Introduction to digital communication, base band system, formatting of textual data, MESSAGES, CHARACTERS, AND SYMBOLS, Example of Messages, Characters, and Symbols, Baseband Modulation, Intersymbol Interference

1. DIGITAL BASE
BAND MODULATION
TECHNIQUES
Presented by- Prof.Prajakta S. Wasekar
Assistant Professor in GHRCE

4. Digital Communication System

5. Information source:
It generates the message signal to be transmitted. In analog
communication, the information is analog i.e speech signal. In case
of digital communication the information is discrete (e.g) data from
computers, teletype etc. Analog signal can be converted into digital
by sampling and quantization.
Formatter:
It converts electrical signals at the output of the transducer into a
sequence of digital signals.
Source Encoder:
Source encoder first converts the symbols into digital form. (i.e.
binary sequence of 1’s and 0’s). Every binary ‘1’ and ‘0’ is called a
bit. The group of bits is called a code word. The codeword can be of
4,8,16 or 32 bits length. For (e.g.) 8 bits will have 28 = 256 distinct
code word. Source encoders are Pulse Code Modulators, Delta
Modulators.

6. Channel Encoder:
After the message signal is converted into binary 1’s and 0’s, it is
passed through the communication channel where noise is added.
The channel encoder adds redundant binary bits to the input sequence
to provide reliable communication.
Base band processor:
For proper detection in the receiver and to reduce noise and
interference, some pulse shaping techniques, line coding and special
filters are used in the receiver. These are called base band processor,
(e.g.) fixed telephony and data storage systems.
Band pass Modulator:
Band pass Modulation scheme is used in digital communication
system for transmitting information over channel

7. Communication channel:
Communication channel is the medium used for transmission of
signal from one place to another place.
Band pass Demodulator:
At the receiver the digital demodulator converts the input modulated
signal to the sequence of binary bits.
Channel Decoder:
It reconstructs the original information sequence.
Source Decoder:
Source Decoder accepts the output sequence from channel decoder
and attempts to reconstruct the original signal from source.

8. Deformatter:
This converts back the digital data to either discrete form or analog
form.
Output Transducer:
This converts the estimate of digital signal to analog non-electrical
signal if needed. However, in data communication, input signal and
reconstructed signal both are in digital form. So, an output transducer
is not needed in that case.

9. Baseband
 Baseband refers to the original frequency range of a transmission
signal before it is converted, or modulated, to a different frequency
range.
 For example, an audio signal may have a baseband range from 20
to 20,000 hertz. When it is transmitted on a radio frequency (RF), it
is modulated to a much higher, inaudible, frequency range.
 Signal modulation is used for radio broadcasts, as well as several
types of telecommunications, including cell phone conversations
and satellite transmissions.
 Therefore, most telecommunication protocols require
original baseband signals to be modulated to a higher
frequency before they are transmitted.

10. Baseband System

12. What is Formatting?
 In Formatting, sources of information are converted into the
sequences of binary digits. The sources of information consist of 1.
1. Digital information,
2. Textual information and
3. Analog information
• Data already in digital format would bypass the formatting
function.
• Data in text is transformed into binary digit.
• Analog information is formatted using 3 processes: Sampling,
Quantization, and Coding

13.  Then these digits are to be transmitted through the Baseband
channel, such as a pair of wires or a coaxial cable, after they are
transformed into the waveforms in a block labeled Pulse modulate
that are compatible with the channel.
 For baseband channel, the waveforms are pulses. After
transmission through the channel, pulses are demodulated,
formatted to recover as the sources of information.

14. FORMATTING TEXTUAL DATA (CHARACTER CODING)
 The original form of most communicated data (except for
computer-to-computer transmissions) is either textual or analog.
 If the data consist of alphanumeric text, they will be character
encoded with one of several standard formats; examples include
the American Standard Code for Information Interchange (ASCII),
the Extended Binary Coded Decimal Interchange Code
(EBCDIC), Baudot, and Hollerith.
 The textual material is thereby transformed into a digital format.
The ASCII format is shown in Figure 2.3; the EBCDIC format is
shown in Figure 2.4.

15. Figure 2.3 Seven-bit American standard code
for information interchange (ASCII).

16.  The bit numbers signify the order of serial transmission, where bit
number 1 is the first signaling element.
 Character coding, then, is the step that transforms text into binary
digits (bits).
 Sometimes existing character codes are modified to meet
specialized needs.
 For example, the 7-bit ASCII code (Figure 2.3) can be modified to
include an added bit for error detection purposes.
 On the other hand, sometimes the code is truncated to a 6-bit
ASCII version, which provides capability for only 64 characters
instead of the 128 characters allowed by 7-bit ASCII.

18. MESSAGES, CHARACTERS, AND SYMBOLS
 Textual messages comprise a sequence of alphanumeric characters.
 When digitally transmitted, the characters are first encoded into a
sequence of bits, called a bit stream or baseband signal.
 Groups of k bits can then be combined to form new digits, or
symbols, from a finite symbol set or alphabet of M = 2k such
symbols.
 A system using a symbol set size of M is referred to as an M-ary
system. The value of k or M represents an important initial choice in
the design of any digital communication system

19. 1. For k = 1, the system is termed binary, the size of the symbol set is
M = 2, and the modulator uses one of the two different waveforms
to represent the binary “one” and the other to represent the binary
“zero.”
1. For k = 2, the system is termed quaternary or 4-ary (M = 4). At
each symbol time, the modulator uses one of the four different
wave- forms that represents the symbol.

