Digital Communications Prof. Sandeep J. Rajput Assistant Professor E & C Engg. Dept. HCET,Sidhpur

Digital Communications

Prof. Sandeep J. RajputAssistant ProfessorE & C Engg. Dept.HCET,Sidhpur

Overview

• Introduction– Communication systems– Digital communication system– Importance of Digital transmission

• Basic Concepts in Signals– Sampling– Quantization– Coding

2Digital Communication

What is Communication?

• Communication is transferring data reliably from one point to another– Data could be: voice, video, codes etc…

• It is important to receive the same information that was sent from the transmitter.

• Communication system– A system that allows transfer of information

reliably


Communication Systems

Communication System

TransmitterSource“Sending Point”

ReceiverSink“Receiving Point”


Information Source

Transmitter Channel Receiver Information Sink

Block Diagram of a typical communication system




• Information Source– The source of data

• Data could be: human voice, data storage device CD, video etc..

– Data types:• Discrete: Finite set of outcomes “Digital”• Continuous : Infinite set of outcomes “Analog”

• Transmitter– Converts the source data into a suitable form for

transmission through signal processing – Data form depends on the channel



• Channel:– The physical medium used to send the signal– The medium where the signal propagates till

arriving to the receiver– Physical Mediums (Channels):

• Wired : twisted pairs, coaxial cable, fiber optics• Wireless: Air, vacuum and water

– Each physical channel has a certain limited range of frequencies ,( fmin fmax ), that is called the channel bandwidth

– Physical channels have another important limitation which is the NOISE



– Noise is undesired random signal that corrupts the original signal and degrades it

– Noise sources:• Electronic equipments in the communication system• Thermal noise • Atmospheric electromagnetic noise (Interference with another

signals that are being transmitted at the same channel)– Another Limitation of noise is the attenuation

• Weakens the signal strength as it travels over the transmission medium

• Attenuation increases as frequency increases– One Last important limitation is the delay distortion

• Mainly in the wired transmission• Delays the transmitted signals Violates the reliability of the

communication system 8Digital Communication


• Receiver– Extracting the message/code in the received signal

Example :

– Speech signal at transmitter is converted into electromagnetic waves to travel over the channel

– Once the electromagnetic waves are received properly, the receiver converts it back to a speech form

• Information Sink– The final stage– The user


Effect of noise on transmitted signal


Digital Communication System

Information Source

A / D Converter

Source Encoder

ChannelEncoder

Modulator

Information Sink

D / AConverter

SourceDecoder

ChannelDecoder Demodulator

Channel



• Information source– Analog Data: Microphone, speech signal, image, video etc… – Discrete (Digital) Data: keyboard, binary numbers, hex

numbers, etc…

• Analog to Digital Converter (A/D)– Sampling:

• Converting continuous time signal to a digital signal– Quantization:

• Converting the amplitude of the analog signal to a digital value

– Coding:• Assigning a binary code to each finite amplitude in the

analog signal12Digital Communication


• Source encoder– Represent the transmitted data more efficiently and

remove redundant information• How? “write Vs. rite”• Speech signals frequency and human ear “20 kHz”

– Two types of encoding:– Lossless data compression (encoding)

• Data can be recovered without any missing information

– Lossy data compression (encoding)• Smaller size of data• Data removed in encoding can not be recovered again



• Channel encoder:– To control the noise and to detect and correct the errors

that can occur in the transmitted data due to the noise.

• Modulator:– Represent the data in a form to make it compatible with

the channel• Carrier signal “high frequency signal”

• Demodulator:– Removes the carrier signal and reverse the process of the

Modulator14Digital Communication


• Channel decoder:– Detects and corrects the errors in the signal gained from

the channel

• Source decoder:– Decompresses the data into it’s original format.

• Digital to Analog Converter:– Reverses the operation of the A/D– Needs techniques and knowledge about sampling,

quantization, and coding methods.

• Information Sink– The User


Why should we use digital communication?• Ease of regeneration

– Pulses “ 0 , 1”– Easy to use repeaters

• Noise immunity– Better noise handling when using repeaters that repeats

the original signal– Easy to differentiate between the values “either 0 or 1”

• Ease of Transmission– Less errors– Faster !– Better productivity 16Digital Communication

Why should we use digital communication?

• Ease of multiplexing– Transmitting several signals simultaneously

• Use of modern technology– Less cost !

• Ease of encryption– Security and privacy guarantee– Handles most of the encryption techniques


Disadvantage !

• The major disadvantage of digital transmission is that it requires a greater transmission bandwidth or channel bandwidth to communicate the same information in digital format as compared to analog format.

• Another disadvantage of digital transmission is that digital detection requires system synchronization, whereas analog signals generally have no such requirement.


Basic Concepts in Signals

• A/D is the process of converting an analog signal to digital signal, in order to transmit it through a digital communication system.

• Electric Signals can be represented either in Time domain or frequency domain.– Time domain i.e – We can get the value of that signal at any time (t) by

substituting in the v(t) equation.

