2. COMMUNICATION ENGINEERING
• Course Code : ISE301
• Course title : Telecommunication Systems
• Credit Hours : 3
• Semester : Fall 2009
• Instructor : Prof. Dr. Tayfun AKGÜL
• Course Page : http://atlas.cc.itu.edu.tr/~akgultay/
• Refernece Book : A. B. Carlson, P.B. Crilly, J.C.
Rutledge, “Communication Systems,” McGraw-Hill,
4th Edition, 2002.
3. Syllabus - I
• Introduction to Signals
• General Topics in Communications and Modulation
• Spectral Analysis
– Fourier Series
– Fourier Transform
– Frequency Domain Representation of Finite Energy
Signals and Periodic Signals
– Signal Energy and Energy Spectral Density
– Signal Power and Power Spectral Density
• Signal Transmission through a Linear System
– Convolution Integral and Transfer Function
– Ideal and Practical Filters
– Signal Distortion over a Communication Channel
4. Syllabus - II
• Amplitude (Linear) Modulation (AM)
– Amplitude Modulation (AM)
– Double Side Band Suppressed Carrier (DSBSC)
– Single Side Band (SSB)
– Vestigial Side Band (VSB)
• AM Modulator and Demodulator Circuits
– AM transmitter block diagram
• Angle (Exponential) Modulation
– Phase Modulation (PM)
– Frequency Modulation (FM)
– Modulation Index
– Spectrum of FM Signals
– Relationship between PM and FM
• FM Modulator and Demodulator Circuits
• FM Transmitter Block Diagram
• FM Receiver
5. Outline
• Signals and Systems
– Signals and Systems
– What is a signal?
– Signal Basics
– Analog / Digital Signals
– Real vs Complex
– Periodic vs. Aperiodic
– Bounded vs. Unbounded
– Causal vs. Noncausal
– Even vs. Odd
– Power vs. Energy
• What is a communications
system?
– Block Diagram
– Why go to higher frequencies?
• Telecommunication
• Wireless Communication
• Another Classification of
Signals (Waveforms)
• Power, Distortion, Noise
• Shannon Capacity
• How transmissions flow over
media
– Coaxial Cable
– Unshielded Twisted Pair
– Glass Media
– Wireless
– Connectors
– The Bands
6. Signals are variables that carry information
System is an assemblage of entities/objects, real or abstract,
comprising a whole with each every component/element
interacting or related to another one.
Systems process input signals to produce output signals
Examples
i. Motion, sound, picture, video, traffic light…
ii. Natural system (ecosystem), human-made system
(machines, computer storage system), abstract system
(traffic, computer programs), descriptive system (plans)
Signal and System
7. Signal Examples
• Electrical signals --- voltages and currents in a
circuit
• Acoustic signals --- audio or speech signals
(analog or digital)
• Video signals --- intensity variations in an image
(e.g. a CAT scan)
• Biological signals --- sequence of bases in a
gene
• Noise: unwanted signal
:
9. Definitions
• Voltage – the force which moves an electrical current
against resistance
• Waveform – the shape of the signal (previous slide is a
sine wave) derived from its amplitude and frequency
over a fixed time (other waveform is the square wave)
• Amplitude – the maximum value of a signal, measured
from its average state
• Frequency (pitch) – the number of cycles produced in a
second – Hertz (Hz). Relate this to the speed of a
processor eg 1.4GigaHertz or 1.4 billion cycles per
second
10. Signal Basics
Continuous time (CT) and discrete time (DT) signals
CT signals take on real or complex values as a function of an independent
variable that ranges over the real numbers and are denoted as x(t).
DT signals take on real or complex values as a function of an independent
variable that ranges over the integers and are denoted as x[n].
Note the subtle use of parentheses and square brackets to distinguish between
CT and DT signals.
