Telecommunication Systems1

Prof. Dr. Tayfun Akgül

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.

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

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

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

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

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

:

Measuring Signals

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400 421 442 463 484 505 526 547 568 589 610 631 652 673 694 715

Period

Am

plitude

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

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.

Analog Signals

• Human Voice – best example

• Ear recognises sounds 20KHz or less

• AM Radio – 535KHz to 1605KHz

• FM Radio – 88MHz to 108MHz

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

binary1 0 1 0 1 0 1 0

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

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

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

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

Real vs. ComplexQ. Why do we deal with complex signals? A. They are often analytically simpler to deal with than real

signals, especially in digital communications.

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).

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

Bounded vs. Unbounded Every system is bounded, but meaningful signal is always

bounded

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), yieldsxe(t) =0.5(x(t)+x(−t)) and xo(t) =0.5(x(t) − x(−t)).

Signal Properties: Terminology

• Waveform• Time-average operator• Periodicity• DC value• Power• RMS Value• Normalized Power• Normalized Energy

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!

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

Communication System

A B

Engineering System

Genetic System

Social System

History and fact of communication

What is a communications system?

• Communications Systems: Systems designed to transmit and receive information

Info Source

Info Source

Info Sink

Info Sink

CommSystem

Block Diagram

ReceiverRx

receivedmessage

tosink

)(~ tm

TransmitterTx s(t)

transmittedsignal

Channelr(t)

receivedsignal

m(t)message

from source

Info Source

Info Source

Info Sink

Info Sink

n(t)noise

Telecommunication

• Telegraph

• Fixed line telephone

• Cable

• Wired networks

• Internet

• Fiber communications

• Communication bus inside computers to communicate between CPU and memory

Wireless Comm Evolution: UMTS (3G)

http://www.3g-generation.com/http://www.nttdocomo.com/reports/010902_ir_presentation_january.pdf

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

Comm. Sys. Bock Diagram

)(~ tmTxs(t)

Channelr(t)

m(t)

Noise

RxBaseband

SignalBaseband

SignalBandpassSignal• “Low” Frequencies

• <20 kHz• Original data rate

• “High” Frequencies• >300 kHz• Transmission data rate

ModulationDemodulation

orDetection

Formal definitions will be provided later

Aside: Why go to higher frequencies?

Tx /2

Half-wave dipole antenna

c = f c = 3E+08 ms-1

Calculate for

f = 5 kHz

f = 300 kHz

There are also other reasons for going from baseband to bandpass

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?

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)

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

sbitSNRBC /)1(log2

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

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

Unshielded Twisted Pair Advantages

InexpensiveEasy to terminateWidely used, testedSupports many

network types

DisadvantagesSusceptible to interferenceProne to damage during

installationDistance limitations not

understood or followed

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

Wireless

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)

Connectors

Fibre Optic

Thicknet

RJ45

T-Piece

Token Ring

The Bands

VLF LF MF HF VHF UHF SHF EHF

Su

bm

illi

me

ter

Ra

ng

e

ELF

3MHz 30MHz300MHz 3GHz 30GHz 300GHz

FarInfra-Red

300KHz30KHz 3THz

300m

Radio Optical

3KHz

NearInfra-Red

700nm

1PetaHz

Red

Orange

Yellow

Green

Blue

Indigo

Violet

600nm 400nm500nm

Ultraviolet

1ExaHz

X-Ray

1500nm