20. Example of Messages, Characters, and Symbols
 Figure a) shows examples of bit stream partitioning, based on the
system specification for the values of k and M.
 The textual message in the figure is the word “THINK.” Using 6-bit
ASCII character coding (bit numbers 1 to 6 from Figure 2.3) yields a
bit stream comprising 30 bits.
 The symbol set size, M, has been chosen to be 8 (each symbol
represents an 8-ary digit). The bits are therefore partitioned into groups
of three (k = log2 8); the resulting 10 numbers represent the 10 octal
symbols to be transmitted.
 The transmitter must have a eight waveforms si(t), where i = 1, . . . , 8,
to represent the possible symbols, any one of which may be transmitted
during a symbol time.
 The final row of figure a) lists the 10 waveforms that an 8-ary
modulating system transmits to represent the textual message
“THINK.”

21. Figure a) Messages, characters, and symbols. (i) 8-ary example. (ii) 32-ary example.

22. Example 1:
 In ASCII alphabets, numbers, and symbols are encoded using
a 7-bit code
 A total of 27 = 128 different characters can be represented using
a 7-bit unique ASCII code
Character Coding (Textual Information)
22

23. FORMATTING ANALOG INFORMATION
 If the information is analog, it cannot be character encoded as in the
case of textual data; the information must first be transformed into a
digital format.
 To transform an analog waveform into a form that is compatible with
a digital communication, the following steps are taken:
1.Sampling
2.Quantization and Encoding
3.Base-band transmission (PCM)

24. Sampling and Sampling theorem
 This process is based on Shannon’s sampling theorem. Numbers of
samples of the signal are taken at regular intervals, at a rate higher
than twice the highest significant signal frequency.
Or
 Sampling is the process of converting continuous time signal to an
equivalent discrete time signal

25.  The maximum frequency component of g(t) is fm. To recover the
signal g(t) exactly from its samples it has to be sampled at a rate
fs ≥ 2fm.
 The minimum required sampling rate fs = 2fm is called Nyquist rate.

26. Quantization:
The process of transforming Sampled amplitude values of a message
signal into a discrete amplitude value is referred to as Quantization.
The quantization Process has a two-fold effect:
1. the peak-to-peak range of the input sample values is subdivided
into a finite set of decision levels or decision thresholds that are
aligned with the risers of the staircase, and
2. the output is assigned a discrete value selected from a finite set of
representation levels that are aligned with the treads of the staircase

27. Baseband Modulation
• An information bearing-signal must conform to the limits of its
channel
• Generally modulation is a two-step process
– baseband: shaping the spectrum of input bits to fit in a limited
spectrum
– passband: modulating the baseband signal to the system carrier
• Most common baseband modulation is Pulse Amplitude Modulation
(PAM)
– data amplitude modulates a sequence of time translates of basic
pulse
– PAM is a linear form of modulation: easy to equalize, BW is
pulse BW
– Typically baseband data will modulate in-phase [cos] and
quadrature [sine] data streams to the carrier passband
• Special cases of modulated PAM include
– phase shift keying (PSK)
– quadrature amplitude modulation (QAM)

28. Waveform Representation of Binary Digits
 An analog waveforms are transformed into binary digits via the
use of PCM. There is nothing “physical” about the digits
resulting from this process. Digits are just abstractions—a way to
describe the message information.
 We will represent the binary digits with electrical pulses in order
to transmit them through a baseband channel.
 We will represent the binary digits with electrical pulses in order
to transmit them through a baseband channel. Codeword time
slots are shown in figure below, where the codeword is a 4-bit
representation of each quantized sample

29. (c)
Figure :Example of waveform representation of binary digits.
(a)PCM sequence. (b) Pulse representation of PCM.
(c) Pulse wave- form (transition between two levels).

30. Pulse code modulation
 Pulse Code Modulation(PCM) is a technique where the message
signal is represented by a sequence of coded pulses.
 In PCM, the binary code varies according to the amplitude of
analog signal.
 It is digitally encoded pulse modulation with pulses are of fixed
length and amplitude

31. Basic elements of a PCM system

35. SOURCES OF CORRUPTION
 The analog signal recovered from the sampled, quantized, and
transmitted pulses will contain corruption from several sources.
 The sources of corruption are related to (1) sampling and
quantizing effects, and (2) channel effects. These effects are
considered in the sections that follow.

36. 1.Sampling and Quantizing Effects
1. Quantization Noise
 The distortion inherent in quantization is a round-off or truncation
error.
 The process of encoding the PAM signal into a quantized PAM
signal involves discarding some of the original analog information.
 This distortion, introduced by the need to approximate the
analog waveform with quantized samples, is referred to as
quantization noise; the amount of such noise is inversely
proportional to the number of levels employed in the quantization
process.

