Oscillator Phase Noise
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Laser Linewidth, Frequency Noise and Measurement
Laser Linewidth, Frequency Noise and Measurement WHITEPAPER | MARCH 2021 OPTICAL SENSING Yihong Chen, Hank Blauvelt EMCORE Corporation, Alhambra, CA, USA LASER LINEWIDTH AND FREQUENCY NOISE Frequency Noise Power Spectrum Density SPECTRUM DENSITY Frequency noise power spectrum density reveals detailed information about phase noise of a laser, which is the root Single Frequency Laser and Frequency (phase) cause of laser spectral broadening. In principle, laser line Noise shape can be constructed from frequency noise power Ideally, a single frequency laser operates at single spectrum density although in most cases it can only be frequency with zero linewidth. In a real world, however, a done numerically. Laser linewidth can be extracted. laser has a finite linewidth because of phase fluctuation, Correlation between laser line shape and which causes instantaneous frequency shifted away from frequency noise power spectrum density (ref the central frequency: δν(t) = (1/2π) dφ/dt. [1]) Linewidth Laser linewidth is an important parameter for characterizing the purity of wavelength (frequency) and coherence of a Graphic (Heading 4-Subhead Black) light source. Typically, laser linewidth is defined as Full Width at Half-Maximum (FWHM), or 3 dB bandwidth (SEE FIGURE 1) Direct optical spectrum measurements using a grating Equation (1) is difficult to calculate, but a based optical spectrum analyzer can only measure the simpler expression gives a good approximation laser line shape with resolution down to ~pm range, which (ref [2]) corresponds to GHz level. Indirect linewidth measurement An effective integrated linewidth ∆_ can be found by can be done through self-heterodyne/homodyne technique solving the equation: or measuring frequency noise using frequency discriminator. -
An Integrated Low Phase Noise Radiation-Pressure-Driven Optomechanical Oscillator Chipset
OPEN An integrated low phase noise SUBJECT AREAS: radiation-pressure-driven OPTICS AND PHOTONICS NANOSCIENCE AND optomechanical oscillator chipset TECHNOLOGY Xingsheng Luan1, Yongjun Huang1,2, Ying Li1, James F. McMillan1, Jiangjun Zheng1, Shu-Wei Huang1, Pin-Chun Hsieh1, Tingyi Gu1, Di Wang1, Archita Hati3, David A. Howe3, Guangjun Wen2, Mingbin Yu4, Received Guoqiang Lo4, Dim-Lee Kwong4 & Chee Wei Wong1 26 June 2014 Accepted 1Optical Nanostructures Laboratory, Columbia University, New York, NY 10027, USA, 2Key Laboratory of Broadband Optical 13 October 2014 Fiber Transmission & Communication Networks, School of Communication and Information Engineering, University of Electronic 3 Published Science and Technology of China, Chengdu, 611731, China, National Institute of Standards and Technology, Boulder, CO 4 30 October 2014 80303, USA, The Institute of Microelectronics, 11 Science Park Road, Singapore 117685, Singapore. High-quality frequency references are the cornerstones in position, navigation and timing applications of Correspondence and both scientific and commercial domains. Optomechanical oscillators, with direct coupling to requests for materials continuous-wave light and non-material-limited f 3 Q product, are long regarded as a potential platform for should be addressed to frequency reference in radio-frequency-photonic architectures. However, one major challenge is the compatibility with standard CMOS fabrication processes while maintaining optomechanical high quality X.L. (xl2354@ performance. Here we demonstrate the monolithic integration of photonic crystal optomechanical columbia.edu); Y.H. oscillators and on-chip high speed Ge detectors based on the silicon CMOS platform. With the generation of (yh2663@columbia. both high harmonics (up to 59th order) and subharmonics (down to 1/4), our chipset provides multiple edu) or C.W.W. -
Analysis and Design of Wideband LC Vcos
Analysis and Design of Wideband LC VCOs Axel Dominique Berny Robert G. Meyer Ali Niknejad Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2006-50 http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-50.html May 12, 2006 Copyright © 2006, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Analysis and Design of Wideband LC VCOs by Axel Dominique Berny B.S. (University of Michigan, Ann Arbor) 2000 M.S. (University of California, Berkeley) 2002 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Electrical Engineering and Computer Sciences in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor Robert G. Meyer, Co-chair Professor Ali M. Niknejad, Co-chair Professor Philip B. Stark Spring 2006 Analysis and Design of Wideband LC VCOs Copyright 2006 by Axel Dominique Berny 1 Abstract Analysis and Design of Wideband LC VCOs by Axel Dominique Berny Doctor of Philosophy in Electrical Engineering and Computer Sciences University of California, Berkeley Professor Robert G. Meyer, Co-chair Professor Ali M. Niknejad, Co-chair The growing demand for higher data transfer rates and lower power consumption has had a major impact on the design of RF communication systems. -
