Phase Jitter in DTV Signals
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Improvement of Bit Error Rate in Fiber Optic Communications
International Journal of Future Computer and Communication, Vol. 3, No. 4, August 2014 Improvement of Bit Error Rate in Fiber Optic Communications Jahangir Alam S. M., M. Rabiul Alam, Hu Guoqing, and Md. Zakirul Mehrab Abstract—The bit error rate (BER) is the percentage of bits II. BIT ERROR RATE AND SIGNAL-TO-NOISE RATIO that have errors relative to the total number of bits received in a transmission. The different modulation techniques scheme is In telecommunication transmission, the bit error rate (BER) suggested for improvement of BER in fiber optic is the percentage of bits that have errors relative to the total communications. The developed scheme has been tested on number of bits received in a transmission. For example, a optical fiber systems operating with a non-return-to-zero (NRZ) transmission might have a BER of 10-6, meaning that, out of format at transmission rates of up to 10Gbps. Numerical 1,000,000 bits transmitted, one bit was in error. The BER is simulations have shown a noticeable improvement of the system an indication of how often data has to be retransmitted BER after optimization of the suggested processing operation on the detected electrical signals at central wavelengths in the because of an error [1]. Too high a BER may indicate that a region of 1310 nm. slower data rate would actually improve overall transmission time for a given amount of transmitted data since the BER Index Terms—BER, modulation techniques, SNR, NRZ, might be reduced, lowering the number of packets that had to improvement. be present. -
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. -
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. -
Applications of Machine Learning in Cable Access Networks Karthik Sundaresan, Nicolas Metts, Greg White; Albert Cabellos-Aparicio Cablelabs; UPC Barcelonatech
Applications of Machine Learning in Cable Access Networks Karthik Sundaresan, Nicolas Metts, Greg White; Albert Cabellos-Aparicio CableLabs; UPC BarcelonaTech. Abstract proven to be powerful components in the Machine Learning space. Recent advances in Machine Learning algorithms have resulted in an explosion of Potential applications for Machine real-world applications, including self-driving Learning abound in the areas of network cars, face and emotion recognition, automatic technology and applications. It can be used to image captioning, real-time speech intelligently learn the various environments of translation and drug discovery. networks and react to dynamic situations better than a fixed algorithm. When it Potential applications for Machine becomes mature, it would greatly accelerate Learning abound in the areas of network the development of autonomic networking. technology, and there are various problem areas in the cable access network which can There are various problem areas in the benefit from Machine Learning techniques. cable access network which can benefit from This paper provides an overview of Machine Machine Learning techniques. For example, Learning algorithms, and how they could be the Proactive Network Maintenance data applied to the applications of interest to cable which represents network conditions obtained operators and equipment suppliers. from CMTS and CM can be processed through Machine Learning algorithms to enable automatic recognition of issues in the cable plant and initiating the needed INTRODUCTION corrective actions. Patterns in network traffic, equipment failures, device reboots or link Recent advances in Machine Learning, and failures can be used to identify the root cause in particular, deep learning, have resulted in of various network problems. -
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. -
Etsi Tr 101 290 V1.3.1 (2014-07)
ETSI TR 101 290 V1.3.1 (2014-07) TECHNICAL REPORT Digital Video Broadcasting (DVB); Measurement guidelines for DVB systems 2 ETSI TR 101 290 V1.3.1 (2014-07) Reference RTR/JTC-DVB-340 Keywords broadcasting, digital, DVB, TV, video 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 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: http://portal.etsi.org/chaircor/ETSI_support.asp 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. -
22Nd International Congress on Acoustics ICA 2016
Page intentionaly left blank 22nd International Congress on Acoustics ICA 2016 PROCEEDINGS Editors: Federico Miyara Ernesto Accolti Vivian Pasch Nilda Vechiatti X Congreso Iberoamericano de Acústica XIV Congreso Argentino de Acústica XXVI Encontro da Sociedade Brasileira de Acústica 22nd International Congress on Acoustics ICA 2016 : Proceedings / Federico Miyara ... [et al.] ; compilado por Federico Miyara ; Ernesto Accolti. - 1a ed . - Gonnet : Asociación de Acústicos Argentinos, 2016. Libro digital, PDF Archivo Digital: descarga y online ISBN 978-987-24713-6-1 1. Acústica. 2. Acústica Arquitectónica. 3. Electroacústica. I. Miyara, Federico II. Miyara, Federico, comp. III. Accolti, Ernesto, comp. CDD 690.22 ISBN 978-987-24713-6-1 © Asociación de Acústicos Argentinos Hecho el depósito que marca la ley 11.723 Disclaimer: The material, information, results, opinions, and/or views in this publication, as well as the claim for authorship and originality, are the sole responsibility of the respective author(s) of each paper, not the International Commission for Acoustics, the Federación Iberoamaricana de Acústica, the Asociación de Acústicos Argentinos or any of their employees, members, authorities, or editors. Except for the cases in which it is expressly stated, the papers have not been subject to peer review. The editors have attempted to accomplish a uniform presentation for all papers and the authors have been given the opportunity to correct detected formatting non-compliances Hecho en Argentina Made in Argentina Asociación de Acústicos Argentinos, AdAA Camino Centenario y 5006, Gonnet, Buenos Aires, Argentina http://www.adaa.org.ar Proceedings of the 22th International Congress on Acoustics ICA 2016 5-9 September 2016 Catholic University of Argentina, Buenos Aires, Argentina ICA 2016 has been organised by the Ibero-american Federation of Acoustics (FIA) and the Argentinian Acousticians Association (AdAA) on behalf of the International Commission for Acoustics. -