)4510002sin(2)( ttv


Time domain Vs. Frequency domain

Time Domain F

ourier/Laplace Transform

Frequency Domain

Fourier/Laplace Transform


Time domain Vs. Frequency domain

• Consider taking two types of images of a person:• Passport image• X-Ray image

• Two different domains, spatial domain “passport image” and “X-Ray domain”.

• Doctors are taking the image in the X-Ray domain to extract more information about the patient.

• Different domains helps fetching and gaining knowledge about an object. – An Object : Electric signal, human body, etc…


Time domain Vs Frequency domain

• We deal with communication system in the time domain.– Lack of information about the signal– Complex analysis

• Frequency domain gives us the ability to extract more information about the signal while simplifying the mathematical analysis.


Frequency Domain

• To study the signal in the frequency domain, we need to transfer the original signal from the time domain into the frequency domain.– Using Fourier Transform

dtetxfX ftj 2)()(

dfefXtx ftj 2)()(

Fourier TransformTime domain Frequency Domain

Inverse Fourier TransformFrequency domain Time Domain


Spectrum

• The spectrum of a signal is a plot which shows how the signal amplitude or power is distributed as a function of frequency.

f

fee

fjdtedtetxfX ftjftjftjftj

)sin(

2

1)()(

5.0

5.0

5.05.022

Time Domain Frequency Domain

Amp. Amp.

Time(s)

Frequency (Hz)


Band limited signals• A band limited signal is a signal who has a finite

spectrum. • Most of signal energy in the spectrum is contained in a

finite range of frequencies.• After that range, the signal power is almost zero or

negligible value.X(f)

+ fH- fH

Freq.

Symmetrical SignalPositive = Negative 25Digital Communication

Converting an Analog Signal to a Discrete Signal (A/D)

• Can be done through three basic steps:

1- Sampling

2- Quantization

3- Coding26Digital Communication

Sampling

• Process of converting the continuous time signal to a discrete time signal.

• Sampling is done by taking “Samples” at specific times spaced regularly.– V(t) is an analog signal

– V(nTs) is the sampled signal

• Ts = positive real number that represent the spacing of the sampling time

• n = sample number integer


Sampling

Original Analog Signal“Before Sampling”

Sampled Analog Signal“After Sampling”


Sampling

• The closer the Ts value, the closer the sampled signal resemble the original signal.

• Note that we have lost some values of the original signal, the parts between each successive samples.

• Can we recover these values? And How?• Can we go back from the discrete signal to the

original continuous signal?


Sampling Theorem

• A band limited signal having no spectral components above fmax (Hz), can be determined uniquely by values sampled at uniform intervals of Ts seconds, where

• An analog signal can be reconstructed from a sampled signal without any loss of information if and only if it is:– Band limited signal– The sampling frequency is at least twice the signal

bandwidth

Ts 1

2 fmax


Quantization

• Quantization is a process of approximating a continuous range of values, very large set of possible discrete values, by a relatively small range of values, small set of discrete values.

• Continuous range infinite set of values

• Discrete range finite set of values


Quantization

• Dynamic range of a signal– The difference between the highest to lowest value

the signal can takes.


Quantization

• In the Quantization process, the dynamic range of a signal is divided into L amplitude levels denoted by mk, where k = 1, 2, 3, .. L

• L is an integer power of 2• L = 2k

• K is the number of bits needed to represent the amplitude level.

• For example:– If we divide the dynamic range into 8 levels,

• L = 8 = 23

– We need 3 bits to represent each level.


Quantization

• Example:– Suppose we have an analog signal with the values

between [0, 10]. If we divide the signal into four levels. We have

• m1 [ 0, 2.5 ]• m2 [ 2.5, 5 ]• m3 [ 5 , 7.5]• m4 [ 7.5, 10]


Quantization

• For every level, we assign a value for the signal if it falls within the same level.

M1 = 1.25 if the signal in m1

M2 = 3.75 if the signal in m2Q [ v(t) ] =




Quantization

Original Analog Signal“Before Quantization”

Quantized Analog Signal“After Quantization” 36Digital Communication

Quantization

Original Discrete Signal“Before Quantization”

Quantized Discrete Signal“After Quantization” 37Digital Communication

Quantization

• The more quantization levels we take the smaller the error between the original and quantized signal.

• Quantization step

• The smaller the Δ the smaller the error.

Dynamic Range

No. of Quantization levels

Smax Smin

L


Coding

• Assigning a binary code to each quantization level.

• For example, if we have quantized a signal into 16 levels, the coding process is done as the following:

Step Code Step Code Step Code Step Code

0 0000 4 0100 8 1000 12 1100

1 0001 5 0101 9 1001 13 1101

2 0010 6 0110 10 1010 14 1110

3 0011 7 0111 11 1011 15 1111


Coding

• The binary codes are represented as pulses

• Pulse means 1• No pulse means 0

• After coding process, the signal is ready to be transmitted through the channel. And Therefore, completing the A/D conversion of an analog signal.


THANKS…..

Digital Communication 41

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Digital Communications Prof. Sandeep J. Rajput Assistant Professor E & C Engg. Dept. HCET,Sidhpur