Experiment # 4 Quadrature Amplitude Modulation (QAM)
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Loudspeaker FM and AM Distortion an 10
Loudspeaker FM and AM Distortion AN 10 Application Note to the KLIPPEL R&D SYSTEM The amplitude modulation of a high frequency tone f1 (voice tone) and a low frequency tone f2 (bass tone) is measured by using the 3D Distortion Measurement module (DIS) of the KLIPPEL R&D SYSTEM. The maximal variation of the envelope of the voice tone f1 is represented by the top and bottom value referred to the averaged envelope. The amplitude modulation distortion (AMD) is the ratio between the rms value of the variation referred to the averaged value and is comparable to the modulation distortion Ld2 and Ld3 of the IEC standard 60268 provided that the loudspeaker generates pure amplitude modulation of second- or third-order. The measurement of amplitude modulation distortion (AMD) allows assessment of the effects of Bl(x) and Le(x) nonlinearity and radiation distortion due to pure amplitude modulation without Doppler effect. CONTENTS: 1 Method of Measurement ............................................................................................................................... 2 2 Checklist for dominant modulation distortion ............................................................................................... 3 3 Using the 3D distortion measurement (DIS) .................................................................................................. 4 4 Setup parameters for DIS Module .................................................................................................................. 4 5 Example ......................................................................................................................................................... -
Degree Project
Degree project Performance of MLSE over Fading Channels Author: Aftab Ahmad Date: 2013-05-31 Subject: Electrical Engineering Level: Master Level Course code: 5ED06E To my parents, family, siblings, friends and teachers 1 Research is what I'm doing when I don't know what I'm doing1 Wernher Von Braun 1Brown, James Dean, and Theodore S. Rodgers. Doing Second Language Research: An introduction to the theory and practice of second language research for graduate/Master's students in TESOL and Applied Linguistics, and others. OUP Oxford, 2002. 2 Abstract This work examines the performance of a wireless transceiver system. The environment is indoor channel simulated by Rayleigh and Rician fading channels. The modulation scheme implemented is GMSK in the transmitter. In the receiver the Viterbi MLSE is implemented to cancel noise and interference due to the filtering and the channel. The BER against the SNR is analyzed in this thesis. The waterfall curves are compared for two data rates of 1 M bps and 2 Mbps over both the Rayleigh and Rician fading channels. 3 Acknowledgments I would like to thank Prof. Sven Nordebo for his supervision, valuable time and advices and support during this thesis work. I would like to thank Prof. Sven-Eric Sandstr¨om.Iwould also like to thank Sweden and Denmark for giving me an opportunity to study in this education system and experience the Scandinavian life and culture. I must mention my gratitude to Sohail Atif, javvad ur Rehman, Ahmed Zeeshan and all the rest of my buddies that helped me when i most needed it. -
Bit & Baud Rate
What’s The Difference Between Bit Rate And Baud Rate? Apr. 27, 2012 Lou Frenzel | Electronic Design Serial-data speed is usually stated in terms of bit rate. However, another oft- quoted measure of speed is baud rate. Though the two aren’t the same, similarities exist under some circumstances. This tutorial will make the difference clear. Table Of Contents Background Bit Rate Overhead Baud Rate Multilevel Modulation Why Multiple Bits Per Baud? Baud Rate Examples References Background Most data communications over networks occurs via serial-data transmission. Data bits transmit one at a time over some communications channel, such as a cable or a wireless path. Figure 1 typifies the digital-bit pattern from a computer or some other digital circuit. This data signal is often called the baseband signal. The data switches between two voltage levels, such as +3 V for a binary 1 and +0.2 V for a binary 0. Other binary levels are also used. In the non-return-to-zero (NRZ) format (Fig. 1, again), the signal never goes to zero as like that of return- to-zero (RZ) formatted signals. 1. Non-return to zero (NRZ) is the most common binary data format. Data rate is indicated in bits per second (bits/s). Bit Rate The speed of the data is expressed in bits per second (bits/s or bps). The data rate R is a function of the duration of the bit or bit time (TB) (Fig. 1, again): R = 1/TB Rate is also called channel capacity C. If the bit time is 10 ns, the data rate equals: R = 1/10 x 10–9 = 100 million bits/s This is usually expressed as 100 Mbits/s. -
Application of 4K-QAM, LDPC and OFDM for Gbps Data Rates Over HFC Plant David John Urban Comcast
