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Data Communication, Introduction 1

Data Communication

Introduction

Data Communication, Introduction 2

Objective

This course covers the basics of digital communications. The topics studied include:

The physical layer of communication systems (physical media, signals, bandwidth, capacity, modems, etc.)Data transmission schemesError detection and correction

Data Communication, Introduction 3

ReferencesP. Lathi, Modern Digital and Analog Communication Systems, Third Edition, Oxford University Press, 1998. Simon Haykin, Communication Systems, Fourth Edition, John Wiley and Sons, 2000.F. Halsall, Data Communications, Computer Networks and Open Systems.,Addison-Wesley, 4th Ed., 1996W. Stallings, Data and Computer Communications. , Prentice-Hall, 5th Ed., 1997)

Data Communication, Introduction 4

Course OutlineIntroductionAmplitude Modulation DSB, AM, SSB, Receivers, BandwidthAngle (Phase) Modulation FM, PM, Receivers, BandwidthA Survey of Probability and Noise

Random Variables and ProcessesAdditive White Gaussian Noise (AWGN)

Binary Digital Communication in AWGNBaseband/Passband, SpectraOn/Off, Orthogonal, AntipodalMinimum Euclidean Distance ReceiverMaximum Correlation ReceiverMatched Filter ReceiverPerformanceNon-coherent Signaling

2

Data Communication, Introduction 5

Course Outline, Cont.Nonbinary Digital Communication in AWGN

Baseband/PassbandOrthonormal BasesPAM, PSK, FSK, QAMMinimum Euclidean Distance ReceiverMaximum Correlation ReceiverMatched Filter ReceiverPerformance

Multi-channel SchemesMultiple Access Schemes

TDMA, FDMA, CDMAError Control:

Channel codingBlock codesConvolution codesChannel capacity

Data Communication, Introduction 6

Consider two sentences, which one carries more information?

The sun will rise tomorrow.There will be a tornado tomorrow.

The measure of information is its probability: If an event has the probability , it has the self-information

( )i iP x P=ix

1log logi b i bi

I PP

≡ − =

1iP =

1 1

0,1log log log

i i

ij b b i b ij i ji j

P I

I P P I IPP

− −

→ → ∞⎧⎪⎨ = = + = +⎪⎩

0,0 1,

i i

i j i j

I PI I P P≥ ≤ ≤⎧

⎨ > <⎩

1 2 1 2 2( ) ( ) 1/ 2, log 2 1bitP x P x I I= = = = =

Data Communication, Introduction 7

Transmitting Information by Telecommunication Systems

Data Communication, Introduction 8

Mediums and Electromagnetic Spectra [5]

3

Data Communication, Introduction 9

Signals A set of voice tones:

Several tones superimposed (added)Tones can not be separated from the time domain representation Frequency components can be

“This is some speech”

BurstsAmplitude variesFrequency (phase) variesMany other practical sources are bursty as

video signals Ethernet data packets

Often analog sources are digitized for transmission that carries several benefits as

error correction & detectioneasy multiplexing Data Communication, Introduction 10

Classification of Signals Deterministic signalsRandom signals; pure or pseudo-randomEnergy signals; pulsesPower signal; periodicContinuous time - discrete time:Analog – DigitalReal – Complex

Data Communication, Introduction 11

Time Domain Representation Can Only Seldom Reveal Small Signal Impairments

Data Communication, Introduction 12

Frequency Domain Representation of the Same Signal Reveals More!

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Data Communication, Introduction 13

Examples of Signal SpectraAll finite signals have spectra that can be determined via Fourier transformation (pulses) or Fourier series (periodic signals)

Ref: [2] Chapter 2Data Communication, Introduction 14

Noise and InterferenceIn practical communication systems signals are blurred by noise and interference:

Time domain Frequency domain

Data Communication, Introduction 15

Modeling Transmission Channels

Information is always transmitted in channels as radio path (wireless cellular channel, microwave link, satellite link) or in wireline channels as coaxial cable, fiber optic cable or wave guide. Note that information storage is also a transmission channelMost common channels we discuss are

Channel transfer function/linear/nonlinear

Channel transfer function/linear/nonlinear +

( )n t= ⊗ +( ) ( ) ( ) ( )r t s t c t n t

(AWGN channel (usually transferfunction is linear) and n(t) is Gaussian,white noise)

( )s t

channel

τ= ⊗ + = − +∫( ) ( ) ( ) ( ) ( ) ( )u

r t s c t n t s t c t dt n t

(u: where integrand exists) Data Communication, Introduction 16

Linear and Nonlinear Channels

Linear channels: generate never new frequency componentscharacterized by transfer function

