UEE3504: Introduction to
Communication Systems
Po-Ning Chen, Professor
Dept. of Electrical and Computer Eng.
National Chiao Tung University
Background and Preview
To give you a basic understanding of
communications
Figure-1 Theory
 The next figure is always the “Figure 1” in
every book regarding communications.
© Po-Ning Chen@ece.nctu
Background 3
Communications
 What is communication (or more specifically,
communication engineering)?
 The transmission of information from one point to
another through a succession of certain processes.
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Background 4
Basic Elements Regard Communications
 Source of information
 Voice, music, picture, or computer data
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Background 5
Basic Elements Regard Communications
 Transmitter
 Source → Source Symbol (i.e., Source Word)
 Symbolize the information from a source
 Source Symbol → Code Word
 Encode the source symbol so that the other sources (i.e.,
noise and interfering signal) can hardly interfere the
information transmission.
 Code Word → Channel Symbol (i.e., Transmitted Signals)
 Modulate the code word into a form that is suitable for
transmission over the channel, which involves varying some
parameter of a carrier wave in accordance with the message
signal.
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Background 6
Basic Elements Regard Communications
 Noise/Interference
 Unwanted waves that tend to disturb the
transmission and processing of messages.
 Could be internal or external to the system.
 Could be additive or multiplicative (or both) to the
information-bearing signals.
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Background 7
Basic Elements Regard Communications
 Receiver
 Hard Decision
 Channel Symbol → Code Bit
 Decode from Code Bits to Code Word
 Code Word → Source Symbol → Source
 Soft Decision
 Decode from Channel Symbol to Code Word
 Code Word → Source Symbol → Source
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Background 8
Example: Basic Elements Regard
Communications
 Source = An alphabet “A”
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Background 9
Example : Basic Elements Regard
Communications
 Transmitter
 Source “A” → Binary Source Symbol (01000001)
 Symbolize the information from a source
 Source Symbol (01000001) → Code Word (000 111 000
000 000 000 000 111)
 Encode the source symbol by the three-times repetition code
so that the other sources (i.e., noise and interfering signals)
can hardly interfere the information transmission.
 001, 010, 011, 100, 101, 110 are not code words. Hence,
their appearance is possible only when noise is introduced.
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Background 10
Example : Basic Elements Regard
Communications
 Code Word (000 111 000 000 000 000 000 111) →
Channel Symbol (000 555 000 000 000 000 000
555 )
 Modulate the code word into some channel-permissible
(physical-medium permissible) symbols.
 Due to Channel Interference, we receive: 010 442
222 033 011 020 032 434
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Background 11
Example : Basic Elements Regard
Communications
 Receiver
 Hard Decision
 Channel Symbol 010 442 222 033 011 020 032 434 →
Code Bit (Threshold 2.5) 000 110 000 011 000 000 010
111
 Decode from Code Bits to Code Word (Majority Rule)
000 111 000 111 000 000 000 111
 Code Word 000 111 000 111 000 000 000 111 →
Source Symbol 01010001 → Source “Q”
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Background 12
Example : Basic Elements Regard
Communications
 Receiver
 Soft Decision
 Decode from Channel Symbol 010 442 222 033 011
020 032 434 to (channel-symbolized) Code Word 000
555 000 000 000 000 000 555
 By finding the minimum distance to legitimate codewords
000 and 111.
 E.g., d(033, 000) = (0-0)2+(3-0)2+(3-0)2 = 18
d(033, 555) = (0-5)2+(3-5)2+(3-5)2 = 33
 Code Word 000 111 000 000 000 000 000 111 →
Source Symbol 01000001→ Source “A”
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Background 13
Basic Modes of Communications
 Broadcasting
 Often, uni-directional.
 A single powerful transmitter to numerous
(inexpensive) receivers
 Example. Radio and TV.
 Point-to-point communication
 Often, bi-directional.
 Two entities exchange information.
 Example. Telephone.
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Background 14
Feature of Communications
 Statistics
 The source is statistical in nature.
 The noise and interference are naturally random.
 Principles of Communication Engineering: How to
design a communication system only based on the
knowledge of the statistics of the source and
interferences (without knowing exactly what the
true source and interference are)?
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Background 15
Feature of Communications
 Example
 Source
 We do not know if the next source symbol is 0 or 1.
 But, we do know the probability of the next source
symbol being 0, and also, the probability of the next
source symbol being 1.
 Noise/Interference
 We do not know what value the noise/interference will
take?
 But, we do know the noise is, say, Gaussian distributed.
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Background 16
Feature of Communications
 This is the reason why “Probabilities” (Chapter
1) is considered an important background to
communication study.
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Background 17
Primary Communication Resources
 Primary Communication Resources are
something “known” at the design stage.
 As aforementioned, source and noise/interference
are (often) something “unknown” at the design
stage.
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Background 18
Primary Communication Resources
 Examples of Primary Communication
Resources
 Transmitted Power
 Specifically, averaged power of the transmitted signals.
 A more useful measure than the absolute transmitted
power is the signal-to noise power ratio (SNR),
defined as the ratio of the average signal power to the
average noise power. This quantity is often expressed
in dB, 10 log10(SNR).
 Channel Bandwidth
 The band of frequencies for use of transmitting
messages.
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Background 19
Primary Communication Resources
 Design principle of a communication system
 How to efficiently use (usually in a tradeoff fashion)
the communication resources!
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Background 20
Sources of Information
 “Sources” can sometimes be viewed as one
kind of Communication Resources.
 For example, there are systems designed
specifically for “exchanging voices.”
 Such a system may not be apt to transmit computer
data.
 This introduces the subjects of “Source-Specific
Communication.”
 Next, we brief several sources commonly seen in
the literature.
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Background 21
Sources of Information: (1) Speech
 Features
 Voice spectrum extends well beyond 10kHz.
 Most of the average power is concentrated in the
range of 100 to 600 Hz.
Pitch Name
Freq (Hz)
Do
Re
Mi
Fa
So
261.6 293.7 329.6 349.2 392.0
La
Si
Do
440
493.9
523
 A band of 300 to 3100 Hz gives good articulation.
 The sound wave propagates through the air at a
speed of 300 meter/second.
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Background 22
Schematic representation of the vocal system
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Background 23
Sources of Information: (1) Speech
 The speech-production process may be viewed
as a form of filtering:
 A sound source excites a vocal tract filter.
Excitation
Glottal Volume
+
Vocal Tract
+
a1
+
a9
+
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a10
Speech
D
Lips
D
Background 24
Sources of Information: Speech
 As the sound propagates along the vocal tract,
the spectrum (i.e., frequency content) is shaped
by the frequency selectivity of the vocal tract —
a resonance phenomenon observed in organ
pipe.
 So the hearing mechanism is (and should be)
sensitive to frequency.
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Background 25
Source of Information: Music
 Originate from musical instruments, such as
piano, violin, and flute.
 It consists of:
 Melody: A time sequence of sounds.
 Harmony: A set of simultaneous sounds.
 Different from speech, the spectrum of a music
source may extend up to about 15 KHz.
 Accordingly, a much wider bandwidth resource is
demanded.
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Background 26
Source of Information: Pictures
 Two dimensional information.
 Classifications
 Dynamic pictures – Video, such as North American
Audio TV (NAA-TV)
 Still pictures – Facsimile.
 To transmit still picture over a telephone channel.
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Background 27
Source of Information: NAA-TV
 North American Analog TV
 525 horizontal lines, decomposed into two 262.5
line interlaced fields (See the next slide.)
 Completion of each interlaced field takes 1/60
second
 Horizontal line-scanning frequency is 262.5/(1/60) =
15.75 KHz.
 Hence, 30 still pictures are shown per second.
 The human “persistence of vision” phenomenon
will perceive these still pictures to be moving
pictures.
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Background 28
Source of Information: NAA-TV
Interlaced
raster scan.
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Background 29
Source of Information: NAA-TV
 In the NTSC (National Television System
Committee) system, a total of 4.2 MHz bandwidth
is demanded for TV transmission.
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Background 30
Source of Information: Computer Data
 The first code developed specifically for computer
communication (1967) – ASCII (American
Standard Code for Information Interchange).
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Background 31
Source of Information: Computer Data
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Background 32
Source of Information: Computer Data
 ASCII (American Standard Code for
Information Interchange)
Bit originates
from “Binary
Digit.”
 7-bit code for alphabetic numerical characters
 Bit 8 is sometimes used as parity-check bit or used
to form the extended ASCII code
 Even parity: Total number of 1’s is even.
 Odd parity: Total number of 1’s is odd.
 Extended ASCII code can be displayed but cannot
necessarily be printed out.
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Background 33
Source of Information: Computer Data
 Since ASCII is defined for communication, it
also includes some symbols for communication
purpose such as
 ENQ (enquiry) – 05X
 ETB (end of transmission block) – 17X
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Background 34
Source of Information: Computer Data
 RS (Recommended Standard) -232
Transmission
 Synchronous
 Asynchronous
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Background 35
Source of Information: Computer Data
 Asynchronous Serial Data






