Digital Communication Course Overview

MATRUSRI ENGINEERING COLLEGE
DEPARTMENT OF ELECTRONICS COMMUNICATION
AND ENGINEERING
SUBJECT NAME: DIGITAL COMMUNICATION(PC601EC)-VI SEM
FACULTY NAME: Mr.A.ABHISHEK Reddy,Asst.Prof.
MATRUSRI
ENGINEERING COLLEGE

DIGITAL COMMUNICATION
COURSE OBJECTIVES:
1. Familiarize the students with elements of digital communication system and
waveform coding techniques like PCM, DPCM, DM and ADM.
2. Introduce the concepts of information theory and source coding
3. Familiarize the students with channel coding techniques such as LBC, BCC and
convolution codes
4. Introduce the concepts of baseband digital data transmission and analyze the
error performance of different digital carrier modulation schemes like ASK, FSK,
PSK etc.
5. Familiarize the students with the concepts of spread spectrum communication
with emphasis on DSSS and FHSS.
COURSE OUTCOMES:
CO1: Classify the different types of digital modulation techniques PCM, DPCM, DM
and ADM and compare their performance by SNR.
CO2: Illustrate the classification of channels and Source coding methods.
CO3:Distinguish different types of Error control codes along with their
encoding/decoding algorithms.
CO4: Examine the Performance of different Digital Carrier Modulation schemes of
Coherent and Non-coherent type based on Probability of error.
CO5:Generation of PN sequence using Spread Spectrum and characterize the
Acquisition Schemes for Receivers to track the signals.
MATRUSRI
ENGINEERING COLLEGE

UNIT I- ELEMENTS OF DIGITAL COMMUNICATION SYSTEM:
Check with autonomous comparison of Digital and Analog
communication systems, analog to digital conversion, quantization and
encoding techniques, PCM. Companding in PCM systems - u law and a
law, applications of PCM: introduction to linear prediction theory.
Modulation and demodulation of DPCM, DM and ADM. Comparison of
PCM, DPCM, DM and ADM. SNRQ of PCM and DM.
UNIT-I
OUTCOMES:
Familiarize the students with elements of digital communication system
and waveform coding techniques like PCM, DPCM, DM and ADM.
MATRUSRI
ENGINEERING COLLEGE

TEXT BOOKS /REFERENCES
TEXT BOOKS:
1. Simon Haykin, “Communication systems” 4/e, Wiley India 2011
2. Sam Shanmugam K, “Digital and Analog Communication systems”,
Wiley 1979.
3. B.P.Lathi, “Modern digital and analog communication systems” 3/e,
OxfordUniversityPress. 1998.
4. Leon W.Couch II., Digital and Analog Communication Systems, 6th Edn,
Pearson Education inc., New Delhi, 2001.
5. R.E.Zimer&R.L.Peterson : Introduction to Digital Communication,
PHI, 2001.
REFERENCES:
1. P. Ramakrishna Rao, “Digital Communication”, TMH, 2011.
2. Dr. Sanjay Sharma, “Digital and Analog Communication”, Mc Graw
Hill Publication, 2009.
3. Bernard Sklar “Digital Communications – Fundamentals and
Applications” / 2nd Edition, Prentice Hall.
4. John G. Proakis” Digital Communications” Fourth Edition (textbook)
McGraw Hill.
MATRUSRI
ENGINEERING COLLEGE

