DOCSLIB.ORG

Characterizing Digitally Modulated Signals with CCDF Curves

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Characterizing Digitally Modulated Signals with CCDF Curves Characterizing Digitally Modulated Signals with CCDF Curves Application Note Table of Contents 1. Introduction When are CCDF curves used? 2. What are CCDF curves? Statistical origin of CCDF curves Why not crest factor? 3. CCDF in communications Modulation formats Modulation filtering Multiple-frequency signals Phases affect multi-tone signals Spread-spectrum systems Number of active codes in spread spectrum Orthogonal coding effects Multi-carrier signals 4. CCDF in component design Compression of signal by nonlinear components Correlating the amplifier curves with the CCDF plot Compression affects other key measurements Applications 5. Summary 6. References 7. Symbols and acronyms 2 Introduction The move to 3G systems will yield This application note examines signals with higher peak-to-average the main factors that affect power ratios (crest factors) than power CCDF curves, and previously encountered. Analog describes how CCDF curves Digital modulation has created a FM systems operate at a fixed are used to help design systems revolution in RF and microwave power level: analog double-side- and components. communications. Cellular systems band large-carrier (DSB-LC) AM have moved from the old analog systems cannot modulate over When are CCDF curves used? AMPS and TACS systems to second 100% (a peak value 6 dB above Perhaps the most important appli- generation NADC, CDMA, and GSM the unmodulated carrier) without cation of power CCDF curves is standards. Today, the cellular distortion. Third generation systems, to specify completely and without industry talks of moving to third on the other hand, combine ambiguity the power character- generation (3G) digital systems multiple channels, resulting in a istics of the signals that will be such as W-CDMA and cdma2000. peak-to-average ratio that is mixed, amplified, and decoded Outside of cellular communications, dependent upon not only the in communication systems. For the broadcast industry is also number of channels being com- example, baseband DSP signal moving into the era of digital bined, but also which specific designers can completely specify modulation. High Definition channels are used. This signal the power characteristics of Television (HDTV) systems will characteristic can lead to higher signals to the RF designers by use 8-level Vestigial Side Band distortion unless the peak power using CCDF curves. This helps (8VSB) and Coded Orthogonal levels are accounted for in the avoid costly errors at system Frequency Division Multiplexing design of system components, integration time. Similarly, system (COFDM) digital modulation for- such as amplifiers and mixers. manufacturers can avoid mats in various parts of the world. ambiguity by completely specify- Power Complementary Cumulative ing the test signal parameters to Distribution Function (CCDF) their amplifier suppliers. curves provide critical information about the signals encountered in CCDF curves apply to many 3G systems. These curves also design applications. Some of provide the peak-to-average power these applications are: data needed by component • Visualizing the effects of designers. modulation formats. • Combining multiple signals via systems components (for example, amplifiers). • Evaluating spread-spectrum systems. • Designing and testing RF components. 3 What are CCDF curves? A. Ref–10.00 dBm RF Envelope A CCDF curve shows how much 3.00 time the signal spends at or above dB/ 3 a given power level. The power 2 level is expressed in dB relative to 1 the average power. For example, Avg each of the lines across the wave- form shown in Figure 1A repre- sents a specific power level above the average. The percentage of time the signal spends at 0.00 ms 1.00 ms or above each line defines the probability for that particular Figure 1A: Construction of a CCDF curve power level. A CCDF curve is a plot of relative power levels ver- The signal power exceeds the average by at least sus probability. B. 7.5dB for 1% of the time. Y-axis Figure 1B displays the CCDF is the 100% percent curve of the same 9-channel of time 10% 1 cdmaOne signal captured on the the signal power E4406A VSA. Here, the x-axis is 1% 2 is at scaled to dB above the average OR ABOVE 3 the power 0.1% signal power, which means we are specified actually measuring the peak-to- by the 0.010% x-axis. average ratios as opposed to 0.0010% absolute power levels. The y-axis 0.00010% is the percent