No clock or timing signal required.
ST : start bit
S : stop bit
P : parity bit
D6~D0 : data bits (often, exact one ASCII character)
Usually, 10 bit frame with even-parity/7-data-bit or
no-parity/8-data-bit.
frame
S
ST
D0
D1
D2
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D3
D4
D5
D6
P
S
ST
D0
D1
D2
D3
D4
D5
D6
P
S
Background 36
Source of Information: Computer Data
 Synchronous Serial Data





No start and stop bits required.
P : parity bit
D6~D0 : data bits (ASCII)
Clock : Timing signal.
Note that it requires sync character (after a certain
number of frames) to avoid losing synchronization.
If two sync characters are used. it is called bi-sync.
Data
D0
D1
D2
D3
D4
D5
D6
P
D0
D1
D2
D3
D4
Clock
© Po-Ning Chen@ece.nctu
Background 37
Source of Information:
Computer Data
 Windows 98
 Baud rate : 110 baud~921600
baud (The # is different for
different computers)
 (E)ven parity, (O)dd parity,
(N)one-parity, Mark, Space
 4~8 Data-bit
 1, 1.5, 2 Stop-bit
The name of “mark” and
“space” for 1 and 0
comes from the days of
telegraphy.
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Background 38
Source of Information: Computer Data
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Background 39
Source of Information: Computer Data
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Background 40
Source of Information: Computer Data
 The computer data stream so formed is then
applied to a device called a modem (modulatordemodulator).
 Unlike source traffic from speech or video, the
computer data is often bursty rather than
continuous.
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Background 41
Missed Part of Figure-1 in Textbook
 Source before entering the transmitter is often
compressed (in order to save time or space).
 This part is missed in Figure 1 of the textbook.
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Background 42
With a source encoder, a digital communication system
(rather an analog communication system) is formed.
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Background 43
Data Compression
 Lossless Data Compression (or Data
Compaction)
 Completely reversible (or asymptotically
reversible).
 E.g., Lempel-Ziv algorithm (PKZIP, compress, etc),
which will be introduced in Chapter 9.
 Lossy Data Compression
 Non-reversible with loss of information in a
controlled manner.
 E.g., JPEG, MPEG, etc.
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Background 44
Lossy Data Compression for Images
 JPEG (Joint Photographic Experts Group)
 An image coding standard
 Pixels are grouped in 8-by-8 block.
 DCT (discrete cosine transform) is then applied to
each block.
 Quantize each of the 64 DCT coefficients according
to a pre-specified table.
 Huffman-encode (introduced in Chapter 9) the
quantization results.
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Background 45
Lossy Data Compression for Images
 DCT
7
7
1
 (2 x  1)u
F (u, v )  C (u )C ( v ) f ( x, y ) cos
4
16

