Signal Modulation Schemes
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Properties of Angle Modulation
Properties of Angle Modulation Properties of Angle Modulation Reference: Sections 4.2 and 4.3 of Professor Deepa Kundur S. Haykin and M. Moher, Introduction to Analog & Digital University of Toronto Communications, 2nd ed., John Wiley & Sons, Inc., 2007. ISBN-13 978-0-471-43222-7. Professor Deepa Kundur (University of Toronto) Properties of Angle Modulation 1 / 25 Professor Deepa Kundur (University of Toronto) Properties of Angle Modulation 2 / 25 Angle Modulation carrier I Phase Modulation (PM): θi (t) = 2πfc t + kpm(t) 1 dθ (t) k dm(t) f (t) = i = f + p message i 2π dt c 2π dt sPM (t) = Ac cos[2πfc t + kpm(t)] amplitude modulation I Frequency Modulation (FM): Z t θi (t) = 2πfc t + 2πkf m(τ)dτ 0 phase 1 dθ (t) modulation f (t) = i = f + k m(t) i 2π dt c f Z t sFM (t) = Ac cos 2πfc t + 2πkf m(τ)dτ 0 frequency modulation Professor Deepa Kundur (University of Toronto) Properties of Angle Modulation 3 / 25 Professor Deepa Kundur (University of Toronto) Properties of Angle Modulation 4 / 25 carrier carrier message message amplitude amplitude modulation modulation phase phase modulation modulation frequency frequency modulation modulation Professor Deepa Kundur (University of Toronto) Properties of Angle Modulation 5 / 25 Professor Deepa Kundur (University of Toronto) Properties of Angle Modulation 6 / 25 4.2 Properties of Angle Modulation 4.2 Properties of Angle Modulation Constancy of Transmitted Power Constancy of Transmitted Power: AM 1 I Consider a sinusoid g(t) = Ac cos(2πf0t + φ) where T0 = or T0f0 =1. f0 I The power of g(t) (over a 1 ohm resister) is defined as: Z T0=2 Z T0=2 1 2 1 2 2 P = g (t)dt = Ac cos (2πf0t + φ)dt T0 −T0=2 T0 −T0=2 2 Z T0=2 Ac 1 = [1 + cos(4πf0t + 2φ)] dt T0 −T0=2 2 2 T0=2 Ac sin(4πf0t + 2φ) = t + 2T 4f 0 0 −T0=2 A2 T −T sin(4πf T =2 + 2φ) − sin(−4πf T =2 + 2φ) = c 0 − 0 + 0 0 0 0 2T0 2 2 4πf0 2 2 Ac sin(2π + 2φ) − sin(−2π + 2φ) Ac = T0 + = 2T0 4πf0 2 I Therefore, the power of a sinusoid is NOT dependent on f0, just its envelop Ac . -
Discrete Cosine Transform Based Image Fusion Techniques VPS Naidu MSDF Lab, FMCD, National Aerospace Laboratories, Bangalore, INDIA E.Mail: [email protected]
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by NAL-IR Journal of Communication, Navigation and Signal Processing (January 2012) Vol. 1, No. 1, pp. 35-45 Discrete Cosine Transform based Image Fusion Techniques VPS Naidu MSDF Lab, FMCD, National Aerospace Laboratories, Bangalore, INDIA E.mail: [email protected] Abstract: Six different types of image fusion algorithms based on 1 discrete cosine transform (DCT) were developed and their , k 1 0 performance was evaluated. Fusion performance is not good while N Where (k ) 1 and using the algorithms with block size less than 8x8 and also the block 1 2 size equivalent to the image size itself. DCTe and DCTmx based , 1 k 1 N 1 1 image fusion algorithms performed well. These algorithms are very N 1 simple and might be suitable for real time applications. 1 , k 0 Keywords: DCT, Contrast measure, Image fusion 2 N 2 (k 1 ) I. INTRODUCTION 2 , 1 k 2 N 2 1 Off late, different image fusion algorithms have been developed N 2 to merge the multiple images into a single image that contain all useful information. Pixel averaging of the source images k 1 & k 2 discrete frequency variables (n1 , n 2 ) pixel index (the images to be fused) is the simplest image fusion technique and it often produces undesirable side effects in the fused image Similarly, the 2D inverse discrete cosine transform is defined including reduced contrast. To overcome this side effects many as: researchers have developed multi resolution [1-3], multi scale [4,5] and statistical signal processing [6,7] based image fusion x(n1 , n 2 ) (k 1 ) (k 2 ) N 1 N 1 techniques. -
Digital Signals