37. Quantizer Saturation
 The quantizer (or analog-to-digital converter) allocates L levels to
the task of approximating the continuous range of inputs with a
finite set of outputs.
 The range of inputs for which the difference between the input and
output is small is called the operating range of the converter.
 If the input exceeds this range, the difference between the input and
the output becomes large, and we say that the converter is operating
in saturation.

38. Channel Effects
1.Channel Noise
 Thermal noise, interference from other users, and interference
from circuit switching transients can cause errors in detecting
the pulses carrying the digitized samples.
 Channel-induced errors can degrade the reconstructed signal
 This rapid degradation of output signal quality with
channel-induced errors is called a threshold effect.
 If the channel noise is small, there will be no problem detecting
the presence of the waveforms. Thus, small noise does not
corrupt the reconstruct signals.
 On the other hand, if the channel noise is large enough to affect
our ability to detect the waveforms, the resulting detection error
causes reconstruction errors.

39. Intersymbol Interference
 The channel is always bandlimited. A bandlimited channel
disperses or spreads a pulse waveform passing through it .
 When the channel bandwidth is much greater than the pulse
bandwidth, the spreading of the pulse will be slight.
 When the channel bandwidth is close to the signal bandwidth, the
spreading will exceed a symbol duration and cause signal pulses to
overlap. This overlapping is called intersymbol interference (ISI).

40. Signal Characteristics
A signal can be represented as a function of time, i.e. it varies with
time. However, it can be also expressed as a function of frequency, i.e.
a signal can be considered as a composition of different frequency
components. Thus, a signal has both time-domain and frequency
domain representation.
Time-domain concepts
A signal is continuous over a period, if
i.e., there is no break in the signal. A signal is discrete if it takes on
only a finite number of values.
A signal is periodic if and only if
s (t+T) = s (t) for - α < t < α ,
where T is a constant, known as period. The period is measured in
seconds.

41. In other words, a signal is a periodic signal if it completes a pattern
within a measurable time frame. A periodic signal is characterized by
the following three parameters.
Amplitude: It is the value of the signal at different instants of time. It
is measured in volts.
Frequency: It is inverse of the time period, i.e. f = 1/T. The unit of
frequency is Hertz (Hz) or cycles per second.
Phase: It gives a measure of the relative position in time of two
signals within a single period. It is represented by φ in degrees or
radian.

42. A sine wave, the most fundamental periodic signal, can be
completely characterized by its amplitude, frequency and phase.
Examples of sine waves with different amplitude, frequency and
phase are shown in Fig below.
Figure : Examples of signals with different amplitude, frequency
and phase

43. An aperiodic signal or nonperiodic signal changes constantly without
exhibiting a pattern or cycle that repeats over time as shown in Fig. a &
b.
a)Analog aperiodic signal b) Digital aperiodic signal

44. Frequency domain concepts
 The time domain representation displays a signal using time-domain
plot, which shows changes in signal amplitude with time.
 The time-domain plot can be visualized with the help of an
oscilloscope.
 The relationship between amplitude and frequency is provided by
frequency domain representation, which can be displayed with the
help of spectrum analyser.

45. Time domain and frequency domain representations of three sine waves of
three different frequencies are shown in fig below.
Figure : Time domain and frequency domain representations of sine
waves

46. Frequency Spectrum
Frequency spectrum of a signal is the range of frequencies that a signal
contains.
Example: Consider a square wave shown in Fig. 2.1.8(a). It can be
represented by a series of sine waves S(t) = 4A/πsin2πft +
4A/3πsin(2π(3f)t) + 4A/5πsin2π (5f)t + . . . having frequency
components f, 3f, 5f, … and amplitudes 4A/π, 4A/3π, 4A/5π and so on.
The frequency spectrum of this signal can be approximation comprising
only the first and third harmonics as shown in Fig. (b)
Figure (a) A square wave, (b) Frequency spectrum of a square wave

47. Digital Signal
 In addition to being represented by an analog signal, data can be
also be represented by a digital signal.
 Most digital signals are aperiodic and thus, period or frequency is
not appropriate.
 Two new terms, bit interval (instead of period) and bit rate (instead
of frequency) are used to describe digital signals.
 The bit interval is the time required to send one single bit. The bit
rate is the number of bit interval per second.
Figure: Bit Rate and Bit Interval

48. Line code
A line code is the code used for data transmission of a digital signal over
a transmission line. This process of coding is chosen so as to avoid
overlap and distortion of signal such as inter-symbol interference.
Properties of Line Coding
Following are the properties of line coding −
 As the coding is done to make more bits transmit on a single signal,
the bandwidth used is much reduced.
 For a given bandwidth, the power is efficiently used.
 The probability of error is much reduced.
 Error detection is done and the bipolar too has a correction capability.
 Power density is much favorable.
 The timing content is adequate.
 Long strings of 1s and 0s is avoided to maintain transparency.

49. Types of Line Coding
Unipolar signaling is also called as On-Off Keying or simply OOK.
The presence of pulse represents a 1 and the absence of pulse
represents a 0.
Unipolar Signaling