Digital Signal Processing (DSP)

Chapter 7
Digital Communication Techniques
Benefits of Digital Communication
– Noise Immunity: Digital signals, which are usually
binary, are more immune to noise than analog
– Error Detection and Correction: With digital
communication, transmission errors can usually
be detected and corrected.
– Compatibility with Time-Division Multiplexing:
Digital data communication is adaptable to time
division multiplexing schemes. Multiplexing is the
process of transmitting two or more signals
simultaneously on a single channel.
Benefits of Digital Communication (cont.)
– Digital ICs: Digital ICs are smaller and easier to
make than linear ICs, therefore can be more
complex and provide greater processing
– Digital Signal Processing (DSP): DSP is the
processing of analog signals by digital methods.
This involves converting an analog signal to
digital and then processing with a fast digital
computer. Processing means filtering,
equalization, phase shifting, mixing, and other
traditionally analog methods.
Disadvantages of Digital Communication
– Considerable bandwidth size is required by a
digital signal.
– Digital communication circuits are usually more
complex than analog circuits.
Simplified block diagram of a single-channel, simplex PCM transmission system
Electronic Communications Systems, 5e
Sampling Rate
Output spectrum for a sample-and-hold circuit: (a) no aliasing; (b) aliasing distortion
Electronic Communications Systems, 5e
Copyright ©2004 by Pearson Education, Inc.
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Example 1:
For a PCM system with a maximum audio input frequency of 4 kHz,
Determine the minimum sample rate and the alias frequency produced
if a 5-kHz audio signal were allowed to enter the sample-and–hold circuit.
(a) Sample-and-hold circuit; (b) input and output waveforms
Electronic Communications Systems, 5e
The A/D converter divides the input voltage
range into discrete voltage increments.
Sampling an analog signal
quantizing errors
(a) Analog input signal; (b) sample
pulse; (c) PAM signal; (d) PCM code
Electronic Communications Systems, 5e
PAM: (a) input signal; (b) sample
pulse; (c) PAM signal
Example 2
An information signal to be transmitted
digitally is a rectangular wave with a period of
71.4 µs. It has been determined that the wave
will be adequately passed if the bandwidth
includes the fourth harmonic. Calculate
1. the signal frequency,
2. the fourth harmonic, and
3. the minimum sampling frequency (Nyquist
Example 3
The voltage range of an A/D converter that
uses 14-bit numbers is -6 to +6 V. Find
1. the number of discrete levels (binary
codes) that are represented,
2. the number of voltage increments used to
divide the total voltage range, and
3. the resolution of digitization expressed as
the smallest voltage increment.
ADC Specifications
 Resolution
q = Vmax/2n
 Dynamic range (DR)
DR = 20log(Vmax/q) = 20log[(Vmax/(Vmax/2n)] = 20log2n = 6.02n
 Signal-to-noise ratio (SNR)
 Spurious free dynamic range (SFDR)
Fig. 7-25
SFDR is the difference between the signal voltage and highest spur voltage
Pulse-Code Modulation: Companding
– Companding is a process of signal compression and
expansion that is used to overcome problems of
distortion and noise in the transmission of audio
– Companding is the most common means of
overcoming the problems of quantizing error and
– All A/D and D/A conversion and related functions, as
well as companding, are taken care of by a single
large-scale IC chip known as a codec or vocoder.
PCM System with Analog Companding
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-law compression characteristics
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Digitally companded PCM system
Electronic Communications Systems, 5e
Copyright ©2004 by Pearson Education, Inc.
Upper Saddle River, New Jersey 07458
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255 compression characteristics (positive values only)
Electronic Communications Systems, 5e
Copyright ©2004 by Pearson Education, Inc.
Upper Saddle River, New Jersey 07458
All rights reserved.
12-bit-to-8-bit digital companding: (a) 8-bit 255 compressed code
format; (b) 255 encoding table; (c) 255 decoding table
Electronic Communications Systems, 5e
Copyright ©2004 by Pearson Education, Inc.
Upper Saddle River, New Jersey 07458
All rights reserved.
Figure 7-2: Parallel data transmission.
Figure 7-3: Serial data transmission.
Figure 7-4: Parallel-to-serial and serial-to-parallel data transfers with shift registers.
The Basis of DSP
– Digital signal processing (DSP) is the use of a fast
digital computer to perform processing on digital
– Any digital computer with sufficient speed and
memory can be used for DSP.
Figure 7-36: Concept of DSP
Basis of DSP
– An analog signal to be processed is fed to an A/D
converter, where it is converted into a series of binary
numbers and stored in a read-write random-access
memory (RAM).
– A program, usually stored in a read-only memory
(ROM), performs mathematical and other
manipulations on the data.
– Most digital processing involves complex
mathematical algorithms that are executed in real
– The processing results in another set of data words
which are also stored in RAM.
– They can be used in digital form or fed to a D/A
DSP Processors
– Most computers and microprocessors use an
organization known as the Von Neumann
– Physicist John Von Neumann created the stored
program concept that is the basis of operation of all
digital computers.
– The key feature of the Von Neumann arrangement is
that both instructions and data are stored in a
common memory space.
– There is only one path between the memory and the
CPU, and therefore only one data or instruction word
can be accessed at a time.
DSP Processors
– DSP microprocessors work in a similar way, but they
use a variation called the Harvard architecture.
– In a Harvard architecture microprocessor, there are
two memories, a program or instruction memory,
usually a ROM, and a data memory, which is a RAM.
– There are two data paths into and out of the CPU
between the memories.
– Because both instructions and data can be accessed
simultaneously, very high-speed operation is possible.
DSP Applications
– The most common DSP application is filtering. A DSP
processor can perform bandpass, low-pass, high-pass,
and band-reject filter operation.
– Data compression is a process that reduces the
number of binary words needed to represent a given
analog signal.
– Spectrum analysis is the process of examining a signal
to determine its frequency content.
– Signal averaging is the process of sampling a
recurring analog signal transmitted in the presence of
Figure 7-38: A block diagram showing the processing algorithm of a nonrecursive FIR filter.

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