Technical Information Digital Signals 1 1 bit t Part 1 Fundamentals Technical Information Part 1: Fundamentals Part 2: Self-operated Regulators Part 3: Control Valves Part 4: Communication Part 5: Building Automation Part 6: Process Automation Should you have any further questions or suggestions, please do not hesitate to contact us: SAMSON AG Phone (+49 69) 4 00 94 67 V74 / Schulung Telefax (+49 69) 4 00 97 16 Weismüllerstraße 3 E-Mail: [email protected] D-60314 Frankfurt Internet: http://www.samson.de Part 1 ⋅ L150EN Digital Signals Range of values and discretization . 5 Bits and bytes in hexadecimal notation. 7 Digital encoding of information. 8 Advantages of digital signal processing . 10 High interference immunity. 10 Short-time and permanent storage . 11 Flexible processing . 11 Various transmission options . 11 Transmission of digital signals . 12 Bit-parallel transmission. 12 Bit-serial transmission . 12 Appendix A1: Additional Literature. 14 99/12 ⋅ SAMSON AG CONTENTS 3 Fundamentals ⋅ Digital Signals V74/ DKE ⋅ SAMSON AG 4 Part 1 ⋅ L150EN Digital Signals In electronic signal and information processing and transmission, digital technology is increasingly being used because, in various applications, digi- tal signal transmission has many advantages over analog signal transmis- sion. Numerous and very successful applications of digital technology include the continuously growing number of PCs, the communication net- work ISDN as well as the increasing use of digital control stations (Direct Di- gital Control: DDC). Unlike analog technology which uses continuous signals, digital technology continuous or encodes the information into discrete signal states (Fig. 1). When only two discrete signals states are assigned per digital signal, these signals are termed binary si- gnals. -
Digital Television Systems
This page intentionally left blank Digital Television Systems Digital television is a multibillion-dollar industry with commercial systems now being deployed worldwide. In this concise yet detailed guide, you will learn about the standards that apply to fixed-line and mobile digital television, as well as the underlying principles involved, such as signal analysis, modulation techniques, and source and channel coding. The digital television standards, including the MPEG family, ATSC, DVB, ISDTV, DTMB, and ISDB, are presented toaid understanding ofnew systems in the market and reveal the variations between different systems used throughout the world. Discussions of source and channel coding then provide the essential knowledge needed for designing reliable new systems.Throughout the book the theory is supported by over 200 figures and tables, whilst an extensive glossary defines practical terminology.Additional background features, including Fourier analysis, probability and stochastic processes, tables of Fourier and Hilbert transforms, and radiofrequency tables, are presented in the book’s useful appendices. This is an ideal reference for practitioners in the field of digital television. It will alsoappeal tograduate students and researchers in electrical engineering and computer science, and can be used as a textbook for graduate courses on digital television systems. Marcelo S. Alencar is Chair Professor in the Department of Electrical Engineering, Federal University of Campina Grande, Brazil. With over 29 years of teaching and research experience, he has published eight technical books and more than 200 scientific papers. He is Founder and President of the Institute for Advanced Studies in Communications (Iecom) and has consulted for several companies and R&D agencies. -
How I Came up with the Discrete Cosine Transform Nasir Ahmed Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, New Mexico 87131
mxT*L. BImL4L. PRocEsSlNG 1,4-5 (1991) How I Came Up with the Discrete Cosine Transform Nasir Ahmed Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, New Mexico 87131 During the late sixties and early seventies, there to study a “cosine transform” using Chebyshev poly- was a great deal of research activity related to digital nomials of the form orthogonal transforms and their use for image data compression. As such, there were a large number of T,(m) = (l/N)‘/“, m = 1, 2, . , N transforms being introduced with claims of better per- formance relative to others transforms. Such compari- em- lh) h = 1 2 N T,(m) = (2/N)‘%os 2N t ,...) . sons were typically made on a qualitative basis, by viewing a set of “standard” images that had been sub- jected to data compression using transform coding The motivation for looking into such “cosine func- techniques. At the same time, a number of researchers tions” was that they closely resembled KLT basis were doing some excellent work on making compari- functions for a range of values of the correlation coef- sons on a quantitative basis. In particular, researchers ficient p (in the covariance matrix). Further, this at the University of Southern California’s Image Pro- range of values for p was relevant to image data per- cessing Institute (Bill Pratt, Harry Andrews, Ali Ha- taining to a variety of applications. bibi, and others) and the University of California at Much to my disappointment, NSF did not fund the Los Angeles (Judea Pearl) played a key role. -