of time the signal 0.00 15.00 dB Res BW 5.00000 MHz spends at or above the power level specified by the x-axis. For Band-limited Gaussian noise X-axis is dB above CCDF reference line. average power example, at t = 1% on the y-axis, the corresponding peak-to-average Figure 1B: CCDF curve of a typical cdmaOne signal ratio is 7.5 dB on the x-axis. This means the signal power exceeds Figure 1A shows the power versus Unfortunately, the signal in the the average by at least 7.5 dB for time plot of a 9-channel cdmaOne form shown in Figure 1A is 1 percent of the time. The posi- signal. This plot represents the difficult to quantify because of tion of the CCDF curve indicates instantaneous envelope power its inherent randomness and the degree of peak-to-average defined by the equation: inconsistencies. In order to deviation, with more stressful extract useful information from Power = I2 + Q2 signals further to the right. this noise-like signal, we need where I and Q are the in-phase a statistical description of the and quadrature components of power levels in this signal, and the waveform. a CCDF curve gives just that. 4 Statistical Rotate PDF Ref–10.00dBm RF Envelope origin of 3.00 dB/ 50 MaxP %Probability 40 CCDF -9.0 30 Avg ExtHt 20 0.0 50 10 dB above average 40 curves %Probability30 dB above average 0 20 10 -3 -2 -1 0 1 2 3 -3 -2 -1 0 1 2 3 Trig 0 -3 -2 -1 0 1 2 3 -3 -2 -1 0 1 2 dB above average Free 0.00 ms 1.00 ms 0 Res BW 100.000 kHz Guassian Samples 1365points @733.33 ns 50 40 30 20 10 %Probability CDF Now that we’ve seen a practical PDF 120 100 CCDF curve (Figure 1A), let’s 50 %Probability 40 80 briefly investigate the mathematics 30 60 20 40 10 Probability 20 of CCDF curves. Let’s start with a = Cumulative 0 dP 0 -3 -2 -1 0 1 2 3 set of data that has the Probability dB above average -3 -2 -1 0 1 2 3 Density Function (PDF) shown in dB above average Figure 2. To obtain the Cumulative Distribution Function (CDF), we CCDF compute the integral of the PDF. CDF 120 Finally, inverting the CDF results 120 100 100 80 in the CCDF. That is, the CCDF 80 60 60 40 40 is the complement of the CDF Probability 20 Cumulative Probability 20 Cumulative – 0 = -3 -2 -1 0 1 2 3 0 (CCDF = 1 – CDF). To generate dB above average -3 -2 -1 0 1 2 3 1 1 - the CCDF curve in the form dB above average shown in Figure 1A, convert the Figure 2: Mathematical origin of CCDF y-axis to logarithmic form and begin the x-axis at 0 dB. A logarith- mic y-axis provides better resolu- This measurement is of question- In short, crest factor places too tion for low-probability events. able value for several reasons: much emphasis on a signal’s The reason we plot CCDF instead instantaneous peak value. To of CDF is that CCDF emphasizes • Error-correction coding will mitigate this, the peak value is peak amplitude excursions, while often remove the effect of a sometimes considered to be the CDF emphasizes minimum values. single error-causing peak in level where 99.8 percent of the the system. waveform is below the peak value, Why not crest factor? • A single peak that is much and 0.2 percent of the waveform As the need for characterizing higher than the prevailing is above it. While this lessens the noise-like signals becomes signal level sometimes is emphasis on a single point of a greater, we search for the most treated as an anomalous waveform, the use of a single convenient, useful, and reliable condition and ignored. level (such as 0.2 percent) is still measurement to meet this need. • A peak that occurs infre rather arbitrary. CCDF gives us Traditionally, a common measure quently causes little spectral more complete information about of stress for a stimulating signal regrowth, which makes the high signal levels than does has been the crest factor. Crest repeatable measurements crest factor [1]. factor is the ratio of the peak difficult. voltage to its root-mean-square • The highest peak value that value. occurs for true noise depends on the length of the measurement time. 5 CCDF in communications A. QPSK signal TRACE A: Ch1 Main Time A Mkr 0.0000 s 28.144 mV -145.59 deg 40 mV I - Q 8 mV/div -40 mV -52.287583351 mV 52.2875833511 mV 100% B. 16QAM signal TRACE B: Ch1 Main Time 10% QPSK signal 40 mV 1% I - Q 0.1% 16QAM signal 8 mV/div 0.01% 0.001% 0.0001% 0.00 10.00 dB -40 mV Res BW 5.00000 MHz -52.287583351 mV 52.2875833511 mV Figure 3: Vector plots of (A.) QPSK signal Figure 4: CCDF curves of a QPSK signal and a 16QAM signal and (B.) 16QAM signal Modulation formats of a 16-Quadrature Amplitude Figure 4 shows the power CCDF The modulation format of a signal Modulation (16QAM) signal.