x 0 y 0
  ( 2 y  1)v 
 cos

16
 

1 7 7
 (2 x  1)u
f ( x, y )   C (u )C (v ) F (u, v ) cos
4 u 0 v 0
16

  ( 2 y  1)v 
 cos

16
 

where
© Po-Ning Chen@ece.nctu
 1
, for u  0

C (u )   2
 1
otherwise
Background 46
Lossy Data Compression for Video
 MPEG-1 (Motion Photographic Experts Group)
video coding standard
 A video coding standard primarily for 30 fps
(frames per second) video
 Result in a bit-stream rate of 1.5 megabits per
second
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Background 47
Lossy Data Compression for Video
 Design objective : To reduce four kinds of
redundancies:
 Interframe (temporal) redundancy
 Its reduction is achieved through the use of prediction to
estimate each frame from its neighbors.
 The resulting prediction error is transmitted for motion
estimation and compensation.
 Interpixel redundancy within a frame
 Psychovisual redundancy
 Entropic coding redundancy
© Po-Ning Chen@ece.nctu
Background 48
Lossy Data Compression for Video
 As with JPEG, the last three redundancies are
reduced through the combined use of DCT,
quantization and lossless entropic coding.
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Background 49
Lossy Data Compression for Audio
 MPEG-1 audio coding standard
 A perceptual (waveform) coder, as contrary to a
vocoder
 The amplitude-time waveform of the decoded audio
signal closely approximates that of the original audio
signal.
© Po-Ning Chen@ece.nctu
Background 50
Lossy Data Compression for Audio
 Encoding process
 Time-Frequency Mapping (sub-band decomposition)
 Psychoacoustic modeling (operates according to the
psychoacoustic behavior of the human auditory system)
 Quantization and coding
 Frame-packing (format the quantized audio samples
into a decodable bit stream)
© Po-Ning Chen@ece.nctu
Background 51
Lossy Data Compression for Audio
 Why Psychoacoustic modeling?
 Human ears have a perceptual phenomenon known as
auditory masking.
 Specifically, the human ear does not perceive
quantization noise in a given frequency band if the
average noise power lies below the masking threshold
 The masking threshold varies with frequency across
the band.
 Hence, a perceptual weighting filter is applied to
waveforms before quantization.
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Background 52
OSI (Open System Interconnection) model; the acronym DLC in the
middle of the figure stands for data link control.
 OSI
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Background 53
Communication Networks
 OSI reference model was developed by ISO
(International Organization for Standardization)
in 1977.
 Figure 1 only concerns PHY layer.
 Now we take a quick look of its relation with
higher layers, such as Network layers.
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Background 54
Communication Networks
Network Layer : Routers
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Background 55
Communication Networks
 Routing mechanisms
 Circuit Switching
 Uninterrupted, exclusively use of links
 E.g., Telephone.
 Packet Switching
 Shared-on-demand links
© Po-Ning Chen@ece.nctu
Background 56
Communication Networks
 Why OSI reference model?
 Each layer can perform its related subset of
primitive functions without knowing the
implementation details of the next lower layer.
 The adjacent layers communicate through welldefined interfaces, which defines the services
offered by the lower layer to the upper layer.
© Po-Ning Chen@ece.nctu
Background 57
Communication Networks
 The entities that comprise the corresponding
layers on different systems are referred to as
peer processes.
 Two peer entities then communicate through a
well-defined set of rules of procedures, named
Protocol.
 Again, this text/course primarily considers PHY
layer.
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Background 58
Internet
 Internet – A special communication network, as
contrary to an Intranet.
 Features of Internet
 Applications are carried out independently of the
technology employed to construct the network.
 The network technology is capable of evolving
without affecting the applications.
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Background 59
Internet
 Architecture of
Internet
Cross-Router Data Exchange
Direct Data Exchange
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Background 60
Internet Protocol (IP)
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Background 61
Internet Service
 Internet Service is “Best Effort” in nature.
 As a consequence, no guarantees of timely
transmission, and even delivery.
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Background 62
Communication Channels
 Channels, where the noise/interference resides,
can be roughly divided into two groups:
 Guided propagation channels
 E.g., telephone channels, coaxial cables, and optical
fibers
 Free propagation channels
 E.g., broadcast channels, mobile radio channels, and
satellite channels
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Background 63
Communication Channels: (i) Telephone
Channel
 Features of telephone channel
 A channel performs “voice → electrical signal →
sound”
 Band-limited channel
 A speech signal (male or female) is essentially limited
to a band from 300 to 3100 Hz.
© Po-Ning Chen@ece.nctu
Background 64
Communication Channels: (i) Telephone
Channel
 Measures used in characterizing channel
 Insertion loss = 10 log10 (P0/PL)
 PL = power delivered to a load from a source via the
channel
 P0 = power delivered to the same source not via the channel
Channel
PL
P0
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Background 65
Communication Channels: (i) Telephone
Channel
 Envelope delay
 The negative of the derivative of the phase response with
respect to the angular frequency w = 2f.
 Example. Envelope delay = a for the next channel.
g (t )
H ( f )  e - j 2fa
g (t - a )
The phase response of a channel filter H(f) is (f), where
H ( f ) | H ( f ) | exp[ j ( f )].
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Background 66