Modeling the Impact of Phase Noise on the Performance of Crystal-Free Radios Osama Khan, Brad Wheeler, Filip Maksimovic, David Burnett, Ali M
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—II: EXPRESS BRIEFS, VOL. 64, NO. 7, JULY 2017 777 Modeling the Impact of Phase Noise on the Performance of Crystal-Free Radios Osama Khan, Brad Wheeler, Filip Maksimovic, David Burnett, Ali M. Niknejad, and Kris Pister Abstract—We propose a crystal-free radio receiver exploiting a free-running oscillator as a local oscillator (LO) while simulta- neously satisfying the 1% packet error rate (PER) specification of the IEEE 802.15.4 standard. This results in significant power savings for wireless communication in millimeter-scale microsys- tems targeting Internet of Things applications. A discrete time simulation method is presented that accurately captures the phase noise (PN) of a free-running oscillator used as an LO in a crystal- free radio receiver. This model is then used to quantify the impact of LO PN on the communication system performance of the IEEE 802.15.4 standard compliant receiver. It is found that the equiv- alent signal-to-noise ratio is limited to ∼8 dB for a 75-µW ring oscillator PN profile and to ∼10 dB for a 240-µW LC oscillator PN profile in an AWGN channel satisfying the standard’s 1% PER specification. Index Terms—Crystal-free radio, discrete time phase noise Fig. 1. Typical PN plot of an RF oscillator locked to a stable crystal frequency modeling, free-running oscillators, IEEE 802.15.4, incoherent reference. matched filter, Internet of Things (IoT), low-power radio, min- imum shift keying (MSK) modulation, O-QPSK modulation, power law noise, quartz crystal (XTAL), wireless communication. -
All You Need to Know About SINAD Measurements Using the 2023
applicationapplication notenote All you need to know about SINAD and its measurement using 2023 signal generators The 2023A, 2023B and 2025 can be supplied with an optional SINAD measuring capability. This article explains what SINAD measurements are, when they are used and how the SINAD option on 2023A, 2023B and 2025 performs this important task. www.ifrsys.com SINAD and its measurements using the 2023 What is SINAD? C-MESSAGE filter used in North America SINAD is a parameter which provides a quantitative Psophometric filter specified in ITU-T Recommendation measurement of the quality of an audio signal from a O.41, more commonly known from its original description as a communication device. For the purpose of this article the CCITT filter (also often referred to as a P53 filter) device is a radio receiver. The definition of SINAD is very simple A third type of filter is also sometimes used which is - its the ratio of the total signal power level (wanted Signal + unweighted (i.e. flat) over a broader bandwidth. Noise + Distortion or SND) to unwanted signal power (Noise + The telephony filter responses are tabulated in Figure 2. The Distortion or ND). It follows that the higher the figure the better differences in frequency response result in different SINAD the quality of the audio signal. The ratio is expressed as a values for the same signal. The C-MES signal uses a reference logarithmic value (in dB) from the formulae 10Log (SND/ND). frequency of 1 kHz while the CCITT filter uses a reference of Remember that this a power ratio, not a voltage ratio, so a 800 Hz, which results in the filter having "gain" at 1 kHz. -
Noise Tutorial Part IV ~ Noise Factor
Noise Tutorial Part IV ~ Noise Factor Whitham D. Reeve Anchorage, Alaska USA See last page for document information Noise Tutorial IV ~ Noise Factor Abstract: With the exception of some solar radio bursts, the extraterrestrial emissions received on Earth’s surface are very weak. Noise places a limit on the minimum detection capabilities of a radio telescope and may mask or corrupt these weak emissions. An understanding of noise and its measurement will help observers minimize its effects. This paper is a tutorial and includes six parts. Table of Contents Page Part I ~ Noise Concepts 1-1 Introduction 1-2 Basic noise sources 1-3 Noise amplitude 1-4 References Part II ~ Additional Noise Concepts 2-1 Noise spectrum 2-2 Noise bandwidth 2-3 Noise temperature 2-4 Noise power 2-5 Combinations of noisy resistors 2-6 References Part III ~ Attenuator and Amplifier Noise 3-1 Attenuation effects on noise temperature 3-2 Amplifier noise 3-3 Cascaded amplifiers 3-4 References Part IV ~ Noise Factor 4-1 Noise factor and noise figure 4-1 4-2 Noise factor of cascaded devices 4-7 4-3 References 4-11 Part V ~ Noise Measurements Concepts 5-1 General considerations for noise factor measurements 5-2 Noise factor measurements with the Y-factor method 5-3 References Part VI ~ Noise Measurements with a Spectrum Analyzer 6-1 Noise factor measurements with a spectrum analyzer 6-2 References See last page for document information Noise Tutorial IV ~ Noise Factor Part IV ~ Noise Factor 4-1. Noise factor and noise figure Noise factor and noise figure indicates the noisiness of a radio frequency device by comparing it to a reference noise source. -