Load more

Recommended publications
  • WILL the REAL MAXIMUM SPL PLEASE STAND UP? Measured Maximum SPL Vs Calculated Maximum SPL and How Not to Be Fooled
    WILL THE REAL MAXIMUM SPL PLEASE STAND UP? Measured Maximum SPL vs Calculated Maximum SPL and how not to be fooled Introduction When purchasing powered loudspeakers, most customers compare three key specifications: price, power and maximum SPL. Unfortunately, this can be like comparing apples and oranges. For the Maximum SPL number in particular, each manufacturer often has its own way of reporting the specification. There are various methods a manufacturer can employ and each tends to choose the one that makes a particular product look the best. Unfortunately for the customer, this makes comparing two products on paper very difficult. In this document, Mackie will do the following to shed some light on this issue: • Compare and contrast two common ways of reporting the maximum SPL of a powered loudspeaker. • Conduct a case study comparing the Mackie HD series loudspeakers with similar models from a key competitor to illustrate these differences. • Provide common practices for the customer to follow, allowing them to see through the hype and help them choose the best loudspeaker for their specific needs. The two most common ways of reporting maximum SPL for a loudspeaker are a Calculated Maximum SPL and a Measured Maximum SPL. These names are given here to simplify comparison; other manufacturers may use different terminology. Calculated Maximum SPL The Calculated Maximum SPL is a purely theoretical specification. The manufacturer uses the known power of their amplifier and the known sensitivity of the transducer to mathematically calculate the maximum SPL they can produce in a particular loudspeaker. For example, a compression driver’s peak sensitivity may be 110 dB at 1W at 1 meter.
    [Show full text]
  • Frequency Based Fatigue
    Frequency Based Fatigue Professor Darrell F. Socie Mechanical Engineering University of Illinois at Urbana-Champaign © 2001 Darrell Socie, All Rights Reserved Deterministic versus Random Deterministic – from past measurements the future position of a satellite can be predicted with reasonable accuracy Random – from past measurements the future position of a car can only be described in terms of probability and statistical averages AAR Seminar © 2001 Darrell Socie, All Rights Reserved 1 of 57 Time Domain Bracket.sif-Strain_c56 750 Strain (ustrain) -750 Time (Secs) AAR Seminar © 2001 Darrell Socie, All Rights Reserved 2 of 57 Frequency Domain ap_000.sif-Strain_b43 102 101 100 Strain (ustrain) 10-1 0 20 40 60 80 100 120 140 Frequency (Hz) AAR Seminar © 2001 Darrell Socie, All Rights Reserved 3 of 57 Statistics of Time Histories ! Mean or Expected Value ! Variance / Standard Deviation ! Coefficient of Variation ! Root Mean Square ! Kurtosis ! Skewness ! Crest Factor ! Irregularity Factor AAR Seminar © 2001 Darrell Socie, All Rights Reserved 4 of 57 Mean or Expected Value Central tendency of the data N ∑ x i = Mean = µ = x = E()X = i 1 x N AAR Seminar © 2001 Darrell Socie, All Rights Reserved 5 of 57 Variance / Standard Deviation Dispersion of the data N − 2 ∑( xi x ) Var()X = i =1 N Standard deviation σ = x Var( X ) AAR Seminar © 2001 Darrell Socie, All Rights Reserved 6 of 57 Coefficient of Variation σ COV = x µ x Useful to compare different dispersions µ =10 µ = 100 σ =1 σ =10 COV = 0.1 COV = 0.1 AAR Seminar © 2001 Darrell Socie, All Rights Reserved 7 of 57 Root Mean Square N 2 ∑ x i = RMS = i 1 N The rms is equal to the standard deviation when the mean is 0 AAR Seminar © 2001 Darrell Socie, All Rights Reserved 8 of 57 Skewness Skewness is a measure of the asymmetry of the data around the sample mean.