LESSON PLAN:
UNIT I- : Elements of Digital Communication System
MATRUSRI
ENGINEERING COLLEGE
S. No. Topic(S)
No.
of Hrs
Relevant
COs
Text Book/
Reference
Book
1. Check with autonomous Comparison of Digital and
Analog Communication Systems
01 CO1 T1,T2,T5,
R1,R2,R4
2. Analog to Digital Conversion 01 CO1 T1,T2,T5,
R1,R2,R4
3. Quantization, PCM 02 CO1 T1,T2,T5,
R1,R2,R4
4. Encoding techniques, SNRQ of PCM 02 CO1 T1,T2,T5,
R1,R2,R4
5. Companding in PCM systems - u law and a law,
Applications of PCM
01 CO1 T1,T2,T5,
R1,R2,R4
6. Introduction to Linear Prediction Theory 01 CO1 T1,T2,T5,
R1,R2,R4
7. Modulation and demodulation of DPCM 01 CO1 T1,T2,T5,
R1,R2,R4
8. Modulation and demodulation of DM,SNRQ 02 CO1 T1,T2,T5,
R1,R2,R4
9 Modulation and demodulation of ADM, Comparison of
PCM, DPCM, DM and ADM
01 CO1 T1,T2,T5,
R1,R2,R4
Total 12

CONTENTS:
-ELEMENTS OF DIGITAL COMMUNICATION
- COMPARISON OF DIGITAL WITH ANALOG SYSTEMS.
OUTCOMES:
Distinguish between analog and digital systems.
MODULE-I
MATRUSRI
ENGINEERING COLLEGE

THE WORD DIGITAL COMES FROM THE LATIN WORD DIGIT AND DIGITUS (THE
LATIN WORD FOR FINGER), AS FINGERS.
WHAT IS DIGITAL COMMUNICATION?
DIGITAL COMMUNICATION IS A MODE OF COMMUNICATION WHERE THE
INFORMATION OR THE THOUGHT IS ENCODED DIGITALLY AS DISCRETE SIGNALS
AND ELECTRONICALLY TRANSFERRED TO THE RECIPIENTS.
Digital communication covers a broad area of communications
techniques including:
• Digital transmission is the transmission of digital pulses between two or more
points in a communication system.
• Digital radio is the transmitted of digital modulated analog carriers between two
or more points in a communication system.
Introduction
MATRUSRI
ENGINEERING COLLEGE

FIRST COMMUNICATION –DIGITAL IN NATURE BY SAMUEL MORSE IN 1837.
MATRUSRI
ENGINEERING COLLEGE

Example of Digital Communication:
Manager wanted to meet all his team members at the Conference room
to discuss their key responsibility areas and areas of expertise. He didn’t
have the time to go to their workstations and invite them individually.
Instead he opted an easier and cheaper mode to communicate his idea.
He sent an email marking a cc to all the participants, inviting them for
the meeting. This is an example of Digital communication where the
information was sent electronically.
In digital communication
Information flows in a digital form and the source is generally the
keyboard of the computer.
A single individual is capable of digital communication.
It also saves wastage of manpower and is one of the cheapest modes
of communication.
Digital communication is also a really quick way to communicate. The
information can reach the recipient within a fraction of a second.
An individual no longer has to wait to personally meet the other
individual and share his information.
MATRUSRI
ENGINEERING COLLEGE

Some examples of digital communication are
• E-mailing- Computers
• Texting- Cell Phones
• Fax
• Teleconferencing
• Video conferencing
Basic Digital Communication Nomenclature:
Textual Message: information comprised of a sequence of characters.
Binary Digit (Bit): the fundamental information unit for all digital
systems.
Symbol (mi where i=1,2,…M): for transmission of the bit stream; groups
of k bits are combined to form new symbol from a finite set of M such
symbols; M=2k.
Digital Waveform: voltage or current waveform representing a digital
symbol.
Data Rate: Symbol transmission is associated with a symbol duration T.
Data rate R=k/T [bps].
Baud Rate: number of symbols transmitted per second [baud]
MATRUSRI
ENGINEERING COLLEGE

Building blocks of Digital Communication System
MATRUSRI
ENGINEERING COLLEGE

Low
Pass
Filter
Sampler Quantizer
Channel
Encoder
Line
Encoder
Pulse
Shaping
Filters
Source
Encoder
Modulator
Multiplexer
Input
Signal
Analog/
Digital
To Channel
Detector
Receiver
Filter
De-
Modulator
From Channel
Channel
Decoder
Digital-to-Analog
Converter
De-
Multiplexer
Signal
at the
user end
Carrier
Analog Digit
al
Carrier
Recovery
Symbol
timing
Recovery
Digit
al
Analog
Twisted Pair
Co-axial Cable
Optical Fiber
Wireless
Space
Building blocks of Digital Communication System
MATRUSRI
ENGINEERING COLLEGE

