2. OBJECTIVES:
To introduce the concepts of various analog modulations
and their spectral characteristics.
To understand the properties of random process.
To know the effect of noise on communication systems.
To study the limits set by Information Theory.
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KARPAGAM INSTITUTE OF TECHNOLOGY, COIMBATORE
3. Fundamentals
Communication is the process of exchanging information.
Basic components:
Transmitter
Channel or medium
Receiver
Noise degrades or interferes with transmitted information.
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4. Transmitter
The transmitter is a collection of electronic components and
circuits that converts the electrical signal into a signal suitable for
transmission over a given medium.
Receivers
A receiver is a collection of electronic components and circuits that
accepts the transmitted message from the channel and converts it
back into a form understandable by humans.
Communication Channel
The communication channel is the medium by which the electronic
signal is sent from one place to another.
Transceivers
A transceiver is an electronic unit that incorporates circuits that
both send and receive signals.
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5. UNIT I - AMPLITUDE MODULATION
To introduce the concepts of various amplitude modulations
and their spectral characteristics for designing AM
communication systems
Modulation is the process of superimposing a low frequency
signal on a high frequency carrier signal.
CONTENT:
AMPLITUDE MODULATION
AM TRANSMITTER
SSB - SC
VSB - SC
DSB - SC
HILBERT TRANSFORM
SUPER HETERODYNE RECEIVER
COMPARISION OF VARIOUS AM TECHNIQUES
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6. UNIT II - ANGLE MODULATION
Angle modulation is the process by which the angle (frequency or
Phase) of the carrier signal is changed in accordance with the
instantaneous amplitude of modulating or message signal also
known as “Exponential modulation"
classified into two types such as
Frequency modulation (FM)
Phase modulation (PM)
CONTENT:
• FREQUENCY & PHASE MODULATION
• NARROW BAND FM
• WIDE BAND FM
• GENERATION OF WIDE BAND FM
• TRANSMISSION BANDWIDTH
• FM TRANSMITTER
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7. UNIT III - RANDOM PROCESS
In probability theory, a stochastic process, or sometimes random process is a collection
of random variables, representing the evolution of some system of random values over
time. This is the probabilistic counterpart to a deterministic process. A random process,
or stochastic process, X(t), is an ensemble of number of sample functions {X1(t),X2(t), .
. . ,X_(t)} together with a probability rule which assigns a probability to any meaningful
event associated with the observation of these functions. Suppose the sample function
Xi(t) corresponds to the sample point si in the sample space S and occurs with
probability Pi.
may be finite or infinite.
Sample functions may be defined at discrete or continuous time instants. Random
process associated with the Poisson model, and more generally, renewal theory include
The sequence of inter arrival times.
The sequence of arrival times.
The counting process.
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8. CONTENT:
RANDOM VARIABLES
CENTRAL LIMIT THEOREM
STATIONARY PEROCESS
CORRELATION
COVARIANCE FUNCTION
ERGODIC PROCESS
GAUSSIAN PROCES
FLITERING THROUGH RANDOM PROCESS
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9. UNIT IV -NOISE CHARACTERIZATION
Noise is a general term which is used to describe an unwanted signal which
affects a wanted signal. These unwanted signals arise from a variety of
sources which may be considered in one of two main categories:-
• Interference, usually from a human source (man made)
• Naturally occurring random noise
Noise is an inevitable consequence of the working of minerals and is an
important health and safety consideration for those working on the site.
Whether it becomes "environmental noise" depends on whether it disrupts
or disturbs people outside the site boundary.
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10. CONTENT:
NOISE IN COMMUNCATION SYSTEM
CLASSIFICATION OF NOISE
NOISE FIGURE & TEMPERATURE
NOISE IN CASCADE SYSTEMS
REPRESENTATION OF NARROW BAND NOISE
NOISE PERFORMANCE
PREEMPHESIS & DE EMPHESIS
CAPTURE AND THERSHOLD EFFECT
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11. UNIT V SAMPLING AND QUANTIZATION
An analog-to-digital converter (ADC) can be modeled as two
processes: sampling and quantization. Sampling converts a time-varying
voltage signal into a discrete-time signal, a sequence of real
numbers. Quantization replaces each real number with an approximation
from a finite set of discrete values.
Analog signal is sampled every TS secs.
Ts is referred to as the sampling interval.
fs = 1/Ts is called the sampling rate or sampling frequency.
There are 3 sampling methods:
Ideal - an impulse at each sampling instant
Natural - a pulse of short width with varying amplitude
Flattop - sample and hold, like natural but with single amplitude value
The process is referred to as pulse amplitude modulation PAM and the
outcome is a signal with analog (non integer) values
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