EGR 544-1 Introduction
Z. Aliyazicioglu
Electrical and Computer Engineering Department
Cal Poly Pomona
• Office : Building 9-143
• Office Hours : M
• Class Folder: EGR54401
• Course Webpage: www.calpolypomona.edu/~zaliyazici/ece544
• Grading: Exam 1
Exam 2
Final
Homework/Quiz
Project
• Textbook: Digital Communication, 4 th Ed.
John Proakis, MCGraw Hill 2000
• Textbook website www.mhhe.com/engcs/electrical/proakis
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Prerequisites
• Probability and Random Processes
• Communication Systems
Reference:
• [1] Introduction to Digital Communication , by Rodger E. Zeimer and
Roger L. Peterson, Second Edition, Prentice Hall, 2001 .
• [2] Digital Communications , by Bernard Sklar, Second Edition, Prentice
Hall, 2001
• [3] Communication Systems , Simon Haykin, 4th Ed. Wiley, 2001,
ISBN 0-471-17869-1
• [4] Probability, Random Variables, and Random Processes , A. A.
Papoulis, 4th Ed., McGraw-Hill, 2001.
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Device transfer information from one location (time) to another location (time)
Digital: Smoke, Morse Code Telegraph
Analog: Commercial Radio, TV
Digital: Data, Computer, HDTV
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• Point to Point: Telephone, Fax
• Point to Multipoint: Broadcast (Radio, TV)
• Simplex: One Way
• Duplex: Two Ways
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Cost/Performance Trade Off
Cost Performance
Power
Data Rate
Bit Error Probability
Transmission Range
Adaptive to Environment
Complexity Security
Anti Jamming Capability
Low Probability of Interception
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• Digital receiver needs only distinguish between two waveforms it is possible to exactly recover digital information
• Transmitted bits can be detected and regenerated, so Noise does not propagate additively.
• More signal processing techniques are available to improve system performance: source coding, channel (error-correction) coding, equalization, encryption, filtering,…
• Better “control” and more flexibility. . .
• Digital ICs are inexpensive to manufacture. A single chip can be mass produced at low cost, no mater how complex
• Digital communications permits integration of voice, video, and data on a single system (ISDN)
• Implementation by software instead of hardware
• Security is easier to implement.
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Digital Communication System
• The basic elements of a digital communication system
Information
Source
Output
Source
Encoder
Channel
Encoder
Source
Decoder
Channel
Decoder
Information & Coding
Theory
Digital
Modulator
Discrete
Channel
Channel
Noise
Digital
Demodulator
Modulation & Detection
Theory
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Digital Communication System
• Source are converted into a sequence of binary digits which is called information sequence
• Represent the source by an efficient number of binary digits
• Efficiently converting the source into a sequence of binary digits is a process, which is called source encoding of data compression
• Channel encoder adds some redundancy into binary information sequence that can be used for handle noise and interference effects at the receiver.
• Digital modulator maps the binary information sequence into signal waveforms.
• Communication channel is used to send the signal from the transmitter to the receiver. Physical channels: the atmosphere, wireless, optical, compact disk,….
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Digital Communication System
• Digital demodulator receives transmitted signal contains the information which is corrupted by noise
• Cannel decoder attempts the reconstruct the original information sequence from knowledge of the code used by channel encoder.
• Source decoder attempts the reconstruct the original signal from the binary information sequence using the knowledge of the source encoding methods.
• The difference between the original signal and the reconstructed signal is measured of the distortion introduced by the digital communication system
• Estimate what was send, aiming at the minimum possible probability of making mistakes
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Communication channels and their characteristics
• Physical channel media
– magnetic-electrical signaled wire channel
– modulated light beam optical (fiber) channel
– antenna radiated wireless channel
– acoustical signaled water channel
• Virtual channel
– magnetic storage media
• Noise characteristic
– thermal noise (additive noise)
– signal attenuation
– phase distortion
– multi-path distortion
• Limitation of channel usage
– transmitter power
– receiver sensitivity
– channel capacity (such as bandwidth)
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Communication channels and their characteristics
Frequency range for guided wire channel
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Communication channels and their characteristics
Frequency range for wireless electromagnetic channels.
[ Adapted from Carlson
(1975), 2nd edition
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Communication channels and their characteristics
• Additive noise channel
= α ( ) + ( )
+
= α ( ) + ( )
• where α is the attenuation factor, s ( t ) is the transmitted signal, and n ( t ) is the additive random noise process.
• Called Additive Gaussian noise channel if n ( t ) is a
Gaussian noise process .
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Communication channels and their characteristics
• The linear filter channel with additive noise
– to ensure the specified bandwidth limitations .
Linear filter c(t)
Channel
+
( ) = ( ) ∗ ( ) + ( )
=
∞
−∞ c τ − ) + ( )
( ) = ( ) ∗ ( ) + ( )
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Communication channels and their characteristics
• The linear time-variant filter channel with additive noise
– Time-variant multipath propagation.
Linear time-variant
Filter c( τ ;t)
Channel
+ ( ) = ( ) ∗ τ + ( )
( ) = ( ) ∗ c τ + ( )
=
∞
−∞ c τ − ) + ( ) where c ( τ ;t ) is the response of the channel time t due to an impulse applied at time tτ .
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