UNIT: 3 Digital and Analog Transmission
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Digital Transmission 01204325 Data Communications and Computer Networks
Digital Transmission 01204325 Data Communications and Computer Networks Chaiporn Jaikaeo Department of Computer Engineering Kasetsart University Based on lecture materials from Data Communications and Networking, 5th ed., Behrouz A. Forouzan, McGraw Hill, 2012. Revised 2021-05-07 Outline • Line coding • Encoding considerations • DC components in signals • Synchronization • Various line coding methods • Analog to digital conversion 2 Line Coding • Process of converting binary data to digital signal 3 Signal vs. Data Elements 1 data element = 1 symbol 4 Encoding Considerations • Signal spectrum ◦ Lack of DC components ◦ Lack of high frequency components • Clocking/synchronization • Error detection • Noise immunity • Cost and complexity 5 DC Components • DC components in signals are not desirable ◦ Cannot pass thru certain devices ◦ Leave extra (useless) energy on the line ◦ Voltage built up due to stray capacitance in long cables v Signal with t DC component v Signal without t DC component 6 Synchronization • To correctly decode a signal, receiver and sender must agree on bit interval 0 1 0 0 1 1 0 1 Sender sends: v 01001101 t 0 1 0 0 0 1 1 0 1 1 Receiver sees: v 0100011011 t 7 Providing Synchronization • Separate clock wire Sender data Receiver clock • Self-synchronization 0 1 0 0 1 1 0 1 v t 8 Line Coding Methods • Unipolar ◦ Uses only one voltage level (one side of time axis) • Polar ◦ Uses two voltage levels (negative and positive) ◦ E.g., NRZ, RZ, Manchester, Differential Manchester • Bipolar ◦ Uses three voltage levels (+, 0, and -
An Efficient Utilization of Power Spectrum Density for Smart Cities
sensors Article Moving towards IoT Based Digital Communication: An Efficient Utilization of Power Spectrum Density for Smart Cities Tariq Ali 1,*, Abdullah S. Alwadie 1, Abdul Rasheed Rizwan 2, Ahthasham Sajid 3 , Muhammad Irfan 1 and Muhammad Awais 4 1 Electrical Engineering Department, College of Engineering, Najran University, Najran 61441, Saudi Arabia; [email protected] (A.S.A.); [email protected] (M.I.) 2 Department of Computer Science, Punjab Education System, Depaalpur 56180, Pakistan; [email protected] 3 Department of Computer Science, Faculty of ICT, Balochistan University of Information Technology Engineering and Management Sciences, Quetta 87300, Pakistan; [email protected] 4 School of Computing and Communications, Lancaster University, Bailrigg, Lancaster LA1 4YW, UK; [email protected] * Correspondence: [email protected] Received: 8 April 2020; Accepted: 14 May 2020; Published: 18 May 2020 Abstract: The future of the Internet of Things (IoT) is interlinked with digital communication in smart cities. The digital signal power spectrum of smart IoT devices is greatly needed to provide communication support. The line codes play a significant role in data bit transmission in digital communication. The existing line-coding techniques are designed for traditional computing network technology and power spectrum density to translate data bits into a signal using various line code waveforms. The existing line-code techniques have multiple kinds of issues, such as the utilization of bandwidth, connection synchronization (CS), the direct current (DC) component, and power spectrum density (PSD). These highlighted issues are not adequate in IoT devices in smart cities due to their small size. -
MC14SM5567 PCM Codec-Filter
Product Preview Freescale Semiconductor, Inc. MC14SM5567/D Rev. 0, 4/2002 MC14SM5567 PCM Codec-Filter The MC14SM5567 is a per channel PCM Codec-Filter, designed to operate in both synchronous and asynchronous applications. This device 20 performs the voice digitization and reconstruction as well as the band 1 limiting and smoothing required for (A-Law) PCM systems. DW SUFFIX This device has an input operational amplifier whose output is the input SOG PACKAGE CASE 751D to the encoder section. The encoder section immediately low-pass filters the analog signal with an RC filter to eliminate very-high-frequency noise from being modulated down to the pass band by the switched capacitor filter. From the active R-C filter, the analog signal is converted to a differential signal. From