    [Show full text]
  • Sound Quality of Audio Systems
    Acoustical Measurement of Sound System Equipment according IEC 60268-21 符合IEC 60268-21的音響系統聲學測量設備 KLIPPEL- live a series of webinars presented by Wolfgang Klippel KLIPPEL-live #5: Maximum SPL – a number becomes important , 1 Previous Sessions 1. Modern audio equipment needs output based testing 2. Standard acoustical tests performed in normal rooms 3. Drawing meaningful conclusions from 3D output measurement 4. Simulated standard condition at an evaluation point 5. Maximum SPL – giving this value meaning 6. Selecting measurements with high diagnostic value 7. Amplitude Compression – less output at higher amplitudes 8. Harmonic Distortion Measurements – best practice 9. Intermodulation Distortion – music is more than a single tone 10.Impulsive distortion - rub&buzz, abnormal behavior, defects 11.Benchmarking of audio products under standard conditions 12.Auralization of signal distortion – perceptual evaluation 13.Setting meaningful tolerances for signal distortion Acoustical14.testingRatingof a modernthe maximum active audio deviceSPL value for a product 1st Session15.2nd SessionSmart speaker testing with wireless audio input 3rd Session 4th Session KLIPPEL-live #5: Maximum SPL – a number becomes important , 2 Ask Klippel First Question: 在沒有復雜的測試箱或基於近場/遠場測量設置的測試箱的情況下，品檢上是否有一個好的解決方案。 Is there a good solution for on-line QC without complex testing box or testing chamber based on near field / far field measurement setting. Response WK: 否，對於傳感器和小型系統（例如智能手機），因為屏蔽環境噪聲非常有用。 NO, for transducers and small system (e.g. smart phones) because the shielding against ambient noise is very useful. 是的，較大的系統（條形音箱，專業設備，電視……）需要不同的解決方式 Yes, larger systems (sound bars, professional equipment, TVs …) need a different solution considering the following points: • 進行近場測量（與環境噪聲相比，SNR更高，SPL更高） Performing a near-field measurement (better SNR, higher SPL compared to ambient noise) • 在終端測試處使用圍繞測試站的吸收牆。 圍繞組裝線建造測試環境的最佳解決方案。 Using absorbing walls around the test station at the end of line.
    [Show full text]
  • Bachelor Thesis
    BACHELOR THESIS Perceived Sound Quality of Dynamic Range Reduced and Loudness Normalized Popular Music Jakob Lalér Bachelor of Arts Audio Engineering Luleå University of Technology Department of Business, Administration, Technology and Social Sciences Perceived sound quality of dynamic range reduced and loudness normalized popular music Lalér Jakob Lalér Jakob 1 S0038F ABSTRACT The lack of a standardized method for controlling perceived loudness within the music industry has been a contributory cause to the level increases that emerged in popular music at the beginning of the 1990s. As a consequence, discussions about what constitutes sound quality have been raised. This paper investigates to what extent dynamic range reduction affects perceived sound quality of popular music when loudness normalized in accordance with ITU-R BS. 1770-2. The results show that perceived sound quality was not affected by as much as -9 dB of average gain reduction. Lalér Jakob 2 S0038F TABLE OF CONTENTS ABSTRACT...........................................................................................................................................2 INTRODUCTION...................................................................................................................................4 Aim, Objectives and Limitations............................................................................................................4 Background..........................................................................................................................................4
    [Show full text]
  • A Review of Feature Extraction Methods in Vibration-Based Condition Monitoring and Its Application for Degradation Trend Estimation of Low-Speed Slew Bearing
    machines Review A Review of Feature Extraction Methods in Vibration-Based Condition Monitoring and Its Application for Degradation Trend Estimation of Low-Speed Slew Bearing Wahyu Caesarendra 1,2 ID and Tegoeh Tjahjowidodo 3,* ID 1 Mechanical Engineering Department, Diponegoro University, Semarang 50275, Indonesia; [email protected] 2 School of Mechanical, Materials and Mechatronic Engineering, University of Wollongong, Wollongong, NSW 2522, Australia 3 School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore * Correspondence: [email protected] Received: 9 August 2017; Accepted: 19 September 2017; Published: 27 September 2017 Abstract: This paper presents an empirical study of feature extraction methods for the application of low-speed slew bearing condition monitoring. The aim of the study is to find the proper features that represent the degradation condition