R&S®FSW-K70 Measuring the BER and the EVM for Signals With
R&S®FSW-K70 Measuring the BER and the EVM for Signals with Low SNR Application Sheet Signals with low signal-to-noise ratios (SNR) often cause bit errors during demodulation, so that modula- tion accuracy values such as the error vector magnitude (EVM) may not be determined correctly. This application sheet describes: ● The significance of the Bit Error Rate (BER) parameter for signal analysis ● How the R&S FSW VSA application calculates the BER and determines bit errors ● How this knowledge can be used to obtain correct modulation accuracy results (;ÜOÔ2) 1178.3170.02 ─ 01 Application Sheet Test & Measurement R&S®FSW-K70 Contents Contents 1 Introduction............................................................................................ 2 2 How to Create Known Data Files..........................................................3 3 BER Measurement in the R&S FSW VSA application.........................6 4 Tips for Improving Signal Demodulation in Preparation for the Known Data File..................................................................................... 8 5 Measurement Example - Measuring the BER....................................14 6 Additional Information.........................................................................16 1 Introduction What is the Bit Error Rate (BER)? In signal analysis, a bit error occurs when a false symbol decision is made during demodulation. That is: the demodulated symbol does not correspond to the transmitted symbol. Bit errors often occur when demodulating highly distorted signals -
Digital Quality Index (DQI) Assessing Downstream Digital Signal Quality
VIAVI Solutions Application Note Digital Quality Index (DQI) Assessing Downstream Digital Signal Quality Overview Most downstream channels are transported on digital quadrature amplitude modulation (QAM) carriers. How are intermittent transport issues detected within those downstream digital services, and are customer quality expectations being met? A patented VIAVI measurement called DQI (Digital Quality Index) concentrates on the condition of the raw information on the physical path and immediately detects intermittent issues and sustained issues within the stream. In comparison, the typical measurement used to check for these issues on a digital QAM carrier is pre and post forward error correction (FEC) bit error ratio (BER), which relies on actual errors and is relatively slow to detect many issues. Drawback of Current Methods Most digital field test equipment today incorporates the same digital hardware components that reception equipment uses. These components use numerous correction technologies to adjust the demodulated carrier correcting problems that were the result of transmission issues on the RF physical path. These technologies make the digital reception a superior quality service versus the older analog methods. Test instruments monitor these technologies to achieve a quantitative view of how hard the reception hardware is working to correct the physical path issues. The resultant measurements become an indicator of potential issues, not actual carrier quality. In some cases, the technologies can mask the issues since their intent is to correct issues before the user sees a problem. Utilizing the same technologies for test purposes is not as responsive as the old analog test measurements. What is the Goal of Field Testing? The goal of field testing is to identify network issues before services are affected and to fix the problem before the customer experiences any degradation of service. -
MODULATION ERROR RATIO by RON HRANAC
Originally appeared in the January 2007 issue of Communications Technology. MODULATION ERROR RATIO By RON HRANAC Awhile back I went target shooting with a friend. While at the range, it occurred to me that what is also known as plinking is a little like modulation error ratio (MER) used to characterize, say, the 64- and 256-QAM (quadrature amplitude modulation) digitally modulated signals we transmit to our customers. OK, before you start to wonder whether I’ve had too much coffee today, bear with me as I discuss this somewhat off-the-wall analogy. Similarities A typical target used at the range comprises a set of concentric circles printed on a piece of paper. The center of the target is called the bull’s-eye, which carries the highest point value. The further away from the bull’s-eye, the lower the assigned points. Ideally, one would always hit the bull’s-eye and get the maximum possible score. In the real world, this seldom happens. Instead, one or two shots might hit at or near the bull’s-eye, and most of the rest hit somewhere in the circles surrounding the center of the target. For a person who is a decent shot, plinking usually results in a fairly uniform “fuzzy cloud” of holes in and around the bull’s-eye. The smaller the diameter of this cloud and the closer it is to the bull’s-eye, the higher the score. Factors affecting how close to the bull’s-eye the shots land include the quality and accuracy of the firearm, type of ammunition used, weather conditions if outdoors, ambient lighting, and the distance to the target.