this point, all analog signal processing is done differentially. This allows processing of an analog signal that is twice the amplitude allowed by a single-ended design, which reduces the significance of noise to both the inverted and non-inverted signal paths. Another advantage of this differential design is that noise injected via the power supplies is a common mode signal that is cancelled when the inverted and non-inverted signals are recombined. This dramatically improves the power supply rejection ratio. After the differential converter, a differential switched capacitor filter band passes the analog signal from 200 Hz to 3400 Hz before the signal is digitized by the differential compressing A/D converter. The decoder accepts PCM data and expands it using a differential D/A converter. The output of the D/A is low-pass filtered at 3400 Hz and sinX/X compensated by a differential switched capacitor filter. -
Presentation on Digital Communication (ECE) III- B.TECH V- Semester (AUTONOMOUS-R16) Prepared By, Dr. S.Vinoth Mr. G.Kiran
Presentation on Digital communication (ECE) III- B.TECH V- Semester (AUTONOMOUS-R16) Prepared by, Dr. S.Vinoth Mr. G.Kiran Kumar (Associate Professor) (Assistant Professor) UNIT -I Pulse Digital Modulation 2 COMMUNICATION •The transmission of information from source to the destination through a channel or medium is called communication. •Basic block diagram of a communication system: 3 COMMUNICATION cont.. • Source: analog or digital • Transmitter: transducer, amplifier, modulator, oscillator, power amp., antenna • Channel: e.g. cable, optical fiber, free space • Receiver: antenna, amplifier, demodulator, oscillator, power amplifier, transducer • Destination : e.g. person, (loud) speaker, computer 4 Necessity of Digital communication • Good processing techniques are available for digital signals, such as medium. • Data compression (or source coding) • Error Correction (or channel coding)(A/D conversion) • Equalization • Security • Easy to mix signals and data using digital techniques 5 Necessity of Digitalization •In Analog communication, long distance communication suffers from many losses such as distortion, interference & security. •To overcome these problems, signals are digitalized. Information is transferred in the form of signal. 6 PULSE MODULATION In Pulse modulation, a periodic sequence of rectangular pulses, is used as a carrier wave. It is divided into analog and digital modulation. 7 Analog Pulse Modulation In Analog modulation , If the amplitude, duration or position of a pulse is varied in accordance with the instantaneous values of the baseband modulating signal, then such a technique is called as • Pulse Amplitude Modulation (PAM) or • Pulse Duration/Width Modulation (PDM/PWM), or • Pulse Position Modulation (PPM). 8 Digital modulation •In Digital Modulation, the modulation technique used is Pulse Code Modulation (PCM) where the analog signal is converted into digital form of 1s and 0s. -
Telecommunications Technology Transfers Contents
CHAPTER 6 Telecommunications Technology Transfers Contents Page INTRODUCTION . 185 TELECOMMUNICATIONS IN THE MIDDLE EAST . 186 Telecommunications Systems . 186 Manpower Requirements . 190 Telecommunications Systems in the Middle East. ........: . 191 Perspectives of Recipient Countries and Firms . 211 Perspectives of Supplier Countries and Firms . 227 IMPLICATIONS FOR U.S. POLICY . 236 CONCLUSIONS . 237 APPENDIX 6A. – TELECOMMUNICATIONS PROJECT PROFILES IN SELECTED MIDDLE EASTERN COUNTRIES. 238 Saudi Arabian Project Descriptions . 238 Egyptian Project Descriptions . 240 Algerian Project Description . 242 Iranian Project Description . 242 Tables Table No. Page 51. Market Shares of Telecommunications Equipment Exports to Saudi Arabia From OECD Countries, 1971, 1975-80 . 194 52. Selected Telecommunications Contracts in Saudi Arabia . 194 53. Market Shares of Telecommunications Equipment Exports to Kuwait From OECD Countries, 1971,1975-80 . 198 54. Selected Telecommunications Contracts in Kuwait . 198 55. Market Shares of Telecommunications Equipment Exports From OECD Countries, 1971, 1975-80 . 202 56. Market Shares of Telecommunications Equipment Exports to Algeria From OECD Countries, 1971,1975-80 . 204 57. Market Shares of Telecommunications Equipment Exports to Iraq From OECD Countries, 1971, 1975-80 . 206 58. Selected Telecommunications Contracts in Iraq . 206 59. Market Shares of Telecommunications Equipment Exports to Iran From OECD Countries, 1971, 1975-80 . 208 60. Saudi Arabian Telecommunications Budgets As Compared to Total Budgets . 212 61. U.S. Competitive Position in Telecommunications Markets in the Middle East Between 1974 and 1982 . 233 Figures Page l0. Apparent Telecommunications Sector Breakdowns-Saudi Arabia, 1974-82 . 195 11. Apparent Market Share, Saudi Arabia, 1974-82 . 196 12. Apparent Sector Breakdowns-Kuwait, 1974-82 . 197 13. Apparent Market Share-Kuwait, 1974-82 . -