of slew bearing rotating at very low speed (≈1 r/min) with naturally defect. The literature study of existing research, related to feature extraction methods or algorithms in a wide range of applications such as vibration analysis, time series analysis and bio-medical signal processing, is discussed. Some features are applied in vibration slew bearing data acquired from laboratory tests. The selected features such as impulse factor, margin factor, approximate entropy and largest Lyapunov exponent (LLE) show obvious changes in bearing condition from normal condition to final failure. Keywords: vibration-based condition monitoring; feature extraction; low-speed slew bearing 1. Introduction Slew bearings are large roller element bearings that are used in heavy industries such as mining and steel milling. They are particularly used in turntables, cranes, cranes, rotatable trolleys, excavators, reclaimers, stackers, swing shovels and ladle cars [1].
    [Show full text]
  • Crest Factors of Complementary-Sequence-Based Multicode MC-CDMA Signals Byoung-Jo Choi and Lajos Hanzo
    1114 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 2, NO. 6, NOVEMBER 2003 Crest Factors of Complementary-Sequence-Based Multicode MC-CDMA Signals Byoung-Jo Choi and Lajos Hanzo Abstract—The crest factor properties of binary phase-shift be bounded by 4 dB upon carefully selecting the code sets keying modulated two- and four-code assisted multicarrier and upon employing high-rate crest-factor reduction coding, code-division multiple-access (MC-CDMA) employing comple- provided that the number of simultaneously used codes is mentary-sequence-based spreading sequences are characterized. More specifically, a complementary-sequence pair, a comple- higher than or equal to four. When is less than four, the mentary-sequence-based subcomplementary code pair, and a MC-CDMA signals employing orthogonal Gold (OGold) Sivaswamy’s complementary code set are studied. It was found codes, Frank codes [8], and Zadoff–Chu codes [10], [11] that the corresponding crest factors are bounded by 3 dB, which resulted in considerably lower crest factors. Even though corresponds to the crest factor of a single sine wave. This low crest Zadoff–Chu codes indeed do produce an ideal crest factor of factor resulted in a lower power loss and a lower out-of-band power spectrum due to clipping when the time-domain signal was less than 3 dB in the context of single-code MC-CDMA, the subjected to a typical nonlinear power amplifier, in comparison to crest factor values of neither Zadoff–Chu codes, Frank codes, those of Walsh code and orthogonal Gold code-spread MC-CDMA nor those of OGold codes are bounded by 3 dB in the context of signals.
    [Show full text]
  • An Efficient Hardware Implementation of the Peak Cancellation Crest Factor Reduction Algorithm
    DEGREE PROJECT IN INFORMATION AND COMMUNICATION TECHNOLOGY, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2016 An efficient Hardware implementation of the Peak Cancellation Crest Factor Reduction Algorithm MATTEO BERNINI KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF INFORMATION AND COMMUNICATION TECHNOLOGY An efficient Hardware implementation of the Peak Cancellation Crest Factor Reduction Algorithm MATTEO BERNINI Master’s Thesis at KTH Information and Communication Technology Supervisor: Shafqat Ullah Examiner: Johnny Öberg TRITA-ICT-EX-2016:187 Abstract An important component of the cost of a radio base station comes from to the Power Am- plifier driving the array of antennas. The cost can be split in Capital and Operational expenditure, due to the high design and realization costs and low energy efficiency of the Power Amplifier respectively. Both these cost components are related to the Crest Factor of the input signal. In order to reduce both costs, it would be possible to lower the average power level of the transmitting signal, whereas in order to obtain a more efficient transmis- sion, a more energized signal would allow the receiver to better distinguish the message from the noise and interferences. These opposed needs motivate the research and development of solutions aiming at reducing the excursion of the signal without the need of sacrificing its average power level. One of the algorithms addressing this problem is the Peak Cancellation Crest Factor Reduction. This work documents the design of a hardware implementation of such method, targeting a possible future ASIC for Ericsson AB. SystemVerilog is the Hardware Description Language used for both the design and the verification of the project, together with a MATLAB model used for both exploring some design choices and to val- idate the design against the output of the simulation.