ADVANTAGES:
1. COMPLEXITY
2. COST
3. ROBUSTNESS
4.STORAGE & RETRIEVAL
5. FLEXIBILITY
6. EFFECT OF NOISE AND INTERFERENCE
7. LONG-HAUL COMMUNICATION USING A NUMBER OF REPEATERS
8. SECRECY OF COMMUNICATION
DISADVANTAGES:
1. MORE BANDWIDTH THAN ANALOG SYSTEMS.
2. DIGITAL COMPONENTS GENERALLY CONSUME MORE POWER AS COMPARED TO
ANALOG COMPONENTS.
MATRUSRI
ENGINEERING COLLEGE

1. What are the major design parameters of an digital
communication systems?
2. Distinguish between baseband and bandpass digital
modulation?
3. What are the advantages of digital communication over
analog systems?
ANSWER!
MATRUSRI
ENGINEERING COLLEGE

CONTENTS:
A/D Conversion
OUTCOMES:
Illustrate the mechanism of how an analog signal is converted to digital
signal.
MODULE-II
MATRUSRI
ENGINEERING COLLEGE

Digital transmission refers to transmission of digital signals between two
or more points in a communication system. if the original signal is in
analog form then it needs to be converted to digital pulses prior to
transmission and converted back to analog signals in the receiver.
The conversion of analog signal to digital pulses is known as
WAVEFORM CODING.
The digitized signals may be in the form of binary or any other form
DIGITAL transmission of discrete level digital pulses .
A/D Conversion
MATRUSRI
ENGINEERING COLLEGE

The process of converting continuous time signals into equivalent
discrete time signals, can be termed as sampling.
A/D Conversion
MATRUSRI
ENGINEERING COLLEGE

Sampling theorem: A bandlimited signal with no spectral components
beyond , can be uniquely determined by values sampled at uniform
intervals of
The sampling rate, is called Nyquist rate.
Sampling
MATRUSRI
ENGINEERING COLLEGE

Sampling
MATRUSRI
ENGINEERING COLLEGE

Def: It is the process of assigning to each one of the sample values of the
message signal, a discrete value from a prescribed set of finite number of
such discrete values called ‘quantum value’.
The total dynamic range of the analog signal
is divided into equal number of finite number
of levels or segments.
We round off a sample value falling within
a particular segment to the value represented
by the prescribed level passing through the
middle of the level.
Quantization
MATRUSRI
ENGINEERING COLLEGE

STEP SIZE
Q is called quantum levels , n –number of bits.
Quantization
MATRUSRI
ENGINEERING COLLEGE
max min
( ) 2
p p p
V V V
V V
Q Q Q
 

   
2n
Q 
2
2
p
n
V
 

When the quantization levels are uniformly distributed over the full
amplitude range of the input signal, the quantizer is called an uniform or
linear quantizer.
UNIFORM QUANTIZATION
MATRUSRI
ENGINEERING COLLEGE
a) Mid tread Type b) Midrise Type

When the quantization levels are not uniformly distributed over the full
amplitude range of the input signal, the quantizer is called an non-uniform
quantization.
A non-uniform quantization practically
gives a SNR ratio that remains essentially
constant for wide r range of input voltage levels.
A non-uniform quantizer is called
Robust Quantizer
COMPANDING
The non-uniform quantization is practically achieved through a process called
Companding.
“The process of compressing message signals like speech at the transmitter and
expanding them at receiver is called Companding”
NON-UNIFORM QUANTIZATION
MATRUSRI
ENGINEERING COLLEGE

