at introducing fundamental issues in
designing a (digital) communication system
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Scope of the course ...
• Example of a (digital) communication system:
• Cellular wireless communication systems
BS
Base Station (BS)
UE
UE
UE
User Equipment (UE)
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Scope of the course …

Learning fundamental issues in designing a digital
communication system (DCS):
 Utilized techniques
 Formatting and source coding
 Modulation (Baseband and bandpass signaling)
 Channel coding
 Equalization
 Synchronization
 ....
 Design goals
 Trade-off between various parameters
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Block Diagram of DCS
General structure of a communication system
Noise
Info.
SOURCE
Source
Received
Transmitted
Received
info.
signal
signal
Transmitter
Receiver
Channel
User
Transmitter
Formatter
Source
encoder
Channel
encoder
Modulator
Receiver
Formatter
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Source
decoder
Channel
decoder
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Demodulator
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Block Diagram and
Transformation
• The upper block are the signal transformation from source
•
•
to transmitter (XMT); format, source encode, encrypt,
channel encode, multiplex, pulse modulated, band pass
modulated, frequency spread and multiple excess.
The lower block are the signal transformation from receiver
(RCV) to sink; reversing the signal processing of the upper
block.
For wireless communication;
(i) transmitter consist of frequency up-conversion stage
to a radio frequency, high power amplifier and antenna.
(ii) receiver consist of antenna and low noise amplifier
(LNA).
Cont’d…
• Signal processing steps;
(i) input information source is convert to binary digits (bits)
(ii) bits grouped to form message symbol (mi )
(iii) system using channel coding; sequence of message
symbol transform to sequence of channel symbol (ui ) or bit
stream.
• The key signal processing blocks of DCS are formatting,
modulation, demodulation/detection and synchronization.
(1) Formatting:
transform source information into bits. Information is inform of bit
stream up to pulse-modulation block.
(2) Modulation:
process of converting the channel symbol to waveform compatible to
transmission channel.
- binary representation  baseband waveform
Cont’d…
(3) Pulse Modulation:
- transform form binary representation to baseband waveform. Include
filtering to minimize the binary waveform. When pulse modulation is
applied to binary symbols result in pulse-code modulation (PCM).
- line code, M-ary pulse modulation.
(4) Band Pass Modulation:
- required if the transmission medium do not support the propagation
of pulse-like waveform.

Equalization
- implemented to compensate for any signal distortion caused by nonideal hc(t).

Source Codin
- produce AD conversion and remove redundant information.
- channel coding can reduce the probability of error and reduce snr.

Multiplexing
- combine signal of different characteristics or sources to share
communication resources.

Encryption;
- provides communication privacy, prevent intrusion.
Digital Communication System

Important features of a DCS:
 The transmitter sends a waveform from a finite set of
possible waveforms during a limited time

The channel distorts, attenuates the transmitted signal
and adds noise to it.

The receiver decides which waveform was transmitted
given the noisy received signal

The probability of erroneous decision is an important
measure for the system performance
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Digital versus Analog

Advantages of digital communications:
 Regenerator receiver

Signal; original-> distortion-> degraded-> badly degraded.., -> amplified
& regenerated
Original
pulse
Regenerated
pulse
Propagation distance
Voice
Data
A bit is a bit!
Media

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Different kinds of digital signal are treated identically.
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Digital versus Analog ..cont’d
•
•
•
•
•
•
•
Digital signals are regenerated.
Less distortion due to ‘1’ and ‘0’ state.
Availability of error detection and correction.
Digital is more reliable, cheap cost and more flexible
compare to analog.
Different types of digital signals; data, telegraph, telephone
television, have identical signal transmission a bit.
Protect against interference, jamming and provide
encryption/privacy.
Distorted analog signal cannot be removed by amplification
and cannot be regenerated.
Classification of Signals

Deterministic and random signals
 Deterministic signal: No uncertainty with respect to the
signal value at any time.

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Random signal: Some degree of uncertainty in signal
values before it actually occurs.
 Thermal noise in electronic circuits due to the
random movement of electrons
 Reflection of radio waves from different layers of
ionosphere
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Classification of Signals …

Periodic and non-periodic signals
A periodic signal

A non-periodic signal
Analog and discrete signals
A discrete signal
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Analog signals
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Classification of Signals ..

Energy and power signals
 A signal is an energy signal if, and only if, it has
nonzero but finite energy for all time:

A signal is a power signal if, and only if, it has
finite but nonzero power for all time:
General rule: Periodic and random signals are power
signals. Signals that are both deterministic and
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Lecturesignals.
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Random Process

A random process is a collection of time functions, or
signals, corresponding to various outcomes of a random
experiment. For each outcome, there exists a
deterministic function, which is called a sample function
or a realization.
Real number
Random
variables
Sample functions
or realizations
(deterministic
function)
time (t)
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Random Process …

Strictly stationary: If none of the statistics of the random
process are affected by a shift in the time origin.

Wide sense stationary (WSS): If the mean and
autocorrelation functions do not change with a shift in the
origin time.

Cyclostationary: If the mean and autocorrelation functions
are periodic in time.
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Ergodic process: A random process is ergodic in mean
and autocorrelation, if
and,
respectively.
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Autocorrelation

Defn: autocorrelation refers to the matching of a signal with a

Autocorrelation of an energy signal

Autocorrelation of a power signal
delayed version of itself.


For a periodic signal:
Autocorrelation of a random signal

For a WSS process:
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Spectral Density
• Energy signals:
• Energy spectral density (ESD):
• Power signals:
• Power spectral density (PSD):
• Random process:
• Power spectral density Lecture
(PSD):
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Properties of an
Autocorrelation function

For real-valued (and WSS in case of random signals):
1. Autocorrelation and spectral density form a Fourier
transform pair.
2. Autocorrelation is symmetric around zero.
3. Its maximum value occurs at the origin.
4. Its value at the origin is equal to the average power
or energy.
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Noise in Communication Systems
• Thermal noise; thermal motion of electrons in all
disipative components, is described by a zero-mean
Gaussian random process, n(t).
• Its PSD is flat, hence, it is called white noise.
• n- Gaussian probability density function
[w/Hz]
Power spectral
density
Autocorrelation
function
Probability density function
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Signal Transmission through
Linear Systems
Input
Output
Linear system
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
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Deterministic signals:
Random signals:
Ideal distortion less transmission:
All the frequency components of the signal not only arrive
with an identical time delay, but also are amplified or
attenuated equally.
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Signal Transmission … - cont’d

Ideal filters:
Non-causal!
Low-pass
Band-pass

High-pass
Realizable filters:
RC filters
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Butterworth filter
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Bandwidth of signal

Baseband versus bandpass:
Baseband
signal
Bandpass
signal
Local oscillator
Bandwidth dilemma:
 Bandlimited signals are not realizable!
 Realizable signals have
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Bandwidth of Signal …

Different definition of bandwidth:
a) Half-power bandwidth
b) Noise equivalent bandwidth
c) Null-to-null bandwidth
a) Fractional power containment bandwidth
b) Bounded power spectral density
c) Absolute bandwidth
(a)
(b)
(c)
(d)
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(e)50dB
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