Transcript Qassim University College of Engineering Electrical Engineering

Qassim University
College of Engineering
Electrical Engineering Department
Electronics and Communications
Review of course EE320 Communications
as a Prerequisite for course EE322
Associate Prof. Dr. Ahmed Abdelwahab
Principles
Communication System
Information Signals
The signals emitted by information sources and the signals sent over a
transmission channel can be classified into two distinct categories according to
their physical characteristics. These two categories encompass analog and
digital signals.
An analog signal conveys information through a continuous and smooth
variation in time of a physical quantity such as optical, electrical, or acoustical
intensities and frequencies. Well-known analog signals include audio (sound)
and video messages. For example, an electric signal can vary in frequency
(such as the kHz, MHz, GHz designations in radio communications), and its
intensity can range from low to high voltages.
As the signal travels through the channel, various imperfect properties of the
channel induce impairments to the signal. These include electrical noise effects,
signal distortions, and signal attenuation. The function of the receiver is to
extract the weakened and distorted signal from the channel, amplify it, and
restore it as closely as possible to its original signal before transmission and
passing it on to the message destination.
• Sources of information: Text, speech, audio, pictures,
video and computer data. They are one, two or three
dimensions. Information production and Human
perceptual system for audio and video.
• Communications networks: telephone networks and
Computer networks.
• Communications channels: guided propagation such
as: telephone channels (two-wire, coaxial cable or
optical fiber) and free propagation (wireless channels)
such as: broadcasting channels, mobile channels and
satellite channels
The Modulation Process
The purpose of a communication system is to deliver a
message (information or baseband) signal from an information
source in recognizable form to a user destination, with the
source and the user being physically separated from each
other. To do this, the transmitter modifies the message signal
into a form called passband signal suitable for transmission
over the channel. This modification is achieved by means of a
process known as modulation, which involves varying some
parameter of a carrier wave in accordance with the message
signal. The receiver reconstructs as closely as possible the
original message signal.
This reconstruction is accomplished at the receiver by using a
process known as demodulation, which is the reverse of the
modulation process done at the transmitter.
Types of Modulation
We may classify the modulation process into continuous-wave
modulation and pulse modulation. In continuous-wave (CW) modulation,
a sinusoidal wave is used as the carrier.
When the amplitude of the carrier is varied in accordance with the
message signal, we have amplitude modulation (AM), and when the
angle of the carrier is varied, we have angle modulation. The latter form
of CW modulation may be further subdivided into:
frequency modulation (FM) and phase modulation (PM), in which the
instantaneous frequency and phase of the carrier, respectively, are varied
in accordance with the message signal.
In pulse modulation, on the other hand, the carrier consists of a periodic
sequence of rectangular pulses.
However, owing to the unavoidable presence of noise and distortion in
the received signal, we find that the receiver cannot reconstruct the
original message signal exactly. The resulting degradation in overall
system performance is influenced by the type of modulation scheme
used. Specifically, we find that some modulation schemes are less
sensitive to the effects of noise and distortion than others.
Continuous-Wave (CW) Modulation
Why do we need modulation?
• For use of practical antenna size where the length of the
antenna is proportional to the signal wavelength(λ) about
1/10 of λ. Therefore, the baseband information signal
spectrum needed to be translated up to a higher
frequency band by means of modulations for a smaller
antenna size.
• For use of Multiplexing that is the process of combining
several independent message signals for their
simultaneous transmisson over the same channel.
Multiplexing could be FDM, TDM or CDM or (WDM for
optical fibers).
• For use of Better signal-to-noise ratio, it is found that
some modulation schemes are less sensitive to the
effects of noise and distortion than others.
The quadrature null effect of the coherent detector may also be put to good use
in the construction of the so-called quadrature-carrier multiplexing or
quadrature-amplitude modulation
Frequency Translation
A modulated wave s1 (t)
whose spectrum is centered
on a carrier frequency f1 ,
and the requirement is to
translate it upward in
frequency such that its
carrier frequency is changed
from f1 to a new value f2.
This requirement may be
accomplished using the
mixer shown in Figure 2.16.
Specifically, the mixer is a
device that consists of a
product modulator followed
by a band-pass filter.
Multiplexing
Multiplexing is another important signal processing operation,
whereby a number of independent signals can be combined into
a composite signal suitable for transmission over a common
channel. Voice frequencies transmitted over telephone systems,
range from 300 to 3100 Hz.
To transmit a number of these signals over the same channel,
the signals must be kept apart so that they do not interfere with
each other, and thus they can be separated at the receiving end.
This is accomplished by separating the signals either in
frequency or in time.