    [Show full text]
  • Efficiency Investigation of Switch Mode Power Amplifier Drving Low Impedance Transducers
    Downloaded from orbit.dtu.dk on: Sep 26, 2021 Efficiency Investigation of Switch Mode Power Amplifier Drving Low Impedance Transducers Iversen, Niels Elkjær; Schneider, Henrik; Knott, Arnold; Andersen, Michael A. E. Published in: Proceedings of the139th Audio Engineering Society Convention. Publication date: 2015 Document Version Peer reviewed version Link back to DTU Orbit Citation (APA): Iversen, N. E., Schneider, H., Knott, A., & Andersen, M. A. E. (2015). Efficiency Investigation of Switch Mode Power Amplifier Drving Low Impedance Transducers. In Proceedings of the139th Audio Engineering Society Convention. Audio Engineering Society. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Audio Engineering Society Convention Paper Presented at the 139th Convention 2015 October 29{November 1 New York, USA This paper was peer-reviewed as a complete manuscript for presentation at this Convention. Additional papers may be obtained by sending request and remittance to Audio Engineering Society, 60 East 42nd Street, New York, New York 10165-2520, USA; also see www.aes.org.
    [Show full text]
  • Crest Factor and Amplifier Power
    TechnAmplifier Specificationical Note Proposals Crest Factor and Amplifier Power Introduction In order to achieve maximum fidelity/performance in an audio system, the loudspeakers and the amplifiers must be able to accurately reproduce peaks in the order of 12dB above the expected RMS levels. Over the last few years, loudspeaker manufacturers have been developing products that meet these criteria. It is especially important in high power PA systems, where the number of boxes needs to be kept to a minimum. Defining Crest Factor The Crest Factor of a waveform is defined as the ratio of the peak amplitude level divided by the RMS signal level. As such, it is a dimensionless value, but can be expressed in audio applications in decibels (dB). The minimum possible Crest Factor has a value of 1, where the peak amplitude is the same as the RMS amplitude. This is the CF of a square wave (assuming this swings symmetrically about zero Volts). A pure sine wave, also swinging symmetrically about zero of the same peak amplitude will have a CF of 1.414 as the RMS value is now ( √2)/2 so we have CF = 1/(( √2)/2) = 1.414. Determining Power Requirements MC 2 have developed the E-series of amplifiers to match the power requirements of these loudspeakers. They will deliver huge amounts of peak power, but automatically reduce (limit) the power if the CF of the signal goes too low. This reduces the heat generated within the amplifier and keeps the mains power draw to an acceptable level. It also helps to protect the loudspeakers which could suffer serious damage for the same reason.