Reception Performance Improvement of AM/FM Tuner by Digital Signal Processing Technology
Reception performance improvement of AM/FM tuner by digital signal processing technology Akira Hatakeyama Osamu Keishima Kiyotaka Nakagawa Yoshiaki Inoue Takehiro Sakai Hirokazu Matsunaga Abstract With developments in digital technology, CDs, MDs, DVDs, HDDs and digital media have become the mainstream of car AV products. In terms of broadcasting media, various types of digital broadcasting have begun in countries all over the world. Thus, there is a demand for smaller and thinner products, in order to enhance radio performance and to achieve consolidation with the above-mentioned digital media in limited space. Due to these circumstances, we are attaining such performance enhancement through digital signal processing for AM/FM IF and beyond, and both tuner miniaturization and lighter products have been realized. The digital signal processing tuner which we will introduce was developed with Freescale Semiconductor, Inc. for the 2005 line model. In this paper, we explain regarding the function outline, characteristics, and main tech- nology involved. 22 Reception performance improvement of AM/FM tuner by digital signal processing technology Introduction1. Introduction from IF signals, interference and noise prevention perfor- 1 mance have surpassed those of analog systems. In recent years, CDs, MDs, DVDs, and digital media have become the mainstream in the car AV market. 2.2 Goals of digitalization In terms of broadcast media, with terrestrial digital The following items were the goals in the develop- TV and audio broadcasting, and satellite broadcasting ment of this digital processing platform for radio: having begun in Japan, while overseas DAB (digital audio ①Improvements in performance (differentiation with broadcasting) is used mainly in Europe and SDARS (satel- other companies through software algorithms) lite digital audio radio service) and IBOC (in band on ・Reduction in noise (improvements in AM/FM noise channel) are used in the United States, digital broadcast- reduction performance, and FM multi-pass perfor- ing is expected to increase in the future. -
Next-Generation Photonic Transport Network Using Digital Signal Processing
Next-Generation Photonic Transport Network Using Digital Signal Processing Yasuhiko Aoki Hisao Nakashima Shoichiro Oda Paparao Palacharla Coherent optical-fiber transmission technology using digital signal processing is being actively researched and developed for use in transmitting high-speed signals of the 100-Gb/s class over long distances. It is expected that network capacity can be further expanded by operating a flexible photonic network having high spectral efficiency achieved by applying an optimal modulation format and signal processing algorithm depending on the transmission distance and required bit rate between transmit and receive nodes. A system that uses such adaptive modulation technology should be able to assign in real time a transmission path between a transmitter and receiver. Furthermore, in the research and development stage, optical transmission characteristics for each modulation format and signal processing algorithm to be used by the system should be evaluated under emulated quasi-field conditions. We first discuss how the use of transmitters and receivers supporting multiple modulation formats can affect network capacity. We then introduce an evaluation platform consisting of a coherent receiver based on a field programmable gate array (FPGA) and polarization mode dispersion/polarization dependent loss (PMD/PDL) emulators with a recirculating-loop experimental system. Finally, we report the results of using this platform to evaluate the transmission characteristics of 112-Gb/s dual-polarization, quadrature phase shift keying (DP-QPSK) signals by emulating the factors that degrade signal transmission in a real environment. 1. Introduction amplifiers—which is becoming a limiting factor In the field of optical communications in system capacity—can be efficiently used. -