Compression of the input samples is accomplished according to a specific law
governing the relationship between amplitudes of the input and output samples.
μ-law Companding: in North America and japan , μ-law Companding is
used.
When μ = 0, it corresponds
to uniform quantization.
8-bit PCM code and μ=255,
the output SNR
MATRUSRI
ENGINEERING COLLEGE
 
max
max
ln 1
sgn
ln 1
x
x
y y x


 
 

 
 
 
 


 
 
2
2
3
ln(1 )
o
Q
SNR



1 for x 0
sgn
1 for x<0
x
 

 



A-law Companding : European countries and India prefer A-law
companding to approximate true logarithmic companding.
A = 1 corresponds to uniform quantization
The standard value of A used in digital telephony is A=87.6
MATRUSRI
ENGINEERING COLLEGE
max
max
max
max
max
max
1
sgn 0
1 lnA
1 ln
1
sgn 1
1 lnA
x
A
x x
y x
x A
y
x
A
x x
y x
x
A
  
 
  
 
 
 
  
 
 
 
 
   
 
  
 
  
 

ENCODING
MATRUSRI
ENGINEERING COLLEGE

ENCODING-UNIPOLAR
MATRUSRI
ENGINEERING COLLEGE

ENCODING-POLAR
MATRUSRI
ENGINEERING COLLEGE

1. What is the need of non-uniform quantization?
2. What happens when the analog signal is passed through
compander?
3. Why there is always a defined upper limit to the analog
information signal frequency that can be transmitted in
digital communication system?
4. Differentiate between mid-tread and mid-rise types of
uniform quantizers. Which one is preferred and why?
5. Represent the binary data 1 0 1 1 0 0 0 1 using the following
line coding techniques:
(i) Unipolar NRZ
(ii) Bipolar RZ
(iii) BP-RZ-AMI
Answer!
MATRUSRI
ENGINEERING COLLEGE

CONTENTS:
PCM
APPLICATION OF PCM
OUTCOMES:
Understand the process of PCM and its application.
MODULE-III
MATRUSRI
ENGINEERING COLLEGE

PULSE CODE MODULATION (PCM) IS A SPECIAL FORM OF A/D
CONVERSION. IT CONSISTS OF SAMPLING, QUANTIZING, AND ENCODING
STEPS. IT IS WIDELY POPULAR BECAUSE:
- USED FOR LONG TIME IN TELEPHONE SYSTEMS
- INEXPENSIVE ELECTRONICS EXISTS
- ERRORS CAN BE CORRECTED DURING LONG HAUL TRANSMISSION
- CAN USE TIME DIVISION MULTIPLEXING
NOTE: PCM IS NOT A MODULATION TECHNIQUIE , IT IS THE NAME GIVEN
TO CLASS OF BASEBAND SIGNALS OBTAINED FROM THE QUANTIZED PAM
SIGNALS BY ENCODING EACH QUANTIZED SAMPLE INTO A DIGITAL
WORD.
PULSE CODE MODULATION
MATRUSRI
ENGINEERING COLLEGE

PCM TRANSMISTTER & RECEIVER
PULSE CODE MODULATION
MATRUSRI
ENGINEERING COLLEGE

Process :
MATRUSRI
ENGINEERING COLLEGE

MATRUSRI
ENGINEERING COLLEGE
Figure shows an analog signal x(t) limited in its excursions to the
range -4 to +4V. The step size between quantization levels has been
set at 1V. Thus, eight quantization levels are employed. These are
located at -3.5, -2.5,……+3.5V. Assign the code number 0 to the level
at -3.5V, code number 1 to the level at -2.5V, and so on, until the
level at 3.5V, which is assigned the code number 7.

