Advance Communication System Lectures Part 7

8/2/2019 Advance Communication System Lectures Part 7

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29 April 20121

Digital Communications


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The RF spectrum must be shared, yet every daythere are more users for that spectrum asdemand for communications services increases.

Digital modulation schemes have greater capacityto convey large amounts of information than

analog modulation schemes

29 April 20122

4.0 Introduction


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29 April 20123


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4.1 Digital Modulation Advantages :

Immunity to noise (due to its finite process)

Easy storage and processing:

Regeneration

Easy to measure

Enables encryption

Data from several sources can be integrated and transmittedusing the same digital communication system

Error correction detection can be utilized

Disadvantages :

Requires a bigger bandwidth

Analog signal need to be changed to digital first

Not compatible to analog system

Need synchronization

MP, DSP, RAM, ROM, Computer


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Performance Metrics

Analog Communication Systems

Metric is fidelity: want

SNR typically used as performance metric

Digital Communication Systems

Metrics are data rate (R bps) and probability of bit error

Symbols already known at the receiver

Without noise/distortion/sync. problem, we will nevermake bit errors

( ) ( )m t m t

( )bP p b b


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Formatting


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4.2 TRANSMISSION METHOD FOR ANALOG &

DIGITAL SIGNALS

Analog

input

Analog channel

Baseband

Analog

output

Analog

inputModulator De

modulator

Analog

output

Analog

channel

Digital

input

encoder decoderDigital

channel

Digital

output

Digital

inputModem Modem

Analog

channel

Digital

output

Analoginput ADC &encoderDecoder& DAC

Analogoutput

Digitalchannel

Analog

input

Analog

outputAnalog

channel

ADC &

encoderModem

ADC &

decoderModem


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Design

To maximize transmission rate, R To maximize system utilization, U

To minimize bit error rate, Pe To minimize required systems bandwidth, W

To minimize system complexity, Cx To minimize required power, Eb/No


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Introduction

Communication systems are used to transport information

bearing signal from source to destination via a channel.

The information bearing signal can be:

(b) Digital : digital communication system

(a) Analog : analog communication system;

Digital communication is expanding because:

(a) The impact of the computer;

(b) flexibility and compatibility;

(c) possible to improve reliability;

(d) integrated solid-state electronic technology

(d) availability of wideband channels


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Introduction

Information Source

(a) Generates the message(s) . Examples are voice,television picture, computer key board, etc..

(b) If the message is not electrical, a transducer is used

to convert it into an electrical signal.(c) Source can be analog or digital.(d) Source can have memory or memoryless.


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Source encoder/decoder

Introduction

(a) The source encoder maps the signal produced by thesource into a digital form (for both analog and digital).

(b) The mapping is done so as to remove redundancy inthe output signal and also to represent the originalsignal as efficiency as possible (using as few bits aspossible).

(c) The mapping must be such that an inverse operation(source decoding) can be easily done.

(d) Primary objective of source encoding/decoding is toreduce bandwidth, while maintaining adequate signalfidelity.


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Introduction

Channel encoder/decoder

(a) Maps the input digital signal into another digitalsignal in such a way that the noise will beminimized.

(b) Channel coding thus provides for reliable

communication over a noisy channel.(c) Redundancy is introduced at the channel encoder

and exploited at the decoder to correct errors.Modulator

(a) Modulation provides for efficient transmission of the

signal over channel.(b) Most modulation schemes impress the information

on either the amplitude, phase or frequency of asinusoid.

(c) Modulation and demodulation is done such thatBit error rate is minimized and Bandwidth is


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Introduction

Channel

Characteristics of channel are(a) Bandwidth(b) Power

(c) Amplitude and phase variations(d) Linearity, etc..

Typical channel models are Additive White Gaussian Channel

and Rayleigh fading channel;


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Bandwidth / Representation

29 April 201215

2000 bps

B=500 Hz

B=1000 Hz

B=1700 Hz

B=4000 Hz

Increasing bandwidth

improves the

representation of the data

signal.

500Hz too low to

reproduce the signal.

Want to maximize the

capacity of the availablebandwidth.


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Bandwidth and information capacity

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The information capacity of a communication systemrepresents the number of independent symbols that can be

carried through the system in a given unit of time.

By using Shannon limit for information capacity, therelationship between Information capacity to the signalbandwidth and SNR is defined below:

I = information capacity (bit/second)

B = system bandwidth (Hertz)

S/N =signal-to-noise power ratio (dimensionless)

2 10log 1 3.32 log 1

S SI B B

N N


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Summary of Line Codes


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Bandpass Modulation and Demodulation

Bandpass Modulation is the process by which some characteristicsof a sinusoidal waveform is varied according to the message signal.

Modulationshifts the spectrum of a baseband signal to some highfrequency.