Communication Channels: (i) Telephone
Channel
Insertion Loss
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Envelope Delay
Background 67
Communication Channels: (ii) Coaxial
Cable
 A coaxial cable offers a greater degree of
immunity to EMI, and a much higher
bandwidth than twisted pair telephone lines.
 Example of its applications
 Local area network in an office environment.
 Cable television
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Background 68
Communication Channels: (iii) Optical Fiber
 Features
 Enormous potential bandwidth
 The bandwidth is roughly equal to 10% of the carrier
frequency (2  1014 Hz).
 Notably, the transmission attainable limit (for additive
white Gaussian noise with SNR=10dB) is around
C  B log 2 (1  SNR)
 (2  1013 ) log 2 (1  1010 dB /10 )
 6.91886  1013 bit per second
 6918 .86 Gigabit per second
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Background 69
Communication Channels: (iii) Optical Fiber
 Low transmission loss
 0.1dB/km
 Immunity to electromagnetic interference
 Small size and weight (thinner than human hair)
 Ruggedness and flexibility
 Possibility of being bent or twisted without damage.
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Background 70
Communication Channels: (iv) Wireless
Broadcast Channels
 Transmission
 Up-convert the modulated baseband informationbearing signal to Radio Frequency (RF) passband
signal
 Transmit the RF passband signal via antenna
 Reception
 Pick up the radiated waves by an antenna.
 Down-convert the received passband signal to
baseband signal (perhaps through an intermediate
step called the intermediate frequency (IF) band).
© Po-Ning Chen@ece.nctu
Background 71
Communication Channels: (v) Mobile Radio
Channels
 The main difference between this channel and
the previous channel is the consideration of
mobility.
 Due to mobility, there is no “line-of-sight” path for
communication;
 rather, radio propagation takes place mainly by way
of scattering from the surfaces of the surrounding
buildings and by diffraction over and around them.
 This results in a multipath fading transmission.
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Background 72
Communication Channels: (v) Mobile Radio
Channels
(1 , 1 )
s (t )
Transmitter
( 2 , 2 )
1 s ( t -  1 )
  2 s (t -  2 )
Receiver
  3 s(t -  3 )
 n(t )
( 3 , 3 )
Notably, j and j
can also be
functions of time.
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Background 73
Communication Channels: (vi) Satellite
Channels
 Satellite communications
 The satellite is placed in geostationary orbit.
 Geostationary orbit
1. The satellite orbits the Earth in exactly 24 hours
(geosynchronous).
2. The satellite is placed in orbit directly above the equator on
an eastward heading.
 It acts as a powerful repeater in the sky.
 It often uses 6 GHz for the uplink and 4 GHz for
the downlink.
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Background 74
Communication Channels: (vi) Satellite
Channels
 The 6/4-GHz band offers the following attributes:
1. Relatively inexpensive microwave equipment.
2. Low attenuation due to rainfall
 Rainfall is a primary atmospheric cause of signal loss.
3. Insignificant sky background noise
 The sky background noise due to random noise emissions
from galactic, solar and terrestrial sources reaches its lowest
level between 1 and 10 GHz.
© Po-Ning Chen@ece.nctu
Background 75
Communication Channels: (vi) Satellite
Channels
 A typical satellite in the 6/4-GHz band is assigned a
500 MHz bandwidth, which is divided among 12
transponders.
 Each transponder can carry at least one color television
signal, 1200 voice circuits, or digital data at a rate of
50 Mb/s.
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Background 76
Classifications of Communication Channels
(according to the natures or resources)
 Linear or non-linear
 A wireless radio channel is linear whereas a satellite
channel is usually non-linear
 Time invariant or time varying
 An optical fiber is time invariant, whereas a mobile
radio channel is typically time varying.
 Band limited or power limited
 A telephone channel is band limited, whereas an
optical fiber link and a satellite channel are both
power limited.
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Background 77
Classification of Modulation Process
 Continuous-wave modulation
 A sinusoidal wave is used as the carrier.
 It can be further classified as:
 Amplitude modulation (AM) : Amplitude of the carrier
is varied in accordance with the message.
 Frequency modulation (FM) : Frequency of the carrier
is varied in accordance with the message.
 Phase modulation (PM) : Phase of the carrier is varied
in accordance with the message.
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Background 78
Classification of Modulation Process
 Pulse modulation
 The carrier consists of a sequence of rectangular
pulses.
 It can be sub-divided to:
 Analog pulse modulation
 Digital pulse modulation
© Po-Ning Chen@ece.nctu
Background 79
Classification of Modulation Process
 Analog pulse modulation
 Pulse-amplitude modulation (PAM), pulse-duration
modulation (PDM), pulse-position modulation (PPM)
 The amplitude, duration, position of the pulses varies
in accordance with the message signals.
 Digital pulse modulation
 Pulse-code modulation (PCM)
© Po-Ning Chen@ece.nctu
Background 80
Example of PAM (Telephone System)
Sampling the
voice according
to some clocks.
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Background 81
Example of PCM
 Originate from PAM, but with the following
modifications.
 Convert the (sampled) pulse into bits, e.g., 8 bits.
 All 8 bits of the input PCM signal are gated to the
output port in parallel.
 The gate can now be designed using “truth table”
which facilitates system integration or multiplexing.
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What is multiplexing?
 To combine (several modulated) signals for
their simultaneous (or concurrent) transmission.