Regenerative Repeater circuit:
MATRUSRI
ENGINEERING COLLEGE

Regenerative Repeater Process :
MATRUSRI
ENGINEERING COLLEGE

Bandwidth of PCM signal:
MATRUSRI
ENGINEERING COLLEGE

When a large number of PCM signals are to be transmitted over a
common channel, multiplexing of these PCM signals are required
PCM-TDM SYSTEM: T1 CARRIER SYSTEM (APPLICATION)
MATRUSRI
ENGINEERING COLLEGE

The frame structure of T-1 carrier system is shown . Instead of using a
separate channel for signaling purposes, the LSB slots normally used for
voice information, are themselves used once in six frames, for the
purpose of signaling referred to as ‘channel associated signaling’.
Frame synchronization: For proper synchronization one frame bit is
included at the beginning of every frame. The pattern formed by 12 such
frame bits occurring in 12 successive frames gives a 12-bit code called the
frame sync word.
MATRUSRI
ENGINEERING COLLEGE

MATRUSRI
ENGINEERING COLLEGE
 
1
l n 1 2
b
m
sampling period
T
tota umber of bits nN f
 

 
1 2 m
nN f

2 m
BW nNf


1. What is the objective of including equalizer circuit in PCM
signal regenerators?
2. An audio signal is required to transmit with sampling rate of
40kHz and 14bits/sample using linear PCM. Calculate
minimum transmission data rate?
3. What are the merits and de-merits of PCM systems?
4. Twenty four voice signals are sampled uniformly and TDM-ed.
The highest frequency component is 3.4KHz.
(i)What is the minimum channel bandwidth required , if signals are pulse
amplitude modulated using Nyquist rate.
(ii)If the signals are Pulse code modulated with 8-bit encoder, what would be
the sampling rate? The bit rate is given as 1.5 Mbits/sec.
ANSWER!
MATRUSRI
ENGINEERING COLLEGE

CONTENTS:
-LINEAR PREDICTIVE CODING
-DPCM
OUTCOMES:
Use the knowledge of prediction theory to understand the design
process of DPCM.
MODULE-IV
MATRUSRI
ENGINEERING COLLEGE

When adjacent samples of a message have good correlation, as in the
case of audio and video message samples encoded using PCM, it is
possible to predict the value of a future sample by making use of the
present and some previous samples.
-P PREVIOUS SAMPLES.
- WEIGHTS
A LINEAR COMBINATION OF THE PREVIOUS SAMPLE VALUES IS USED FOR OBTAINING THE
PREDICTED VALUE, THE PREDICTION PROCESS IS CALLED ‘LINEAR PREDICTION’.
LINEAR PREDECTIVE THEORY
MATRUSRI
ENGINEERING COLLEGE
1 2
( ) ( 1 ) ( 2 ) ( )
s s s p s
x nT h x n T h x n T h x n pT
      
( 1 ), ( 2 ), ( )
s s s
x n T x n T x n pT
  
1 2
, , p
h h h

(A) P-th order filter transmitter
THE PREDICTOR WEIGHTS OR COEFFICIENTS
MUST BE CHOSEN THAT THE
‘PREDICTION ERROR’ IS MINIMIZED
(B) P-th order filter Receiver
LINEAR PREDECTIVE THEORY
MATRUSRI
ENGINEERING COLLEGE

Differential PCM
MATRUSRI
ENGINEERING COLLEGE

DPCM
MATRUSRI
ENGINEERING COLLEGE

DPCM TRANSMITTER
DPCM RECEIVER
DPCM
MATRUSRI
ENGINEERING COLLEGE

 The principle of DPCM is “over sampling “ and
“Prediction”
DPCM
MATRUSRI
ENGINEERING COLLEGE

irrespective pf properties of prediction filter, the quantized signal at the
prediction filter i/p differs by original i/p by quantizing error.
DPCM
MATRUSRI
ENGINEERING COLLEGE

PROCESSING GAIN:
with the prediction order of 5, DPCM gives 11dB improvement in SNR
compared to PCM and with sampling rate of 8KHZ, DPCM gives saving
bitrate of 1 or 2 bits/sample i.e 8 to 16 kbps compared to PCM
DPCM
MATRUSRI
ENGINEERING COLLEGE