Non-linear systems:characterized by transfer characteristics

Note: Often non-linearity in transmission is generated by transmitter

( )iv t

( )ov t

( )iv t

( )ov t

Linear channel Nonlinear channel

1( ) ( )

Nu

o o u iu

v t a a v t=

= +∑ with ( ) sin( ), 2iv t t Nω= =

produces 0 1 2( ) sin( ) / 2(1 cos(2 ))ov t a a t a tω ω= + + −

= +0( ) ( )iv t Kv t M

5

Data Communication, Introduction 17

e Channel

Most information channels are time-variable (fading) channels: cable, microwave link, cellular channel. Received signal is

In frequency domain, (in differential time instant) there exists a frequency response and for this instance we may write

( ) ( ) ( ) ( ; )r t n t s t c tτ= + ⊗

1 1( ; ) ( )C f C fτ ≈

1 1( ) ( ) ( ) ( )R f N f S f C f= +

Data Communication, Introduction 18

Multiplexing

Multiple information channels are transported by using multiplexingIn multiple access, same channel is used to transmit multiple messages to different usersFixed multiple access (originally for circuit switched networks):

TDMA (time division multiple access), users occupy different time slotsFDMA (frequency division multiple access), users occupy different frequency bandsCDMA (code division multiple access), users occupy the same frequency band but modulate their messages with different codes

Statistical multiple access (packet networks), example:ALOHA: Station send a packet and waits for acknowledgement (AC) for the maximum time of round trip delay. If AC not received (collision), send again!

MultiplexingFDMA and TDMA multiplexing

Data Communication, Introduction 19

The unmodulated sinusoidal wave is parameterized by constant amplitude, frequency and phase

In unmodulated sinusoidal all

Unmodulated and Modulated Sinusoidals

[ ]( ) co (s( )) cx t A t t tω φ= +Amplitude modulation (AM)...,Amplitude Shift Keying (ASK)...

Frequency modulation (FM),Frequency/Phase Shift Keying (FSK,PSK)...

Carrier-term

some digital carriers [5]unmodulated sinusoidal

Data Communication, Introduction 20

Baseband and Carrier Wave (CW) Systems

Figures show baseband message transfer by linear (AM) and exponential modulation (FM)In linear modulation, transmission bandwidth is always below or equal to

cf

w

Linear modulation(AM...)

2bw w=Exponential modulation(FM...)

2bw w>>

Baseband spectra

f

f

f

6

Data Communication, Introduction 21

Which Modulation Method to Apply?Modulation is done to enable the usage of medium for transmission. Thus the modulation method is selected based on

Message to be transmitted (source) asvoice/video (analog source)data (digital source, machine-to-machine communications)traffic statistics: continuous / bursty traffic

Allowed delayMedium that is to be usedNetworking type as

cellular wireless networks (GSM)RF-LANs (802.11b Wi-Fi, HiperLAN /2) wire-line local area networks (Ethernet LANs) public switched telephone network (PSTN)C

hann

el

dete

rmin

es

mod

ulat

ion

met

hod

Data Communication, Introduction 22

CodingChannel coding is done ...

For detection and/or correction of errorsproduced by the channel (as block and convolutional coding) by

noiseinterferencedistortion

linearnonlinear

To alleviate synchronization problems (as Manchester coding)To alleviate detection problems (as differential coding)To enable secrecy and security (as scrambling or ciphering)

Channel coding principles:ARQ (Automatic Repeat Request) as go-back-N ARQFEC (Forward Error Correction) as block & convolutional coding

Data Communication, Introduction 23

Coding

Coding is classified to two flavorssource coding: makes transmitted bits equal probable - maximizes channel capacitychannel coding: protects message & adapts it to channel

Channel coding means adding extra bits for message for error detection and/or correction

Data Communication, Introduction 24

SummaryTelecommunication systems divided into

transmitters, channels, receivers

Understanding of source statistics is important

Fixed multiple access for bulk dataStatistical multiplexing for demanding sources and networks

Channels can be linear or non-linear. Non-linear channels generally more demanding due to introduced extra frequency components

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Data Communication, Introduction 25

Summary, Cont

Coding is used to protect message in channels (channel coding) and to compress source information (source coding)Modulation is used to carry messages in carrier wave systems - Selection of modulation method affects

reception sensitivity transmission bandwidthapplicability in networking applications