The technique of separating the signals in frequency is referred
to as frequency-division multiplexing (FDM), whereas the
technique of separating the signals in time is called timedivision multiplexing (TDM).
The Sampling Theorem
The sampling theorem for strictly band-limited signals of finite energy
may be stated in two equivalent parts, which apply to the transmitter
and the receiver of a pulse modulation system, respectively:
• A band-limited signal of finite energy, which has no frequency
components higher than B Hertz, is completely described by
specifying the values of the signal at instants of time separated by
(1/2B) seconds.
• A band-limited signal of finite energy, which has no frequency
components higher than B Hertz, may be completely recovered from a
knowledge of its samples taken at the rate of 2B samples per second.
• The sampling rate of 2 B samples per second, for a signal whose
bandwidth of B Hertz, is called the Nyquist rate; its reciprocal 1/2 B
(measured in seconds) is called the Nyquist interval.
The Sampling Theorem
some aliasing is produced by the
sampling process if the sampling
frequency is less than Nyquist rate.
Aliasing refers to the phenomenon
of a high-frequency component in
the spectrum of the signal
seemingly taking on the identity of a
lower frequency in the spectrum of
its sampled version, as illustrated in
Figure 3.3.
To combat the effects of aliasing in practice, we may use two corrective measures, as
described here:
1. Prior to sampling, a low-pass anti-aliasing filter is used to attenuate those high
frequency components of the signal that are not essential to the information being
conveyed by the signal.
2. The filtered signal is sampled at a rate slightly higher than the Nyquist rate.
The reconstruction filter is a low-pass filter with
• A passband extending from - W to W, which is itself
determined by the anti-aliasing filter.
• A transition band extending (for positive frequencies)
from W to fs - W, where fs is the sampling rate.
The fact that the reconstruction filter has a
well-defined transition band means that it is
physically realizable.
Practical Sampling
In proving the sampling theorem, we assumed ideal
samples obtained by multiplying a signal g(t) by an
impulse train which is physically nonexistent. In
practice, we multiply a signal g(t) by a train of pulses
of finite width, shown in Fig. b. The sampled signal is
shown in Fig.c. Now is it possible to recover or
reconstruct g(t) from the sampled signal g(t) in
Fig. c?. Unsurprisingly, the answer is positive,
provided that the sampling rate is not below the
Nyquist rate. The signal g(t) can be recovered by
low-pass filtering g(t) as if it were sampled by
impulse train.
Signal Reconstruction: The Interpolation Formula
Pulse Modulation
In continuous-wave (CW) modulation, some parameter of a sinusoidal carrier wave is
varied continuously in accordance with the message signal.
In pulse modulation, some parameter of a pulse train is varied in accordance with the
message signal.
There are two families of pulse modulation: analog pulse modulation and digital pulse
modulation. In analog pulse modulation, a periodic pulse train is used as the carrier
wave, and some characteristic feature of each pulse (e.g., amplitude, duration, or
position) is varied in a continuous manner in accordance with the corresponding
sample value of the message signal. Thus in analog pulse modulation, information is
transmitted basically in analog form, but the transmission takes place at discrete times.
In digital pulse modulation, on the other hand, the message signal is represented in a
form that is discrete in both time and amplitude, thereby permitting its transmission
in digital form as a sequence of coded pulses; this form of signal transmission has no
CW counterpart.
The use of coded pulses for the transmission of analog information-bearing signals
represents a basic ingredient in the application of digital communications. This chapter
may therefore be viewed as a transition from analog to digital communications in
study of the principles of communication systems. We begin the discussion by
describing the sampling process, which is basic to all pulse modulation systems,
whether they are analog or digital.
Pulse Amplitude Modulation (PAM)
In pulse-amplitude modulation (PAM), the amplitudes of
regularly spaced pulses are varied in proportion to the
corresponding sample values of a continuous
message signal; the pulses can be of a rectangular form or
some other appropriate shape.
The dashed curve in fig.3.5
depicts the waveform of
a message signal m(t),
and the sequence of amplitude-modulated rectangular pulses
shown as solid lines represents the corresponding PAM signal
s(t).
In digital circuit technology, two operations that are jointly
called "sample and hold" involve in the generation of the
PAM signal. One important reason for intentionally
lengthening the duration of each sample is to avoid the use of
an excessive channel bandwidth, since bandwidth is inversely
proportional to pulse duration T. However, care has to be
exercised in how long we make the sample duration T. In
order to recover (reconstruct) the original message signal m(t),
The PAM signal s(t) is passed through a LPF whose frequency
response is defined in Figure 3.4c followed by an equalizer in
order to compensate for the amplitude distortion. However,
for a duty cycle T/Ts ≤ 0.1, the amplitude distortion is less than
0.5 percent, in which case the need for equalization may be
omitted altogether.