1. What are the benefits of reducing the amount of redundant
information between adjacent sample?
2. What are the advantages of using a predictor in DPCM?
3. What is the conceptual difference between the conceptual
PCM and DPCM?
4. What is meant by oversampling?
ANSWER!
MATRUSRI
ENGINEERING COLLEGE

CONTENTS:
-DELTA MODULATION
-ADAPTIVE DM
-COMPARISION OF WAVEFORM CODING’S
OUTCOMES:
Understand necesscesity of DM and overcome its drawbacks and also
Compare various waveform coding techniques
MODULE-V
MATRUSRI
ENGINEERING COLLEGE

The type of modulation, where the sampling rate is much higher and in
which the step size after quantization is of a smaller value Δ, such a
modulation is termed as delta modulation.
If this sampling interval in differential PCM is reduced considerably, the
sample to-sample amplitude difference is very small, as if the difference
is 1-bit quantization, then the step-size will be very small i.E., Δ delta.
Delta modulation is a simplified form of DPCM technique, also viewed
as 1-bit DPCM scheme. As the sampling interval is reduced, the signal
correlation will be higher.
DELTA MODULATION
MATRUSRI
ENGINEERING COLLEGE

MATRUSRI
ENGINEERING COLLEGE


(2) GRANULAR NOISE.
The granular noise occurs when the step size is too large relative to the local slope
characteristics of the input wave form x(t), thereby causing the staircase
approximation u(t) to hunt around a relatively flat segment of the input
waveform; the granular noise is analogous to quantization noise in a PCM system.
Advantages of DM Over DPCM
1-bit quantizer
Very easy design of the modulator and the demodulator
However, there exists some noise in DM.
Slope Over load distortion (when Δ is small)
Granular noise (when Δ is large)
MATRUSRI
ENGINEERING COLLEGE

ADAPTIVE DELTA MODULATION
MATRUSRI
ENGINEERING COLLEGE

NUMBER OF SUCCESSIVE 1’S OR 0’S STEP SIZE
1 
2 
3 2
4 4
. .
MATRUSRI
ENGINEERING COLLEGE

COMPARISION OF PCM,DPCM,DM,ADM
MATRUSRI
ENGINEERING COLLEGE

1. How is DM different from pcm and DPCM?
2. What is the common algorithm followed in ADM?
3. Why is it necessary to use higher sampling rate for DM than
that for pcm?
4. Indicate the possible situations in which the use of DM
scheme is recommended?
5. What are the distortions encountered in DM and how to
overcome?
ANSWER!
MATRUSRI
ENGINEERING COLLEGE

CONTENTS:
- QUANTIZATION ERROR
- SNR OF PCM
-BANDWIDTH-POWER TRADEOFF
-SNR OF DM
OUTCOMES:
Derive the SNR expressions for PCM and DM and understand tradeoff
mechanisms.
MODULE-VI
MATRUSRI
ENGINEERING COLLEGE

The difference between the actual sampled values to the approximated
quantized value is called quantization error.
Maximum quantization error
should not exceed
Mean square value of the error
= avg.Power in quantization noise
QUANTIZATION NOISE
MATRUSRI
ENGINEERING COLLEGE
( ) ( )
e s q s
Q x nT x nT
 
2


2 2
e
Q
 
   
2
2 2
2
( )d
e e e e
Q Q f Q Q




  2
12
q
N

 

Let the sampled value of the signal x(t) is assumed to lie in range (-vp ,vp ),
then the step size of uniform quantizer is
assume that input x(t) is normalized , i.e Vp=1
Also if the destination signal power ‘P’ is normalized i.e P≤1 watt
FOR NORMALIZED INPUT AND POWER,
MATRUSRI
ENGINEERING COLLEGE
2
2
p
n
V
  2 2
1
2
3
n
q p
N V 
 2
2
3
[ ] 2 n
o
p
P
SNR
V
 
  
 
 
 
4.77 6.02
q dB
S n dB
N
 
  
 