Application of 4K-QAM, LDPC and OFDM for Gbps Data Rates over HFC Plant David John Urban Comcast Abstract Higher spectral density requires mapping more bits into a symbol at the expense of a This paper describes the application of higher signal to noise ratio (SNR) threshold. 4096-QAM, low density parity check codes The new physical layer will map 12 bits per (LDPC), and orthogonal frequency division symbol on the downstream compared to the 8 multiplexing (OFDM) to transmission over a bits per symbol used in DOCSIS 3.0. 4K- hybrid fiber coaxial cable plant (HFC). These QAM (or 4096-QAM) is a modulation techniques enable data rates of several Gbps. technique that has 4,096 points in the constellation diagram and each point is A complete derivation of the equations mapped to 12 bits. The new physical layer used for log domain sum product LDPC will map 10 bits per symbol using 1024-QAM decoding is provided. The reasons for (or 1K-QAM) on the upstream compared to 6 selecting OFDM and 4K-QAM are described. bits per symbol with 64-QAM used in Analysis of performance in the presence of DOCSIS 3.0. noise taken from field measurements is made. INCREASING SPECTRAL EFFICIENCY INTRODUCTION The three key methods for increasing the A new physical layer is being developed for spectral efficiency of the HFC plant in the transmission of data over a HFC cable plant. new physical layer are LDPC, OFDM and The objective is to increase the HFC plant 4K-QAM. LDPC is a very efficient coding capacity. -
Lecture 25 Demodulation and the Superheterodyne Receiver EE445-10
EE447 Lecture 6 Lecture 25 Demodulation and the Superheterodyne Receiver EE445-10 HW7;5-4,5-7,5-13a-d,5-23,5-31 Due next Monday, 29th 1 Figure 4–29 Superheterodyne receiver. m(t) 2 Couch, Digital and Analog Communication Systems, Seventh Edition ©2007 Pearson Education, Inc. All rights reserved. 0-13-142492-0 1 EE447 Lecture 6 Synchronous Demodulation s(t) LPF m(t) 2Cos(2πfct) •Only method for DSB-SC, USB-SC, LSB-SC •AM with carrier •Envelope Detection – Input SNR >~10 dB required •Synchronous Detection – (no threshold effect) •Note the 2 on the LO normalizes the output amplitude 3 Figure 4–24 PLL used for coherent detection of AM. 4 Couch, Digital and Analog Communication Systems, Seventh Edition ©2007 Pearson Education, Inc. All rights reserved. 0-13-142492-0 2 EE447 Lecture 6 Envelope Detector C • Ac • (1+ a • m(t)) Where C is a constant C • Ac • a • m(t)) 5 Envelope Detector Distortion Hi Frequency m(t) Slope overload IF Frequency Present in Output signal 6 3 EE447 Lecture 6 Superheterodyne Receiver EE445-09 7 8 4 EE447 Lecture 6 9 Super-Heterodyne AM Receiver 10 5 EE447 Lecture 6 Super-Heterodyne AM Receiver 11 RF Filter • Provides Image Rejection fimage=fLO+fif • Reduces amplitude of interfering signals far from the carrier frequency • Reduces the amount of LO signal that radiates from the Antenna stop 2/22 12 6 EE447 Lecture 6 Figure 4–30 Spectra of signals and transfer function of an RF amplifier in a superheterodyne receiver. 13 Couch, Digital and Analog Communication Systems, Seventh Edition ©2007 Pearson Education, Inc. -
A Measurement Instrument for Fault Diagnosis in Qam-Based Telecommunications
12th IMEKO TC4 International Symposium Electrical Measurements and Instrumentation September 25−27, 2002, Zagreb, Croatia A MEASUREMENT INSTRUMENT FOR FAULT DIAGNOSIS IN QAM-BASED TELECOMMUNICATIONS Pasquale Arpaia(1), Luca De Vito(1,2), Sergio Rapuano(1), Gioacchino Truglia(1,2) (1) Dipartimento di Ingegneria, Università del Sannio, piazza Roma, Benevento, Italy (2) Telsey Telecommunications, viale Mellusi 68, Benevento, Italy Abstract − A method for diagnosing faults in Some techniques for classifying automatically the main communication systems based on QAM (Quadrature faults on QAM modulation via the constellation diagram Amplitude Modulation) modulation scheme is proposed. were proposed. The approach followed in [4] is based on a The most relevant faults affecting this modulation have been Wavelet Network (WN). This method provides very good observed and modelled. Such faults, individually and results on simulated and actual signals. combined, are classified and estimated by analysing the Another method classifies the faults through an image- statistical moments of the received symbols. Simulation and processing approach [5]. The constellation diagram is experimental results of characterisation and validation digitised, then the obtained image is compared with some highlight the practical effectiveness of the proposed method. fault models, by using a correlation method, and a similarity score is provided. Keywords: Fault diagnosis, telecommunication, testing, However, both the WN- and the image processing-based QAM. methods can recognize and eventually measure only the dominating fault, and can not recognize the simultaneous 1. INTRODUCTION presence of several faults. In this paper, a diagnostics method, based on analytical Quadrature Amplitude Modulation (QAM) is an estimation of the statistical moments of the received symbol attractive method for transmitting two data streams in distribution, is proposed for QAM-modulation. -
Statistical Distortion: Consequences of Data Cleaning