Time Division Multiplexing (TDM)
An important feature of the sampling process is a
conservation of time. That is, the transmission of the
message samples engages the communication channel
for only a fraction of the sampling interval on a
periodic basis, and in this way some of the time
interval between adjacent samples is cleared for use by
other independent message sources on a time-shared
basis resulting in a time-division multiplex (TDM)
system, which enables the joint utilization of a
common communication channel by a plurality of
independent message sources without mutual
interference among them.
Synchronization is essential for a satisfactory operation of the TDM system. The way
this synchronization is implemented depends naturally on the method of pulse
modulation used to transmit the multiplexed sequence of samples.
The TDM system is highly sensitive to dispersion in the common channel, that is, to
variations of amplitude with frequency or lack of proportionality of phase with
frequency.
Accordingly, accurate equalization of both magnitude and phase responses of the
channel is necessary to ensure a satisfactory operation of the TDM system
TDM is immune to nonlinearities in the channel as a source of cross-talk. Because
different message signals are not simultaneously applied to the channel.
Pulse Code Modulation (PCM)
In pulse-code modulation (PCM), a message signal is
represented in discrete form in both time and
amplitude. This form of signal representation permits
the transmission of the message signal as a sequence
of coded binary pulses. Given such a sequence, the
effect of channel noise at the receiver output can be
reduced to a negligible level simply by making the
average power of the transmitted binary PCM wave
large enough compared to the average power of the
noise.
The Quantization Process
The sampling process takes care of the discrete-time
representation of the message signal while the quantization
process takes care of the discrete amplitude representation of
the message signal. A continuous signal, such as voice, has a
continuous range of amplitudes and therefore its samples have
a continuous amplitude range. In other words, within the finite
amplitude range of the signal, we find an infinite number of
amplitude levels. It is not necessary in fact to transmit the
exact amplitudes of the samples. Any human sense (the ear or
the eye), as ultimate receiver, can detect only finite intensity
differences. This means that the original continuous signal
may be approximated by a signal constructed of discrete
amplitudes selected on a minimum error basis from an
available set.
The discrete amplitudes mk,
k = 1, 2,. . . , L, at the quantizer
input are called decision levels
or decision thresholds. At the
quantizer output, the index k is
transformed into an amplitude vk
that represents all amplitudes of
the cell
; the discrete
amplitudes vk, k = 1,2,. . . , L,are
called representation levels or
reconstruction levels, and the
spacing between two adjacent
representation levels is called a
quantum or step-size. Thus, the
quantizer output v equals
vk if the input signal sample m
belongs to the interval
Quantizers can be of a uniform or nonuniform type. In a uniform quantizer, the
representation levels are uniformly spaced; otherwise, the quantizer is nonuniform.
Binary Encoding
To exploit the advantages of sampling and quantizing for the
purpose of making the transmitted signal more robust to noise,
interference and other channel impairments, we require the use
of an encoding process to translate the discrete set of sample
values to a more appropriate form of signal. A particular
arrangement of symbols used in a code to represent a single
value of the discrete set is called a codeword or character. The
two symbols of a binary code are customarily denoted as 0 and
1. in a binary code, each codeword consists of R bits. Thus R
denotes the number of bits per sample. Then, using such a
code, we may represent a total of 2R distinct samples. For
example, a sample quantized into one of 256 levels may be
represented by an 8-bit codeword.
PCM Receiver
• Decoding: The first operation in the receiver is to
regenerate (i.e., reshape and clean up) the received pulses
one last time. These clean pulses are then regrouped into
code words and decoded (i.e., mapped back) into a
quantized PAM signal.
• Filtering: The final operation in the receiver is to recover
the message signal by passing the decoder output through a
low-pass reconstruction filter whose cutoff frequency is
equal to the message bandwidth B. Assuming that the
transmission path is error free, the recovered signal
includes no noise with the exception of the initial
distortion introduced by the quantization process.
Differential PCM
The difference between the successive
source samples are PC modulated instead
of the original samples for smaller range of
values and hence less bits/sample can be
used to achieve more data compression with
good quality of the reconstructed information
signal.
Noise Considerations in PCM Systems
The performance of a PCM system is influenced by
two major sources of noise:
1. Channel noise, which is introduced anywhere
between the transmitter output and the receiver
input. Channel noise is always present, once the
equipment is switched on.