Frequency-division multiplexing (FDM)
Time-division multiplexing (TDM)
Code-division multiplexing (CDM)
Wavelength-division multiplexing (WDM),
specifically for use of optical fibers.
 Some treats WDM as a special case of FDM, since c =
f l.
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Background 83
Shannon’s Information Capacity Theorem
 The underlying limit for digital
communications
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Background 84
Transmission Rate = Source code bit per second (Information bit
per second)
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Background 85
Shannon’s Information Capacity Theorem
 Reliable transmission rate (for pre-specified
modulator, channel and demodulator).
 The rate for which a proper design of channel
encoder-decode pair can fulfill arbitrarily small
error requirement.
 Shannon finds the general formula for the
largest reliable transmission rate, which he
baptized as “(coding) channel capacity.”
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Background 86
Shannon’s Information Capacity Theorem
 For additive white Gaussian noise as
demodulator output = modulator input + Gaussian
the channel capacity is equal to
C = B log2(1+SNR) bit/second, where B is the bandwidth.
 It took 45 years (1948~1993) of research to
reach this “capacity!”
© Po-Ning Chen@ece.nctu
Background 87
An Exemplified Ideal Digital Communication
Problem – Phase Shift Keying
Channel
Encoder
…0110
…,-m(t), m(t), m(t), -m(t)
Modulator
m(t)
No IF here because
this is an ideal
system.
T
Local carrier
cos(2fct)
0110…
>0
<
yT