Demodulator/Decoder baseband waveform recovery


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Digital Bandpass Modulation TechniquesThree ways of representing bandpass signal:

(1) Magnitude and Phase (M & P)

Any bandpass signal can be represented as:

A(t) 0is real valued signal representing the magnitude

(t) is the genarlized angle

(t) is the phase

The representation is easy to interpret physically, but often is notmathematically convenient

In this form, the modulated signal can represent information throughchanging three parameters of the signal namely:

Amplitude A(t) : as inAmplitude Shift Keying (ASK)

Phase (t) : as inPhase Shift Keying (PSK)

Frequency d(t)/ dt : as in Frequency Shift Keying (FSK)

)](cos[)(cos[)()( 0 tttAttAts


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Digital Modulation Schemes Basic Digital Modulation Schemes:

Amplitude Shift Keying (ASK) Frequency Shift Keying (FSK)

Phase Shift Keying (PSK)

Amplitude Phase Keying (APK)

For Binary signals (M = 2), we have

Binary Amplitude Shift Keying (BASK)

Binary Phase Shift Keying (BPSK)

Binary Frequency Shift Keying (BFSK)

For M > 2, many variations of the above techniques exit usuallyclassified as M-ary Modulation/detection


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Figure4.5: digital modulations, (a) PSK (b) FSK (c) ASK (d) ASK/PSK (APK)


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Channel coding (1)


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Introduction

Channel coding is also called error control coding or errorcorrecting coding

Purpose of Error Control Coding

(1) In data communications, coding is used for controllingtransmission errors induced by channel noise or other

impairments, such as fading and interferences, so that error-

free communication can be achieved.

(2) In data storage systems, coding is used for controllingstorage errors (during retrieval) caused by storage medium

defects, dust particles and radiation so that error-free

storage can be achieved.


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Coding PrincipleCoding is achieved by adding properly designed redundant

digits (bits) to each message. These redundant digits (bits)

are used for detecting and/or correcting transmission (or

storage) errors.

Type of Coding

Block Coding : Block codes process the information on a

block-by-block basis, treating each block of information bitsindependently of others.

A message of k digits is mapped into a structure sequence

of n digits, called a codeword.

Introduction


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IntroductionType of Coding

Convolutional Coding:

An information sequence is divided into (short) blocks of

k-digits each. Each k-digit message is encoded into an n-digit

coded block. The n-digit coded block depends not only onthe corresponding k-digit message block but also on m

previous message blocks. That is, the encoder has memory

of order m .

1m

The encoder has k inputs and n outputs.

An information is encoded into a coded sequence. The

collection of all possible code sequences is called an

convolutional code.

, ,n k m


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IntroductionType of Errors

Random errors caused by:

Thermal and shot noise in transmitter and receiver

Thermal noise in channel.

Radiation picked by antenna.

Burst errors (More than one symbol or

bit is affected) caused by:

Lightning and switching transients.

Fast fades.


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Type of Channels

Introduction

Random error channels:

Deep space channel, satellite channels, light of

sight transmission channel, etc.

Burst error channels:

Radio links, terrestrial microwave links, wire and

cable transmission channels, etc.


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Decoding

Introduction

Two types of decoding: Hard-decision decoding and

soft-decision decoding.

Hard-decision decoding: When binary coding is used, the modulator

has only binary inputs. If binary demodulator output quantization is

used, the decoder has only binary inputs. In this case, thedemodulator is said to make hard decisions. Decoding based on hard

decision made by the demodulator is called hard decision decoding.

Soft-decision decoding: If the output of the demodulator consists of

more than one quantization level or is left unquantized, the

demodulator is said to make soft decisions. Decoding based on soft

decision made by the demodulator is called soft-decision decoding.


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Optimum Decoding

Introduction

Suppose the codeword corresponding to a certain

message is transmitted. Let be the corresponding

output of the demodulator.

c

mr

An optimum decoding rule is the one that minimizesthe probability of decoding error. That is, is

minimized. Or equivalently, maximizing .

P c c r P c c r

Introd ction Channel Coding


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Principle: Add redundancy to minimize error rate

01 0 1111 0

Transmitter Receiver1 1 0 1

00 0 1111 1

Source

Channelencoder

Sink

ChanneldecoderChannel

Introduction: Channel Coding

1 1 0 1


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Different channel types 00

1 1

1-p

1-p

pp

-1 +10

Binary Symmetric Channel

Additive White Gaussian NoiseChannel

MIMO Channel T R

Convolutional Codes


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Convolutional Codes

Coding by convolution

Encoder is aFinite-State-Machine

z-1 z-1Input

Output 1

Output 2

00

01

10

11

(m1m2)

Coding a bit sequence= Choosing one path in trellis graph

Decoding: Find the most likely path


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Linear Block Codes

Formed by the linear combination of data andparity bits

Also known as (n,k) codes

Where n is the number of data bits and k is

length of codeword

The information rate is depicted as k/n

For example if data is 10 01 11

The n for (2,6) code could be 101100 010011 110101 for the given data bits

where first two bits are date bits and rest of 4 bitsare redundant bits

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Turbo Codes


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Turbo Codes

Turbo Decoder

P

C 2

C 1

P

D 2

D 1 P

P-1

Turbo Encoder

U

One Decoder (D) for every Encoder (C)

Iterative Decoding: D1 D2 D1 D2 D1 Improved Bit-Error Rate Performance


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Coding advantages

Pn

Eb/N0 dB

10-8

10-3

8 19

Coding gain


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Coding disadvantages

More bandwidth due to redundant Processing Delay

Design Complexity

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Advance Communication System Lectures Part 7