4.1 DIGITAL-TO-DIGITAL CONVERSION in Chapter 3, We Discussed Data and Signals
A computer network is designed to send information from one point to another. This information needs to be converted to either a digital signal or an analog signal for trans• mission. In this chapter, we discuss the first choice, conversion to digital signals; in Chapter 5, we discuss the second choice, conversion to analog signals. We discussed the advantages and disadvantages of digital transmission over analog transmission in Chapter 3. In this chapter, we show the schemes and techniques that we use to transmit data digitally. First, we discuss digital-to-digital conversion tech• niques, methods which convert digital data to digital signals. Second, we discuss analog- to-digital conversion techniques, methods which change an analog signal to a digital signal. Finally, we discuss transmission modes. 4.1 DIGITAL-TO-DIGITAL CONVERSION In Chapter 3, we discussed data and signals. We said that data can be either digital or analog. We also said that signals that represent data can also be digital or analog. In this section, we see how we can represent digital data by using digital signals. The conver• sion involves three techniques: line coding, block coding, and scrambling. Line coding is always needed; block coding and scrambling may or may not be needed. Line Coding Line coding is the process of converting digital data to digital signals. We assume that data, in the form of text, numbers, graphical images, audio, or video, are stored in com• puter memory as sequences of bits (see Chapter 1). Line coding converts a sequence of bits to a digital signal. At the sender, digital data are encoded into a digital signal; at the receiver, the digital data are recreated by decoding the digital signal. -
2.1 Fundamentals of Data and Signals the Major Function of the Physical
2.1 Fundamentals of Data and Signals The major function of the physical layer is to move data in the form of electromagnetic signals across a transmission medium. Whether the data may be numerical statistics from another computer, sending animated pictures from a design workstation, or causing a bell to ring at a distant control center, you are working with the transmission of data across network connections. Analog and Digital Data Data can be analog or digital. The term analog data refers to information that is continuous, Digital data refers to information that has discrete states. For example, an analog clock that has hour, minute, and second hands gives information in a continuous form, the movements of the hands are continuous. On the other hand, a digital clock that reports the hours and the minutes will change suddenly from 8:05 to 8:06. Analog and Digital Signals: An analog signal has infinitely many levels of intensity over a period of time. As the wave moves from value A to value B, it passes through and includes an infinite number of values along its path. A digital signal, on the other hand, can have only a limited number of defined values. Although each value can be any number, it is often as simple as 1 and 0. The following program illustrates an analog signal and a digital signal. The curve representing the analog signal passes through an infinite number of points. The vertical lines of the digital signal, however, demonstrate the sudden jump that the signal makes from value to value. -
Design of Return to Zero (RZ) Bipolar Digital to Digital Encoding Data Transmission
IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org ISSN (e): 2250-3021, ISSN (p): 2278-8719 Vol. 05, Issue 02 (February. 2015), ||V4|| PP 33-36 Design of Return to Zero (RZ) Bipolar Digital to Digital Encoding Data Transmission Amna mohammed Elzain1,Abdelrasoul Jabar Alzubaidi2 Alazhery University- Engineering college Sudan University of Science and technology –Engineering College- Electronics Engineering School Abstract: - Line encoding is the method used to represent the digital information on the media. A pattern, that uses either voltage or current, is used to represent the 1s and 0s of the digital signal on the transmission link. Common types of line encoding methods used in data communications are: Unipolar line encoding, Polar line encoding, Bipolar line encoding and Manchester line encoding. This paper deals with the design of bipolar digital to digital encoding (RZ) data transmission using latch SN 74373, darlington amplifier ULN 2003-500 m A, solid state relay, personnel computer and Turbo C++ programming language ). Keywords: - Bipolar, Encoding, Digital to Digital, Latch SN 74373, Darlington Amplifier ULN 2003-500 m A, Solid State Relay (SSR) ,Turbo C++ , Computer. I. INTRODUCTION A computer network is used for communication of data from one station to another station in the network [1]. Data and signals are two of the basic building blocks of any computer network. Data must be encoded into signals before it can be transported across communication media [2]. Encoding means conversion of data into bit stream [3]. There are different encoding schemes available: Analog-to-Digital Digital-to-Analog Analog-to-Analog Digital-to-Digital Digital-to-Digital Digital-to-Digital encoding is the representation of digital information by a digital signal . -
Broadcasters Respond to the Challenges of HDTV and Digital Transmission
Emerging Trends: Broadcasters Respond to the Challenges of HDTV and Digital Transmission Communications Federal, state and local rules typically lag behind, sometimes far behind, new developments in technology. Such is the case with advancements in television broadcasting, such as High Definition Television (HDTV). Earlier Clifford M. Harrington this month, the National Association of Broadcasters unveiled two basic 202.663.8525 digital converter prototypes that will make it possible for the approximately [email protected] 20 million American consumers who don’t own or can’t afford to buy HDTV-compatible systems to still receive an HDTV signal when all network, cable and local stations switch over from analog to digital on February 17, 2009. These prototypes will be rolled out in electronics and department stores in January, at an expected cost of about $50 to $70. In the following Q&A, Clifford M. Harrington, who heads the Communications Practice at Pillsbury Winthrop Shaw Pittman, discusses how new federal laws enacted by the Federal Communications Commission (FCC) related to HDTV are affecting virtually every consumer, as well as redefining the television industry. Q: What’s happening in the world of television technology? Harrington: Anyone who walks into a consumer electronics showroom has seen the public face of HDTV: high resolution digital images on often enormous flat screens. But HDTV is just one benefit of the new digital transmission system that is being adopted by the American television industry. Digital television will also permit multicasting—the simultaneous broadcast by a single station of several Standard Definition program streams of equal or better quality than current television signals. -
M-Ary Aggregate Spread Pulse Modulation in Lpwans for Iot Applications
M-ary Aggregate Spread Pulse Modulation in LPWANs for IoT applications Alexei V. Nikitin Ruslan L. Davidchack Nonlinear LLC Sch. of Mathematics and Actuarial Sci., Wamego, Kansas, USA U. of Leicester, Leicester, UK E-mail: [email protected] E-mail: [email protected] Abstract—In low-power wide-area networks (LPWANs), various However, the designed pulse train Gˆ»:¼ given by (1) can be trade-offs among the bandwidth, data rates, and energy per bit “re-shaped” by linear filtering: have different effects on the quality of service under different ∑︁ propagation conditions (e.g. fading and multipath), interference G »:¼ = ¹Gˆ ∗ 6ˆº»:¼ = 퐴9 6ˆ»: −:9 ¼ , (3) scenarios, multi-user requirements, and design constraints. Such 9 compromises, and the manner in which they are implemented, fur- where 6ˆ»:¼ is the impulse response of the filter and the asterisk