Statistical Distortion: Consequences of Data Cleaning Tamraparni Dasu Ji Meng Loh AT&T Labs Research AT&T Labs Research 180 Park Avenue 180 Park Avenue Florham Park, NJ 07932 Florham Park, NJ 07932 [email protected] [email protected] ABSTRACT There is considerable research in the database community We introduce the notion of statistical distortion as an essen- on varied aspects of data quality, data repair and data clean- tial metric for measuring the effectiveness of data cleaning ing. Recent work includes the use of machine learning for strategies. We use this metric to propose a widely applica- guiding database repair [14]; inferring and imputing miss- ble yet scalable experimental framework for evaluating data ing values in databases [10] ; resolving inconsistencies using cleaning strategies along three dimensions: glitch improve- functional dependencies [6]; and for data fusion [8]. ment, statistical distortion and cost-related criteria. Exist- From an enterprise perspective, data and information qual- ing metrics focus on glitch improvement and cost, but not ity assessment has been an active area of research as well. on the statistical impact of data cleaning strategies. We The paper [12] describes subjective and objective measures illustrate our framework on real world data, with a compre- for assessing the quality of a corporation’s data. An overview hensive suite of experiments and analyses. of well known data quality techniques and their comparative uses and benefits is provided in [2]. A DIMACS/CICCADA 1 workshop on data quality metrics featured a mix of speak- 1. INTRODUCTION ers from database and statistics communities. It covered a Measuring effectiveness of data cleaning strategies is al- wide array of topics from schema mapping, graphs, detailed most as difficult as devising cleaning strategies. -
En 300 720 V2.1.0 (2015-12)
Draft ETSI EN 300 720 V2.1.0 (2015-12) HARMONISED EUROPEAN STANDARD Ultra-High Frequency (UHF) on-board vessels communications systems and equipment; Harmonised Standard covering the essential requirements of article 3.2 of the Directive 2014/53/EU 2 Draft ETSI EN 300 720 V2.1.0 (2015-12) Reference REN/ERM-TG26-136 Keywords Harmonised Standard, maritime, radio, UHF ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cedex - FRANCE Tel.: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16 Siret N° 348 623 562 00017 - NAF 742 C Association à but non lucratif enregistrée à la Sous-Préfecture de Grasse (06) N° 7803/88 Important notice The present document can be downloaded from: http://www.etsi.org/standards-search The present document may be made available in electronic versions and/or in print. The content of any electronic and/or print versions of the present document shall not be modified without the prior written authorization of ETSI. In case of any existing or perceived difference in contents between such versions and/or in print, the only prevailing document is the print of the Portable Document Format (PDF) version kept on a specific network drive within ETSI Secretariat. Users of the present document should be aware that the document may be subject to revision or change of status. Information on the current status of this and other ETSI documents is available at http://portal.etsi.org/tb/status/status.asp If you find errors in the present document, please send your comment to one of the following services: https://portal.etsi.org/People/CommiteeSupportStaff.aspx Copyright Notification No part may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm except as authorized by written permission of ETSI. -
Of Single Sideband Demodulation by Richard Lyons
Understanding the 'Phasing Method' of Single Sideband Demodulation by Richard Lyons There are four ways to demodulate a transmitted single sideband (SSB) signal. Those four methods are: • synchronous detection, • phasing method, • Weaver method, and • filtering method. Here we review synchronous detection in preparation for explaining, in detail, how the phasing method works. This blog contains lots of preliminary information, so if you're already familiar with SSB signals you might want to scroll down to the 'SSB DEMODULATION BY SYNCHRONOUS DETECTION' section. BACKGROUND I was recently involved in trying to understand the operation of a discrete SSB demodulation system that was being proposed to replace an older analog SSB demodulation system. Having never built an SSB system, I wanted to understand how the "phasing method" of SSB demodulation works. However, in searching the Internet for tutorial SSB demodulation information I was shocked at how little information was available. The web's wikipedia 'single-sideband modulation' gives the mathematical details of SSB generation [1]. But SSB demodulation information at that web site was terribly sparse. In my Internet searching, I found the SSB information available on the net to be either badly confusing in its notation or downright ambiguous. That web- based material showed SSB demodulation block diagrams, but they didn't show spectra at various stages in the diagrams to help me understand the details of the processing. A typical example of what was frustrating me about the web-based SSB information is given in the analog SSB generation network shown in Figure 1. x(t) cos(ωct) + 90o 90o y(t) – sin(ωct) Meant to Is this sin(ω t) represent the c Hilbert or –sin(ωct) Transformer. -