CE-OFDM Thesis
Design and Implementation of a Constant Envelope OFDM Waveform in a Software Defined Radio Platform Amos Vershima Ajo Jr. Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering Carl B. Dietrich, Chair A. A. (Louis) Beex, Chair Allen B. MacKenzie May 5, 2016 Blacksburg, Virginia Keywords: OFDM, Constant Envelope OFDM, Peak-to-Average Power Ratio, Software Defined Radio, GNU Radio Design and Implementation of a Constant Envelope OFDM Waveform in a Software Defined Radio Platform Amos Vershima Ajo Jr. ABSTRACT This thesis examines the high peak-to-average-power ratio (PAPR) problem of OFDM and other spectrally-efficient multicarrier modulation schemes, specifically their stringent requirements for highly linear, power-inefficient amplification. The thesis then presents a most intriguing answer to the PAPR-problem in the form of a constant-envelope OFDM (CE-OFDM) waveform, a waveform which employs phase modulation to transform the high-PAPR OFDM signal into a constant envelope signal, like FSK or GMSK, which can be amplified with non-linear power amplifiers at near saturation levels of efficiency. A brief analytical description of CE-OFDM and its suboptimal receiver architecture is provided in order to define and analyze the key parameters of the waveform and their performance impacts. The primary contribution of this thesis is a highly tunable software-defined radio (SDR) implementation of the waveform which enables rapid-prototyping and testing of CE-OFDM systems. The digital baseband processing of the waveform is executed on a general purpose processor (GPP) in the Ubuntu 14.04 Linux operating system, and programmed using the GNU Radio SDR software framework with a mixture of Python and C++ routines. -
Chapter 1 Computers and Digital Basics Computer Concepts 2014 1 Your Assignment…
Chapter 1 Computers and Digital Basics Computer Concepts 2014 1 Your assignment… Prepare an answer for your assigned question. Use Chapter 1 in the book and this PowerPoint to procure information. Prepare a PowerPoint presentation to: 1. Show your answer and additional information/facts – make sure you understand and can explain your answer. Provide as must information and detail as possible. Add graphics to enhance. 2. Where in the book did you find your information? Include the page number. 3. What more do you need to find out to help you better understand this question? Be prepared to share your information with the class. Chapter 1: Computers and Digital Basics 2 1 The Digital Revolution The digital revolution is an ongoing process of social, political, and economic change brought about by digital technology, such as computers and the Internet The technology driving the digital revolution is based on digital electronics and the idea that electrical signals can represent data, such as numbers, words, pictures, and music Chapter 1: Computers and Digital Basics 6 1 The Digital Revolution Digitization is the process of converting text, numbers, sound, photos, and video into data that can be processed by digital devices The digital revolution has evolved through four phases, beginning with big, expensive, standalone computers, and progressing to today’s digital world in which small, inexpensive digital devices are everywhere Chapter 1: Computers and Digital Basics 7 1 The Digital Revolution Chapter 1: Computers and Digital Basics -
Analog Output Signal the Signal Saturation Can Be Controlled by Setting the Respective ▪ Introduction AO-LL and the AO-UL
FieldGuide Enhance Operations Analog Output Signal The Signal Saturation can be controlled by setting the respective ▪ Introduction AO-LL and the AO-UL. The AO-LL and the AO-UL are programmable Yokogawa’s pressure transmitters with BRAIN or HART within the parameter limits of the transmitter via the FieldMate. communication have a 4 to 20 mA analog signal corresponding to the Primary Variable (PV). This output signal is generated from the digital signal supplied by the DPHarp sensor using a 15BitD/A signal converter with 0.004% resolution. The transmitters are designed to drive output slightly greater than the 4 to 20 mA “Base” signal. The intention is to set analog alarm thresholds recognizably beyond the normal operating 4 to 20 mA range, to