Next Topic: NOISE
ECE145A/ECE218A Performance Limitations of Amplifiers 1. Distortion in Nonlinear Systems The upper limit of useful operation is limited by distortion. All analog systems and components of systems (amplifiers and mixers for example) become nonlinear when driven at large signal levels. The nonlinearity distorts the desired signal. This distortion exhibits itself in several ways: 1. Gain compression or expansion (sometimes called AM – AM distortion) 2. Phase distortion (sometimes called AM – PM distortion) 3. Unwanted frequencies (spurious outputs or spurs) in the output spectrum. For a single input, this appears at harmonic frequencies, creating harmonic distortion or HD. With multiple input signals, in-band distortion is created, called intermodulation distortion or IMD. When these spurs interfere with the desired signal, the S/N ratio or SINAD (Signal to noise plus distortion ratio) is degraded. Gain Compression. The nonlinear transfer characteristic of the component shows up in the grossest sense when the gain is no longer constant with input power. That is, if Pout is no longer linearly related to Pin, then the device is clearly nonlinear and distortion can be expected. Pout Pin P1dB, the input power required to compress the gain by 1 dB, is often used as a simple to measure index of gain compression. An amplifier with 1 dB of gain compression will generate severe distortion. Distortion generation in amplifiers can be understood by modeling the amplifier’s transfer characteristic with a simple power series function: 3 VaVaVout=−13 in in Of course, in a real amplifier, there may be terms of all orders present, but this simple cubic nonlinearity is easy to visualize. -
Understanding Phase Error and Jitter: Definitions, Implications
This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS–I: REGULAR PAPERS 1 Understanding Phase Error and Jitter: Definitions, Implications, Simulations, and Measurement Ian Galton , Fellow, IEEE, and Colin Weltin-Wu, Member, IEEE (Invited Paper) Abstract— Precision oscillators are ubiquitous in modern elec- multiplication by a sinusoidal oscillator signal whereas most tronic systems, and their accuracy often limits the performance practical mixer circuits perform multiplication by squared-up of such systems. Hence, a deep understanding of how oscillator oscillator signals. Fundamental questions typically are left performance is quantified, simulated, and measured, and how unanswered such as: How does the squaring-up process change it affects the system performance is essential for designers. the oscillator error? How does multiplying by a squared-up Unfortunately, the necessary information is spread thinly across oscillator signal instead of a sinusoidal signal change a mixer’s the published literature and textbooks with widely varying notations and some critical disconnects. This paper addresses this behavior and response to oscillator error? problem by presenting a comprehensive one-stop explanation of Another obstacle to learning the material is that there are how oscillator error is quantified, simulated, and measured in three distinct oscillator error metrics in common use: phase practice, and the effects of oscillator error in typical oscillator error, jitter, and frequency stability. Each metric offers advan- applications. tages in certain applications, so it is important to understand Index Terms— Oscillator phase error, phase noise, jitter, how they relate to each other, yet with the exception of [1], frequency stability, Allan variance, frequency synthesizer, crystal, the authors are not aware of prior publications that provide phase-locked loop (PLL). -
AN279: Estimating Period Jitter from Phase Noise
AN279 ESTIMATING PERIOD JITTER FROM PHASE NOISE 1. Introduction This application note reviews how RMS period jitter may be estimated from phase noise data. This approach is useful for estimating period jitter when sufficiently accurate time domain instruments, such as jitter measuring oscilloscopes or Time Interval Analyzers (TIAs), are unavailable. 2. Terminology In this application note, the following definitions apply: Cycle-to-cycle jitter—The short-term variation in clock period between adjacent clock cycles. This jitter measure, abbreviated here as JCC, may be specified as either an RMS or peak-to-peak quantity. Jitter—Short-term variations of the significant instants of a digital signal from their ideal positions in time (Ref: Telcordia GR-499-CORE). In this application note, the digital signal is a clock source or oscillator. Short- term here means phase noise contributions are restricted to frequencies greater than or equal to 10 Hz (Ref: Telcordia GR-1244-CORE). Period jitter—The short-term variation in clock period over all measured clock cycles, compared to the average clock period. This jitter measure, abbreviated here as JPER, may be specified as either an RMS or peak-to-peak quantity. This application note will concentrate on estimating the RMS value of this jitter parameter. The illustration in Figure 1 suggests how one might measure the RMS period jitter in the time domain. The first edge is the reference edge or trigger edge as if we were using an oscilloscope. Clock Period Distribution J PER(RMS) = T = 0 T = TPER Figure 1. RMS Period Jitter Example Phase jitter—The integrated jitter (area under the curve) of a phase noise plot over a particular jitter bandwidth. -