11. Analog Signals
• Human Voice – best example
• Ear recognises sounds 20KHz or less
• AM Radio – 535KHz to 1605KHz
• FM Radio – 88MHz to 108MHz
12. Digital signals
• Represented by Square Wave
• All data represented by binary values
• Single Binary Digit – Bit
• Transmission of contiguous group of bits is a bit
stream
• Not all decimal values can be represented by
binary
1 0 1 0 1 0 1 0
13. Analogue vs. Digital
Analogue Advantages
• Best suited for audio and video
• Consume less bandwidth
• Available world wide
• Less susceptible to noise
Digital Advantages
• Best for computer data
• Can be easily compressed
• Can be encrypted
• Equipment is more common and less expensive
• Can provide better clarity
14. Analog or Digital
• Analog Message: continuous in amplitude and over
time
– AM, FM for voice sound
– Traditional TV for analog video
– First generation cellular phone (analog mode)
– Record player
• Digital message: 0 or 1, or discrete value
– VCD, DVD
– 2G/3G cellular phone
– Data on your disk
– Your grade
• Digital age: why digital communication will prevail
15. A/D and D/A
• Analog to Digital conversion; Digital to
Analog conversion
– Gateway from the communication device to the
channel
• Nyquist Sampling theorem
– From time domain: If the highest frequency in the
signal is B Hz, the signal can be reconstructed
from its samples, taken at a rate not less than 2B
samples per second
16. A/D and D/A
• Quantization
– From amplitude domain
– N bit quantization, L intervals L=2N
– Usually 8 to 16 bits
– Error Performance: Signal to noise ratio
17. Real vs. Complex
Q. Why do we deal with complex signals?
A. They are often analytically simpler to deal with than real signals,
especially in digital communications.
18. Periodic vs. Aperiodic Signals
Periodic signals have the property that x(t + T) = x(t) for all t.
The smallest value of T that satisfies the definition is called the
period.
Shown below are an aperiodic signal (left) and a periodic signal
(right).
19. A causal signal is zero for t < 0 and an non-causal signal is zero
for t > 0
Right- and left-sided signals
A right-sided signal is zero for t < T and a left-sided signal is zero
for t > T where T can be positive or negative.
Causal vs. Non-causal
21. Even vs. Odd
Even signals xe(t) and odd signals xo(t) are defined as
xe(t) = xe(−t) and xo(t) = −xo(−t).
Any signal is a sum of unique odd and even signals. Using
x(t) = xe(t)+xo(t) and x(−t) = xe(t) − xo(t), yields
xe(t) =0.5(x(t)+x(−t)) and xo(t) =0.5(x(t) − x(−t)).
22. Signal Properties: Terminology
• Waveform
• Time-average operator
• Periodicity
• DC value
• Power
• RMS Value
• Normalized Power
• Normalized Energy
23. Power and Energy Signals
• Power Signal
– Infinite duration
– Normalized power
is finite and non-
zero
– Normalized energy
averaged over
infinite time is
infinite
– Mathematically
tractable
• Energy Signal
– Finite duration
– Normalized energy
is finite and non-
zero
– Normalized power
averaged over
infinite time is zero
– Physically
realizable
• Although “real” signals are energy signals, we
analyze them pretending they are power signals!
24. The Decibel (dB)
• Measure of power transfer
• 1 dB = 10 log10 (Pout / Pin)
• 1 dBm = 10 log10 (P / 10-3) where P is in Watts
• 1 dBmV = 20 log10 (V / 10-3) where V is in Volts
28. Telecommunication
• Telegraph
• Fixed line telephone
• Cable
• Wired networks
• Internet
• Fiber communications
• Communication bus inside computers to
communicate between CPU and memory
29. Wireless Comm Evolution:
UMTS (3G)
http://www.3g-generation.com/
http://www.nttdocomo.com/reports/010902_ir_presentation_january.pdf
30. Wireless Communications
• Satellite
• TV
• Cordless phone
• Cellular phone
• Wireless LAN, WIFI
• Wireless MAN, WIMAX
• Bluetooth
• Ultra Wide Band
• Wireless Laser
• Microwave
• GPS
• Ad hoc/Sensor Networks
31. Comm. Sys. Bock Diagram
)
(
~ t
m
Tx
s(t)
Channel
r(t)
m(t)
Noise
Rx
Baseband
Signal
Baseband
Signal
Bandpass
Signal
• “Low” Frequencies
• <20 kHz
• Original data rate
• “High” Frequencies
• >300 kHz
• Transmission data rate
Modulation
Demodulation
or
Detection
Formal definitions will be provided later
32. Aside: Why go to higher
frequencies?
