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Analog Communication 10EC53

SJBIT/Dept of ECE Page 1

SYLLABUS

ANALOG COMMUNICATION

Subject Code: 10EC53

IA Marks: 25 No. of Lecture Hrs/Week: 04 Exam Hours: 03 Total no. of Lecture Hrs: 52 Exam Marks: 100

PART A

UNIT - 1

RANDOM PROCESS: Random variables: Several random variables. Statistical averages: Function of Random variables, moments, Mean, Correlation and Covariance function: Principles of autocorrelation function, cross correlation functions. Central limit theorem, Properties of Gaussian process. 7 Hours

UNIT - 2

AMPLITUDE MODULATION: Introduction, AM: Time-Domain description, Frequency Domain description. Generation of AM wave: square law modulator, switching modulator. Detection of AM waves: square law detector, envelop detector. Double side band suppressed carrier modulation (DSBSC): Time-Domain description,

Frequency-Domain representation, Generation of DSBSC waves: balanced modulator, ring modulator. Coherent detection of DSBSC modulated waves. Costas loop. 7 Hours

UNIT - 3

SINGLE SIDE-BAND MODULATION (SSB): Quadrature carrier multiplexing, Hilbert transform, properties of Hilbert transform, Pre envelope, Canonical representation of band pass signals, Single side-band modulation, Frequency-Domain description of SSB wave, Time-Domain description. Phase discrimination method for generating an SSB modulated wave, Time-Domain description. Phase discrimination method for generating an SSB modulated wave. Demodulation of SSB waves. 6 Hours

UNIT - 4

VESTIGIAL SIDE-BAND MODULATION (VSB): Frequency Domain description, Generation of VSB modulated wave, Time - Domain description, Envelop detection of VSB wave plus carrier, Comparison of amplitude modulation techniques, Frequency

translation, Frequency division multiplexing, Application: Radio broadcasting, AM radio.

6 Hours

PART B

UNIT - 5

ANGLE MODULATION (FM)-I: Basic definitions, FM, narrow band FM,wide band FM, transmission bandwidth of FM waves, generation of FM waves: indirect FM and

direct FM. 6 Hours

UNIT - 6

ANGLE MODULATION (FM)-II: Demodulation of FM waves, FM stereo multiplexing, Phase-locked loop, Nonlinear model of the phase locked loop, Linear

Analog Communication 10EC53

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model of the phase locked loop, Nonlinear effects in FM systems.

7 Hours

UNIT - 7

NOISE: Introduction, shot noise, thermal noise, white noise, Noise equivalent bandwidth, Narrow bandwidth, Noise Figure, Equivalent noise temperature, cascade connection of two-port networks. 6 Hours

UNIT - 8

NOISE IN CONTINUOUS WAVE MODULATION SYSTEMS:

Introduction, Receiver model, Noise in DSB-SC receivers, Noise in SSB receivers, Noise in AM receivers, Threshold effect, Noise in FM receivers, FM threshold effect, Pre-emphasis and De-emphasis in FM. 7 Hours

TEXT BOOKS:

1. Communication Systems, Simon Haykins, 5th Edition, John Willey, India Pvt. Ltd,

2009.

2. An Introduction to Analog and Digital Communication, Simon Haykins, John Wiley

India Pvt. Ltd., 2008

REFERENCE BOOKS:

1. Modern digital and analog Communication systems B. P. Lathi, Oxford University

Press., 4th ed, 2010,

2. Communication Systems, Harold P.E, Stern Samy and A Mahmond, Pearson Edn,

2004.

3. Communication Systems: Singh and Sapre: Analog and digital TMH 2nd , Ed 2007.

Analog Communication 10EC53

SJBIT/Dept of ECE Page 3

INDEX SHEET

SL.NO TOPIC PAGE NO.

I UNIT 1 RANDOM PROCESS 4-8

II UNIT 2 AMPLITUDE MODULATION 9-24

III UNIT 3 SINGLE SIDE-BAND

MODULATION (SSB) 25-39

IV UNIT 4 VESTIGIAL SIDE-BAND

MODULATION 40-46

V UNIT 5 ANGLE MODULATION (FM)-I 47-56

VI UNIT 6 ANGLE MODULATION (FM)-II 57-62

VII UNIT 7 NOISE: 63-67

VIII

UNIT 8 NOISE IN CONTINUOUS

WAVE MODULATION SYSTEMS:

68-73

Analog Communication 10EC53

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UNIT 1

RANDOM PROCESS: Random variables: Several random variables. Statistical averages: Function of Random variables, moments, Mean, Correlation and Covariance function: Principles of autocorrelation function, cross correlation functions. Central limit theorem, Properties of Gaussian process. 7 Hrs

TEXT BOOKS:

1. Communication Systems, Simon Haykins, 5th Edition, John Willey, India Pvt. Ltd,

2009.

2. An Introduction to Analog and Digital Communication, Simon Haykins, John

Wiley India Pvt. Ltd., 2008

REFERENCE BOOKS:

1. Modern digital and analog Communication systems B. P. Lathi, Oxford University

Press., 4th ed, 2010

2. Communication Systems, Harold P.E, Stern Samy and A Mahmond, Pearson Edn,

2004.

3. Communication Systems: Singh and Sapre: Analog and digital TMH 2nd , Ed 2007.

Analog Communication 10EC53

SJBIT/Dept of ECE Page 5

1.1. Random Process

A random process is a signal that takes on values, which are determined (at least in part) by chance. A sinusoid with amplitude that is given by a random variable is an example of a random process. A random process cannot be predicted precisely. However, a deterministic signal is completely predictable. An ergodic process is one in which time averages may be used to replace ensemble averages. As signals are often functions of time in signal processing applications, egodicity is a useful property. An example of an ensemble average is the mean win at the blackjack tables across a whole casino, in one day. A similar time average could be the mean win at a particular blackjack table over every day for a month, for example. If these averages were approximately the same, then the process of blackjack winning would appear to be ergodic. Ergodicity can be difficult to prove or demonstrate, hence it is often simply assumed.

1.2. Probabilistic Description of a Random Process

Although random processes are governed by chance, more typical values and trends in the signal value can be described. A probability density function can be used to describe the typical intensities of the random signal (over all time). An autocorrelation function describes how similar the signal values are expected to be at two successive time instances. It can

Probability Theory:

Statistics is branch of mathematics that deals with the collection of data. It also concerns with what can be learned from data. Extension of statistical theory is Probability Theory. Probability deals with the result of an experiment whose actual outcome is not known. It also deals with averages of mass phenomenon. The experiment in which the Outcome cannot be predicted with certainty is called Random Experiment. These experiments can also be referred to as a probabilistic experiment in which more than one thing can happen. Eg: Tossing of a coin, throwing of a dice. Deterministic Model and Stochastic Model or Random Mathematical Mode can be used to describe a physical phenomenon. In Deterministic Model there is no uncertainty about its time dependent behavior. A sample point corresponds to the aggregate of all possible outcomes. Sample space or ensemble composed of functions of time-Random Process or stochastic Process.

Types of Random Variable(RV):

1. Discrete Random Variable: An RV that can take on only a finite or countably infinite

set of outcomes.

2. Continuous Random Variable: An RV that can take on any value along a continuum

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