End-To-End Deep Learning for Phase Noise-Robust Multi-Dimensional Geometric Shaping
MITSUBISHI ELECTRIC RESEARCH LABORATORIES https://www.merl.com End-to-End Deep Learning for Phase Noise-Robust Multi-Dimensional Geometric Shaping Talreja, Veeru; Koike-Akino, Toshiaki; Wang, Ye; Millar, David S.; Kojima, Keisuke; Parsons, Kieran TR2020-155 December 11, 2020 Abstract We propose an end-to-end deep learning model for phase noise-robust optical communications. A convolutional embedding layer is integrated with a deep autoencoder for multi-dimensional constellation design to achieve shaping gain. The proposed model offers a significant gain up to 2 dB. European Conference on Optical Communication (ECOC) c 2020 MERL. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Mitsubishi Electric Research Laboratories, Inc. 201 Broadway, Cambridge, Massachusetts 02139 End-to-End Deep Learning for Phase Noise-Robust Multi-Dimensional Geometric Shaping Veeru Talreja, Toshiaki Koike-Akino, Ye Wang, David S. Millar, Keisuke Kojima, Kieran Parsons Mitsubishi Electric Research Labs., 201 Broadway, Cambridge, MA 02139, USA., [email protected] Abstract We propose an end-to-end deep learning model for phase noise-robust optical communi- cations. -
Receiver Sensitivity and Equivalent Noise Bandwidth Receiver Sensitivity and Equivalent Noise Bandwidth
11/08/2016 Receiver Sensitivity and Equivalent Noise Bandwidth Receiver Sensitivity and Equivalent Noise Bandwidth Parent Category: 2014 HFE By Dennis Layne Introduction Receivers often contain narrow bandpass hardware filters as well as narrow lowpass filters implemented in digital signal processing (DSP). The equivalent noise bandwidth (ENBW) is a way to understand the noise floor that is present in these filters. To predict the sensitivity of a receiver design it is critical to understand noise including ENBW. This paper will cover each of the building block characteristics used to calculate receiver sensitivity and then put them together to make the calculation. Receiver Sensitivity Receiver sensitivity is a measure of the ability of a receiver to demodulate and get information from a weak signal. We quantify sensitivity as the lowest signal power level from which we can get useful information. In an Analog FM system the standard figure of merit for usable information is SINAD, a ratio of demodulated audio signal to noise. In digital systems receive signal quality is measured by calculating the ratio of bits received that are wrong to the total number of bits received. This is called Bit Error Rate (BER). Most Land Mobile radio systems use one of these figures of merit to quantify sensitivity. To measure sensitivity, we apply a desired signal and reduce the signal power until the quality threshold is met. SINAD SINAD is a term used for the Signal to Noise and Distortion ratio and is a type of audio signal to noise ratio. In an analog FM system, demodulated audio signal to noise ratio is an indication of RF signal quality. -
AN10062 Phase Noise Measurement Guide for Oscillators
Phase Noise Measurement Guide for Oscillators Contents 1 Introduction ............................................................................................................................................. 1 2 What is phase noise ................................................................................................................................. 2 3 Methods of phase noise measurement ................................................................................................... 3 4 Connecting the signal to a phase noise analyzer ..................................................................................... 4 4.1 Signal level and thermal noise ......................................................................................................... 4 4.2 Active amplifiers and probes ........................................................................................................... 4 4.3 Oscillator output signal types .......................................................................................................... 5 4.3.1 Single ended LVCMOS ........................................................................................................... 5 4.3.2 Single ended Clipped Sine ..................................................................................................... 5 4.3.3 Differential outputs ............................................................................................................... 6 5 Setting up a phase noise analyzer ...........................................................................................................