DTV Interference Rejection Thresholds Are Shown on the Plot As a Reference
Interference Rejection Thresholds of Consumer Digital Television Receivers Available in 2005 and 2006 March 30, 2007 Technical Research Branch Laboratory Division Office of Engineering and Technology Federal Communications Commission OET Report Prepared by: FCC/OET 07-TR-1003 Stephen R. Martin ACKNOWLEDGEMENTS The author gratefully acknowledges the following contributions to this work. Mark Hryszko of the Digital Television group of Advanced Micro Devices provided the “Muddy Waters” RF vector file (mathematically derived from an MPEG2 transport stream) that was used with the Wavetech WS2100 RF player to provide a “desired signal” for the final few tests performed for this report. John Gabrysch of the Commission’s Media Bureau set up and evaluated the performance of the Rohde and Schwarz SFU DTV signal generator and developed channel assignment files for the instrument. The work of Charles Rhodes on third-order intermodulation inspired the paired-signal tests in this project. Gary Sgrignoli of MSW provided a fast-track DTV education to prepare the author for the prequel to this project. The author thanks the following Commission employees for reviewing drafts of this document: Alan Stillwell, Rashmi Doshi, and William Hurst (Office of Engineering and Technology); Doug Miller, John Raymond, and Steve DeSena (Enforcement Bureau); Richard Engelman and Sankar Persaud (International Bureau). The author also acknowledges the support of wife, Dr. Bonnie Dorr, through many long hours spent completing this work. i TABLE OF CONTENTS EXECUTIVE SUMMARY -
N9064A & W9064A VXA Signal Analyzer Measurement Application Measurement Guide
Agilent X-Series Signal Analyzer This manual provides documentation for the following analyzers: PXA Signal Analyzer N9030A MXA Signal Analyzer N9020A EXA Signal Analyzer N9010A CXA Signal Analyzer N9000A N9064A & W9064A VXA Signal Analyzer Measurement Application Measurement Guide Agilent Technologies Notices © Agilent Technologies, Inc. Manual Part Number as defined in DFAR 252.227-7014 2008-2010 (June 1995), or as a “commercial N9064-90002 item” as defined in FAR 2.101(a) or No part of this manual may be as “Restricted computer software” reproduced in any form or by any Supersedes: July 2010 as defined in FAR 52.227-19 (June means (including electronic storage Print Date 1987) or any equivalent agency and retrieval or translation into a regulation or contract clause. Use, foreign language) without prior October 2010 duplication or disclosure of Software agreement and written consent from is subject to Agilent Technologies’ Agilent Technologies, Inc. as Printed in USA standard commercial license terms, governed by United States and Agilent Technologies Inc. and non-DOD Departments and international copyright laws. 1400 Fountaingrove Parkway Agencies of the U.S. Government Trademark Santa Rosa, CA 95403 will receive no greater than Acknowledgements Warranty Restricted Rights as defined in FAR 52.227-19(c)(1-2) (June 1987). U.S. Microsoft® is a U.S. registered The material contained in this Government users will receive no trademark of Microsoft Corporation. document is provided “as is,” and is greater than Limited Rights as subject to being changed, without defined in FAR 52.227-14 (June Windows® and MS Windows® are notice, in future editions. -
Spatial Characteristics of Distortion Radiated from Antenna Arrays with Transceiver Nonlinearities Christopher Mollen,´ Ulf Gustavsson, Thomas Eriksson, Erik G
1 Spatial Characteristics of Distortion Radiated from Antenna Arrays with Transceiver Nonlinearities Christopher Mollen,´ Ulf Gustavsson, Thomas Eriksson, Erik G. Larsson Abstract—The distortion from massive MIMO (multiple-input– paper is to give a rigorous description of the distortion created multiple-output) base stations with nonlinear amplifiers is studied by nonlinear hardware in multi-antenna transmitters, and to and its radiation pattern is derived. The distortion is analyzed quantify to which degree the distortion combines coherently. both in-band and out-of-band. By using an orthogonal Her- mite representation of the amplified signal, the spatial cross- The contribution of this paper is to give a rigorous correlation matrix of the nonlinear distortion is obtained. It continuous-time system model of a multi-antenna transmitter shows that, if the input signal to the amplifiers has a dominant for both single-carrier and OFDM (orthogonal frequency- beam, the distortion is beamformed in the same way as that beam. division multiplexing) transmission that uses digital precoding When there are multiple beams without any one being dominant, to beamform to multiple users. Orthogonal polynomials are it is shown that the distortion is practically isotropic. The derived theory is useful to predict how the nonlinear distortion will used to partition the amplified transmit signal into a desired behave, to analyze the out-of-band radiation, to do reciprocity signal—the linearly amplified signal—and a distortion term calibration, and to schedule users in the frequency plane to that is uncorrelated from the desired signal in order to analyze minimize the effect of in-band distortion.