2. Quantization noise, which is introduced in the
transmitter. Unlike channel noise, quantization noise
is signal dependent in the sense that it disappears
when the message signal is switched off.
Advantages of PCM
In a generic sense, pulse-code modulation (PCM) has emerged as the most
favored modulation scheme for the transmission of analog information-bearing
signals such as voice and video signals. We may summarize the important
advantages of PCM as follows:
1. Robustness to channel noise and interference.
2. Efficient regeneration of the coded signal along the transmission path.
3. Efficient exchange of increased channel bandwidth for improved signal-tonoise ratio, obeying an exponential law.
4. A uniform format for the transmission of different kinds of baseband signals,
hence their integration with other forms of digital data in a common network.
5. Comparative ease with which message sources may be dropped or reinserted
in a time-division multiplex system.
6. Secure communication through the use of special modulation schemes or
encryption.
These advantages, however, are attained at the cost of increased system
complexity and increased channel bandwidth.
Today, communication channel bandwidth constraint becomes of no real
concern for two different reasons:
First, the increasing availability of wideband communication channels
means that bandwidth is no longer a system constraint in the traditional
way it used to be. This is because of the deployment of communication
satellites for broadcasting and the ever-increasing use of fiber optics for
networking.
Second, the use of sophisticated data compression techniques, it is
indeed possible to remove the redundancy inherently present in a PCM
signal and thereby reduce the bit rate of the transmitted data without
serious degradation in system performance.
In effect, increased processing complexity (and therefore increased cost
of implementation) is traded off for a reduced bit rate and therefore
reduced bandwidth requirement.
Regenerative Repeater
The most important feature of PCM systems lies in the ability to control the effects of distortion
and noise produced by transmitting a PCM signal through a channel. This capability is
accomplished by reconstructing the PCM signal by means of a chain of regenerative repeaters
located at sufficiently close spacing along the transmission route.
The equalizer shapes the received pulses so as to compensate for the effects of amplitude and
phase distortions produced by the no ideal channel. The timing circuitry provides a periodic
pulse train, derived from the received pulses, for sampling the equalized pulses at the instants at
time where the signal-to-noise ratio is a maximum. Each sample so extracted is compared to a
predetermined threshold in the decision-making device. In each bit interval, a decision is then
made whether the received symbol is a 1 or a 0 on the basis of whether the threshold is exceeded
or not. If the threshold is exceeded, a clean new pulse representing symbol 1 is transmitted to the
next repeater. Otherwise, another clean new pulse representing symbol 0 is transmitted.
In practice, however, the regenerated signal departs from
the original signal for two main reasons:
1. The unavoidable presence of channel noise and
interference causes the repeater to make wrong decisions
occasionally, thereby introducing bit errors into the
regenerated signal.
2.
If the spacing between received pulses deviates from its
assigned value, a jitter is introduced into the regenerated
pulse position, thereby causing distortion.
T1 Carrier System
The T1 system, which carries 24 voice channels over separate pairs of
wires with regenerative repeaters spaced at approximately 2-km
intervals. each of the 24 voice channels uses a binary code with an 8-bit
word. The first bit indicates whether the input voice sample is positive
(1) or negative (0). The next three bits of the code word identify a
particular segment inside which the amplitude of the input voice sample
lies, and the last four bits identify the actual representation level inside
that segment.
With a sampling rate of 8 kHz, each frame of the multiplexed signal
occupies a period of 125 μsec. In particular, it consists of twenty-four 8bit words, plus a single bit that is added at the end of the frame for the
purpose of synchronization. Hence, each frame consists of a total of
(24 x 8) + 1 = 193 bits. Correspondingly, the duration of each bit equals
0.647 μsec, and the resulting transmission rate is 1.544 megabits per
second (Mb/s).
Time Division Multiplexing (TDM)
The T1 carrier (1.544 Mbps)
TDM Hierarchy
Multiplexing T1 streams into higher carriers
T1 (DS1) consists of 24 Telephone calls
T2 (DS2) consists of 24*4= 96 Telephone calls
T3 (DS3) consists of 96*7=672 Telephone calls
T4 (DS4) consists of 672*6= 4032 Telephone calls
Metric Units
The principal metric prefixes.
Memory
Transmission rate
1-KB memory = 2^10 = 1024 bytes
1-kbps = 10^3 bits/sec
1-MB memory = 2^20 = 1,048,576 bytes
1-Mbps = 10^6 bits/sec
1-GB memory = 2^30 = 1,073,741,824 bytes
1-Gbps = 10^9 bits/sec
1-TB memory = 2^40 = 1,099,511,627,776
40 bytes