Digital Communication Techniques 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 Tomasi Electronic Communications Systems, 5e

Sampling Rate Output spectrum for a sample-and-hold circuit: (a) no aliasing; (b) aliasing distortion Tomasi Electronic Communications Systems, 5e Copyright ©2004 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved.

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 Tomasi Electronic Communications Systems, 5e

Sampling an analog signal 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 Tomasi Electronic Communications Systems, 5e

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 the signal frequency, the fourth harmonic, and 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 the number of discrete levels (binary codes) that are represented, the number of voltage increments used to divide the total voltage range, and 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 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 Tomasi Electronic Communications Systems, 5e

-law compression characteristics Tomasi Electronic Communications Systems, 5e

Digitally companded PCM system Tomasi Electronic Communications Systems, 5e Copyright ©2004 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved.

255 compression characteristics (positive values only) Tomasi 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 Tomasi 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 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.