chapter 7 digital communication techniques. benefits of digital communication –noise immunity:...
TRANSCRIPT
Chapter 7
Digital Communication Techniques
Benefits of Digital Communication– Noise Immunity: Digital signals, which are usually
binary, are more immune to noise than analog signals.
– 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 capability.
– 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
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Output spectrum for a sample-and-hold circuit: (a) no aliasing; (b) aliasing distortion
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Copyright ©2004 by Pearson Education, Inc.Upper Saddle River, New Jersey 07458
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Sampling Rate
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
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The A/D converter divides the input voltage range into discrete voltage increments.
Sampling an analog signal
PAM quantizing errors
PAM: (a) input signal; (b) sample pulse; (c) PAM signal(a) Analog input signal; (b) sample
pulse; (c) PAM signal; (d) PCM code
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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, and3. the minimum sampling frequency (Nyquist
rate).
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. 7-25SFDR 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 signals.
– Companding is the most common means of overcoming the problems of quantizing error and noise.
– 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
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Copyright ©2004 by Pearson Education, Inc.Upper Saddle River, New Jersey 07458
All rights reserved.
255 compression characteristics (positive values only)
TomasiElectronic 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
TomasiElectronic 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 signals.
– 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 time.
– 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 converter.
DSP Processors– Most computers and microprocessors use an
organization known as the Von Neumann architecture.
– 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 noise.
Figure 7-38: A block diagram showing the processing algorithm of a nonrecursive FIR filter.