 

STEP-1 : The quantization noise power
Case (i): consider n-bit binary PCM, a message signal which is uniformly
distributed between
mean-squared value of a RVX S=
SNR of PCM
MATRUSRI
ENGINEERING COLLEGE
2
12
q
N

 
max max
x and x

max
max
2
2 2 max
max
1
2 3
x
x
x
X x dx
x

 
 
 
 

2 2
max max
2 2
4
2 12 2 3
q n n
x x
N
   
  
   
 
   
max max
2 2
,
2n
x x
where
Q
  
6
q dB
S n dB
N
 
 
 
 

CASE (II): Let us assume that a message signal is of sinusoidal nature,
signal power, s =
CASE (III): Suppose that the baseband signal x(t) is modelled as the sample function of a
Gaussian random Process of zero mean and that the amplitude range of x(t) at the quantizer
input extends from -4Arms to 4Arms.
Avg.signal power, S=
It is observed that a 1-bit increase per sample increases SNR by 6db. In general as
number of bits per sample increases from n to n+k, the SNR increases by
“6ndb/6kdb”. Hence it is called “6ndb rule”.
MATRUSRI
ENGINEERING COLLEGE
( ) cos2
m m
x t A f t

 max min m
2
V V A
Q Q

  
2
m
2
3 2
q n
A
N
 

2
m
2
A
 
1.76 6.02
q dB
S n dB
N
 
 
 
 
2
rms
A
8
2
rms
n
A
 
 
6 7.2
q dB
S n dB
N
 
  
 
 

As n increases, SNR increases rapidly (exponentially). At the same time, the
required transmission bandwidth BT also increases. Without increasing the
transmitter power we can just increase n and get an improved destination SNR,
there is a power- bandwidth trade-off possible in PCM.
For radio broadcasting applications, SNR required is 60dB for a PCM systems but
with b=6, the same SNR is achieved by FM but for PCM b needs to be increased
beyond 8 to achieve 60dB SNR. Hence, in broadcasting applications FM is
preferred over PCM.
Bandwidth-power tradeoff PCM
MATRUSRI
ENGINEERING COLLEGE
 
2
2
l
SNR c

 
2
2
2
( )
3 ( )
,
3
( )
ln 1
p
m t
uncompanded
m
where c
companded




 

 
 
 

   
2
2
2 2
T
B
b
B
SNR c c
  , exp
T
B
b called bandwidth ansion factor
B


Assume that no slope overload distortion
Consider a sinusoidal message signal
, avg.signal power
with in a filter bandwidth W
SNR of DM
MATRUSRI
ENGINEERING COLLEGE
max
( )
s
d
m t
T dt

 ( ) sin 2 m
m t A f t


2
s
m
f
A
f



2
2
A
S 
2
2 2
2 2
2
2 8
s
m s
m
f
f f
S
f


 

 

 
  
3
3
q
N

 
3 3
2
3 3
8 80
s s
q m m
DM
f f
S
N f f

     
 
     
 
   
 
3
2 2
3
8
s
q m
DM
f
S
N f W

 
 
 
 
 

1. Why PCM is not used for radio broad casting applications?
2. Consider an analog input signal to PCM whose bandlimited to
4KHz and varies from -3.8 V to +3.8 V, with average power of
30mW. The required SNR is given as 20dB.Assumimg uniform
quantization, determine number of bits required per sample.
3. Compute SNR for PCM and DM systems for 8-bits . Comment
on result.
4. An audio signal comprising of single term s(t)=3cos(2π1000t)
is quantized using DM. Determine SNR of DM with sampling
frequency 8-times the Nyquist rate.
ANSWER!
MATRUSRI
ENGINEERING COLLEGE

Digital Communication Course Overview

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Digital Communication Course Overview

Similar to Digital Communication Course Overview (20)

More from Matrusri Engineering College

More from Matrusri Engineering College (6)

Recently uploaded

Recently uploaded (20)

Digital Communication Course Overview