ther affect other technical aspects, such as system’s computational denotes convolution. The filter 6ˆ»:¼ can be, for example, a complexity and power efficiency. At the same time, this difference lowpass filter with a given bandwidth 퐵. If the filter 6ˆ»:¼ has a in trade-offs also adds to the technical flexibility in addressing a broader range of IoT applications. This paper addresses a sufficiently large time-bandwidth product (TBP) [4], [5], most of physical layer LPWAN approach based on the Aggregate Spread the samples in the reshaped train G »:¼ will have non-zero values, Pulse Modulation (ASPM) and provides a brief assessment of its and G »:¼ will have a much smaller PAPR than the designed properties in additive white Gaussian noise (AWGN) channel. -
Digital Transmission of Analog Signals
The Communications Edge™ Tech-note Author: John F. Delozier Digital Transmission of Analog Signals The digital transmission of analog information ment that is similar to the improvement is an old idea which has always had a certain V found when wideband FM systems are com- amount of appeal to telecommunication sys- τ pared to AM systems. (a) tem designers. If a minimum level of signal- T to-noise ratio is maintained, then it is possible DIGITAL PULSE MODULATION to operate a digital transmission system (b) Pulse code modulation (PCM) and delta almost error free. modulation (DM) are the major digital pulse It is the intent of this article to provide a brief formats. Digital pulse modulation is charac- tutorial on digital telecommunications for terized by the representation of the informa- personnel not already familiar with this sub- (c) tion signal as a discrete value in a finite set of ject. As background material, some modula- values. Pulse code modulation begins with a tion and multiplexing techniques will be cov- sampled information signal (PAM) whose sample amplitudes are quantized and encoded ered initially. The focus of the article will be a (d) UNMODULATED presentation of the two major telecommuni- PULSES into a finite number of bits or into an n-bit cation hierarchies found in today’s networks word. The implementation of PCM is more complicated than analog pulse modulation and then digital transmission via microwave (e) formats, but PCM’s transmission and regener- modulation techniques will be briefly covered. Figure 1. Pulse modulation format. The carrier pulse train ation capabilities are more attractive. -
Optical Modulation for High Bit Rate Transport Technologies by Ildefonso M
Technology Note Optical Modulation for High Bit Rate Transport Technologies By Ildefonso M. Polo I October, 2009 Scope There are plenty of highly technical and extremely mathematical articles published about optical modulation formats, showing complex formulas, spectral diagrams and almost unreadable eye diagrams, which can be considered normal for every emerging technology. The main purpose of this article is to demystify optical modulation in a way that the rest of us can visualize and understand them. Nevertheless, some of these modulations are so complex that they can’t be properly represented in a simple time domain graph, so polar (constellation) or spherical coordinates are often used to represent the different states of the signal. Within this document some of these polar diagrams have been enhanced with the state diagram (blue) to indicate the possible transitions and logic. Introduction Back in the early ‘90s, copper lines moved from digital baseband line coding (e.g. 2B1Q, 4B3T, AMI, and HDB3, among others) to complex modulation schemes to increase speed, reach, and reliability. We were all skeptical that a technology like DSL would have been able to transmit 256 simultaneous QAM16 signals and achieve 8 Mbit/s. Today copper is already reaching the 155 Mbit/s mark. This is certainly a full circle. We moved from analog to digital transmission to increase data rates and reliability, and then we resorted to analog signals (through modulation) to carry digital information farther, faster and more reliably. Back then, 155 Mbit/s were only thought of for fiber optics transmission. It is also interesting to note that only a few years ago we seemed to be under the impression that ‘fiber optics offered an almost infinite amount of bandwidth’ or more than we would ever need.