indicate measurement our of range, and to set further alarm thresholds to indicate a fault condition. ▪ Applicable Models > EJA-E Series: All models with either BRAIN or HART communication > EJX-A Series: All models with either BRAIN or HART communication ▪ Process Measurement Out-of-Range Standard Analog Output Signal Yokogawa’s standard analog output transmitters are factory set to an Analog Output– Lower Limit (AO-LL) and Analog Output-Upper Limit The AO-LL and the AO-UL can be set to any value between 3.6 mA to (AO-UL) of 3.6 mA and 21.6 mA respectively. This allows for a small 21.6 mA. amount of linear over-range process readings. This over-range signal is referred to as Signal Saturation. During operation, if the AO-LL or Although FieldMate is highlighted here, any Hart Communicator has AO-UL limits are reached, the analog signal locks to the respective access to these functions. -
Lecture Notes for Digital Electronics
Lecture Notes for Digital Electronics Raymond E. Frey Physics Department University of Oregon Eugene, OR 97403, USA [email protected] March, 2000 1 Basic Digital Concepts By converting continuous analog signals into a finite number of discrete states, a process called digitization, then to the extent that the states are sufficiently well separated so that noise does create errors, the resulting digital signals allow the following (slightly idealized): • storage over arbitrary periods of time • flawless retrieval and reproduction of the stored information • flawless transmission of the information Some information is intrinsically digital, so it is natural to process and manipulate it using purely digital techniques. Examples are numbers and words. The drawback to digitization is that a single analog signal (e.g. a voltage which is a function of time, like a stereo signal) needs many discrete states, or bits, in order to give a satisfactory reproduction. For example, it requires a minimum of 10 bits to determine a voltage at any given time to an accuracy of ≈ 0:1%. For transmission, one now requires 10 lines instead of the one original analog line. The explosion in digital techniques and technology has been made possible by the incred- ible increase in the density of digital circuitry, its robust performance, its relatively low cost, and its speed. The requirement of using many bits in reproduction is no longer an issue: The more the better. This circuitry is based upon the transistor, which can be operated as a switch with two states. Hence, the digital information is intrinsically binary. So in practice, the terms digital and binary are used interchangeably. -
Angle Modulation
ANGLE MODULATION [email protected] Source : SIGA2800 Basic SIGINT Technology Objectives 1. Identify which modulations are also known as angle modulations. 2. Given a maximum modulating frequency and either a frequency of deviation or deviation ratio of a frequency modulated signal, determine signal bandwidth as given by Carson's rule. Objectives 3. Given a bandwidth and either a maximum frequency deviation or deviation ratio, calculate the maximum modulating frequency that will comply with Carson's rule. Objectives 4. Given a carrier being frequency modulated by a sine wave at a fixed deviation ratio, calculate: a. Average signal power b. Bandwidth in accordance with Carson's rule. c. Signal power present at the carrier frequency, any frequency harmonic, and at a frequency equal to the frequency deviation. Objectives 5. For angle modulated signals, identify what factors drive overall power in the signal. 6. State what factors affect the bandwidth of signals modulated using angle modulation. Sinewave Characteristics Phase Period Time 1 Frequency Period A sinusoid has three properties . These are its amplitude, period (or frequency), and phase. Types of Modulation Amplitude Modulation Phase Modulation Asin(t ) Asin(t ) Frequency Modulation With very few exceptions, phase modulation is used for digital information. Asin(t ) Types of Modulation Types of Information Carrier • Analog Variations Amplitude • Digital Frequency These two Phase constitute angle modulation. (Objective #1) WHAT IS ANGLE MODULATION? Angle modulation is a variation of one of these two parameters. UNDERSTANDING PHASE VS. FREQUENCY To understand the difference between phase and frequency, V a signal can be thought of phase using a phasor diagram.