    [Show full text]
  • The Crest Factor in DVB-T (OFDM) Transmitter Systems and Its Influence on the Dimensioning of Power Components
    ® ® ® ® ® ® Products: R&S NV7000, R&S NV7001, R&S NV8200, R&S SV7000, R&S SV7002, R&S SV8000 ® ® ® DTV transmitters, R&S EFA, R&S FSP, R&S FSU test instruments The Crest Factor in DVB-T (OFDM) Transmitter Systems and its Influence on the Dimensioning of Power Components Application Note 7TS02 Are there really power peaks that are 20 dB above the average value? Yes, there are. Ever since the intro- duction of digital transmission technology, it has been necessary to deal with such orders of magnitude. RF power components must be suitably dimensioned to handle the expected voltage peaks and avoid break- ing down. If we can determine the crest factor, i.e. the ratio of the peak value to the average or RMS value, with sufficient accuracy (even though it can only be assessed statistically), then we will have solved the question of dimensioning power components. This Application Note is intended to help with this problem by providing some useful insights including basic formulas, some statistical background and a practical look at the limiting factors when it comes to dealing with real transmitter systems. Subject to change – Bernhard Kaehs, January 2007 – 7TS02_2E Introduction Contents 1 Introduction ............................................................................................. 2 2 Determination and Usage of the Crest Factor ........................................ 3 The crest factor of a modulated RF signal......................................... 3 Crest factor for multiple superimposed signals.................................. 5 Crest factor measurement ................................................................. 6 Output signal from a DVB-T transmitter............................................. 9 Output bandpass.............................................................................. 11 Interconnection of multiple transmitters on an antenna................... 12 3 The Crest Factor During Generation of a DVB-T Signal .....................
    [Show full text]
  • New Methods for HD Radio™ Crest Factor Reduction and Pre-Correction
    New Methods for HD Radio Crest Factor Reduction and Pre-correction April 12, 2015 NAB Show 2015 Featuring GatesAir’s Tim Anderson Kevin Berndsen Radio Product & Business Senior Signal Development Manager Processing Engineer Copyright © 2015 GatesAir, Inc. All rights reserved. New Methods for HD Radio Crest Factor Reduction and Pre-correction Timothy Anderson, CPBE Radio Product Development Manager, GatesAir Kevin Berndsen, MSEE Senior Signal Processing Engineer, GatesAir NAB 2015 Broadcast Engineering Conference Crest Factor and Intermodulation Distortion The biggest challenge in amplifying orthogonal frequency-division multiplexed (OFDM) waveforms used for HD Radio and all other digital radio formats is: a) High Crest Factor of multiple carriers. b) Intermodulation products of multiple carriers Crest Factor vs. Peak-Average Power Ratio . Crest factor is a measure of a waveform, such as alternating current, sound or complex RF waveform, . As a power ratio, PAPR is showing the ratio of peak values to the normally expressed in average value. decibels (dB). Crest Factor is defined as the peak . When expressed in decibels, amplitude of the waveform divided by Crest Factor and PAPR are the RMS value of the waveform equivalent . The peak-to-average power ratio (PAPR) is the peak amplitude squared (giving the peak power) divided by the RMS value squared (giving the average power). It is the square of the crest factor Peak Distribution . The Hybrid HD Radio™ system uses up to 534 Orthogonal Frequency Division Multiplexed (OFDM) subcarriers modulated at equally spaced frequencies and 90 degrees to one another. Statistically, with this number of orthogonally opposed subcarriers, there can and will occasionally be very high amplitude peaks due to vector summation of the carriers.
    [Show full text]
  • AN-1434 Crest Factor Invariant RF Power Detector (Rev. A)
    Application Report SNWA004A–January 2006–Revised April 2013 AN-1434 Crest Factor Invariant RF Power Detector ..................................................................................................................................................... ABSTRACT The objective of this application report is to demonstrate and briefly explain how the LMV232 Mean Square Power Detector from Texas Instruments can be used as an accurate RF power detector for bandwidth efficiency modulated RF transmission in a handset or mobile unit. Contents 1 Introduction .................................................................................................................. 2 2 Overview of Digital Modulation in Cellular Phones ..................................................................... 2 3 GMSK Modulation in GSM/GPRS ........................................................................................ 4 4 QPSK and 16QAM Modulation in 3G CDMA ............................................................................ 4 5 Crest Factor (CF) or Peak-to-Average Ratio (PAR) in Digitally-Modulated RF ..................................... 4 6 Power Definition and Measurement in Cellular Phone Systems ...................................................... 5 7 Peak Power Detector ....................................................................................................... 5 8 Average Power Detector ................................................................................................... 5 9 Mean Square Detection ...................................................................................................
    [Show full text]