T
0
dt

x(t)
w(t)

Carrier wave
Accos(2fct)
s(t)

correlator
© Po-Ning Chen@ece.nctu
Background 88
An Exemplified Ideal Digital Communication
Problem – Phase Shift Keying
 Assume that the local carrier (at the receiver
end) is exactly the same as the transmitter
carrier.
 Assume that the correlator is completely
synchronized with the transmitter.
 So the integration inside correlator covers a
complete message signal m(t). In other words, it
will not happen that the integration inside correlator
covers 80% of the current m(t) but 20% of the
previous m(t).
© Po-Ning Chen@ece.nctu
Background 89
yT   x (t ) cos(2f c t )dt
T
0
  [ s(t )  w(t )] cos(2f c t )dt
T
0
  [  Ac cos(2f c t )  w(t )] cos(2f c t )dt
T
0
  Ac  cos ( 2f c t )dt   w(t ) cos(2f c t )dt
T
0
2
T
0
T
1 - cos(4f c t )
dt   w(t ) cos(2f c t )dt
  Ac 
0
0
2
T
T
1
1
  AcT  Ac  cos(4f c t )dt   w(t ) cos(2f c t )dt
0
0
2
2
T
1
  AcT   w(t ) cos(2f c t )dt (By assuming that fc is a
0
2
multiple of 1/T.)
T
© Po-Ning Chen@ece.nctu
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An Exemplified Ideal Digital Communication
Problem – Phase Shift Keying
 Some interesting issues to consider:
 What if the local carrier does not equal the
transmitter carrier.
yT   [  Ac cos(2f rc t )  w(t )] cos(2f tc t )dt
T
0
 What if fc is not a multiple of 1/T.
 What if the receiver does not synchronize with the
transmitter?
 What is the BER of this system?
© Po-Ning Chen@ece.nctu
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An Exemplified Ideal Digital Communication
Problem – Phase Shift Keying
 Is the correlator receiver optimal in the sense of
BER?
 Is the “sign-decision” optimal in the sense of BER?
 Is the above combination optimal in the sense of
BER?
 Is the BER robust for imperfect system, such as
timing and carrier mismatch?
 Is the rectangular m(t) a fine choice? Moreover, is
PSK a fine choice? If affirmative, in what sense?
 ….
© Po-Ning Chen@ece.nctu
Background 92
An Exemplified Ideal Digital Communication
Problem – Phase Shift Keying
 All these problems will be hopefully answered
in this course (and subsequent courses).
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Background 93