Tx l/2
Half-wave dipole antenna
c = f l
c = 3E+08 ms-1
Calculate l for
f = 5 kHz
f = 300 kHz
There are also other reasons for going from baseband to bandpass
33. Another Classification of Signals
(Waveforms)
• Deterministic Signals: Can be modeled as a
completely specified function of time
• Random or Stochastic Signals: Cannot be
completely specified as a function of time; must be
modeled probabilistically
• What type of signals are information bearing?
34. Power, Distortion, Noise
• Transmit power
– Constrained by device, battery, health issue, etc.
• Channel responses to different frequency and different time
– Satellite: almost flat over frequency, change slightly over time
– Cable or line: response very different over frequency, change
slightly over time.
– Fiber: perfect
– Wireless: worst. Multipath reflection causes fluctuation in
frequency response. Doppler shift causes fluctuation over time
• Noise and interference
– AWGN: Additive White Gaussian noise
– Interferences: power line, microwave, other users (CDMA
phone)
35. Shannon Capacity
• Shannon Theory
– It establishes that given a noisy channel with information
capacity C and information transmitted at a rate R, then if
R<C, there exists a coding technique which allows the
probability of error at the receiver to be made arbitrarily
small. This means that theoretically, it is possible to
transmit information without error up to a limit, C.
– The converse is also important. If R>C, the probability of
error at the receiver increases without bound as the rate is
increased. So no useful information can be transmitted
beyond the channel capacity. The theorem does not
address the rare situation in which rate and capacity are
equal.
• Shannon Capacity s
bit
SNR
B
C /
)
1
(
log2
36. How transmissions flow over
media
• Simplex – only in one direction
• Half-Duplex – Travels in either direction,
but not both directions at the same time
• Full-Duplex – can travel in either direction
simultaneously
37. Coaxial Cable
•First type of networking
media used
•Available in different
types (RG-6 – Cable TV,
RG58/U – Thin Ethernet,
RG8 – Thick Ethernet
•Largely replaced by
twisted pair for networks
38. Unshielded Twisted Pair
Advantages
Inexpensive
Easy to terminate
Widely used, tested
Supports many
network types
Disadvantages
Susceptible to interference
Prone to damage during
installation
Distance limitations not
understood or followed
39. Glass Media
• Core of silica, extruded glass or plastic
• Single-mode is 0.06 of a micron in diameter
• Multimode = 0.5 microns
• Cladding can be Kevlar, fibreglass or even steel
• Outer coating made from fire-proof plastic
Advantages
Can be installed over long
distances
Provides large amounts of
bandwidth
Not susceptible to EMI RFI
Can not be easily tapped (secure)
Disadvantages
Most expensive media to
purchase and install
Rigorous guidelines for
installation
41. Wireless (2)
• Radio transmits at 10KHz to 1KHz
• Microwaves transmit at 1GHz to 500GHz
• Infrared transmits at 500GHz to 1THz
• Radio transmission may include:
– Narrow band
– High-powered
– Frequency hopping spread spectrum (the hop is
controlled by accurate timing)
– Direct-sequence-modulation spread spectrum (uses
multiple frequencies at the same time, transmitting
data in ‘chips’ at high speed)
44. The Bands
VLF LF MF HF VHF UHF SHF EHF
Submillimeter
Range
ELF
3MHz 30MHz300MHz 3GHz 30GHz 300GHz
Far
Infra-
Red
300KHz
30KHz 3THz
300mm
Radio Optical
3KHz
Near
Infra-
Red
700nm
1PetaHz
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B
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600nm 400nm
500nm
Ultraviolet
1ExaHz
X-Ray
1500nm
