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Waveos User Guide
WAVEOS USER GUIDE DTUS070 rev A.5 – December, 2016 Page 2 / 273 COPYRIGHT (©) ACKSYS 2016-2017 This document contains information protected by Copyright. The present document may not be wholly or partially reproduced, transcribed, stored in any computer or other system whatsoever, or translated into any language or computer language whatsoever without prior written consent from ACKSYS Communications & Systems - ZA Val Joyeux – 10, rue des Entrepreneurs - 78450 VILLEPREUX - FRANCE. REGISTERED TRADEMARKS ® Ø ACKSYS is a registered trademark of ACKSYS. Ø Linux is the registered trademark of Linus Torvalds in the U.S. and other countries. Ø CISCO is a registered trademark of the CISCO company. Ø Windows is a registered trademark of MICROSOFT. Ø WireShark is a registered trademark of the Wireshark Foundation. Ø HP OpenView® is a registered trademark of Hewlett-Packard Development Company, L.P. Ø VideoLAN, VLC, VLC media player are internationally registered trademark of the French non-profit organization VideoLAN. DISCLAIMERS ACKSYS ® gives no guarantee as to the content of the present document and takes no responsibility for the profitability or the suitability of the equipment for the requirements of the user. ACKSYS ® will in no case be held responsible for any errors that may be contained in this document, nor for any damage, no matter how substantial, occasioned by the provision, operation or use of the equipment. ACKSYS ® reserves the right to revise this document periodically or change its contents without notice. DTUS070 rev A.5 – December, 2016 Page 3 / 273 REGULATORY INFORMATION AND DISCLAIMERS Installation and use of this Wireless LAN device must be in strict accordance with local regulation laws and with the instructions included in the user documentation provided with the product. -
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. -
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. -
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. -
High Frequency (HF)
Calhoun: The NPS Institutional Archive Theses and Dissertations Thesis Collection 1990-06 High Frequency (HF) radio signal amplitude characteristics, HF receiver site performance criteria, and expanding the dynamic range of HF digital new energy receivers by strong signal elimination Lott, Gus K., Jr. Monterey, California: Naval Postgraduate School http://hdl.handle.net/10945/34806 NPS62-90-006 NAVAL POSTGRADUATE SCHOOL Monterey, ,California DISSERTATION HIGH FREQUENCY (HF) RADIO SIGNAL AMPLITUDE CHARACTERISTICS, HF RECEIVER SITE PERFORMANCE CRITERIA, and EXPANDING THE DYNAMIC RANGE OF HF DIGITAL NEW ENERGY RECEIVERS BY STRONG SIGNAL ELIMINATION by Gus K. lott, Jr. June 1990 Dissertation Supervisor: Stephen Jauregui !)1!tmlmtmOlt tlMm!rJ to tJ.s. eave"ilIE'il Jlcg6iielw olil, 10 piolecl ailicallecl",olog't dU'ie 18S8. Btl,s, refttteste fer litis dOCdiii6i,1 i'lust be ,ele"ed to Sapeihil6iiddiil, 80de «Me, "aial Postg;aduulG Sclleel, MOli'CIG" S,e, 98918 &988 SF 8o'iUiid'ids" PM::; 'zt6lI44,Spawd"d t4aoal \\'&u 'al a a,Sloi,1S eai"i,al'~. 'Nsslal.;gtePl. Be 29S&B &198 .isthe 9aleMBe leclu,sicaf ,.,FO'iciaKe" 6alite., ea,.idiO'. Statio", AlexB •• d.is, VA. !!!eN 8'4!. ,;M.41148 'fl'is dUcO,.Mill W'ilai.,s aliilical data wlrose expo,l is idst,icted by tli6 Arlil! Eurse" SSPItial "at FRIis ee, 1:I.9.e. gec. ii'S1 sl. seq.) 01 tlls Exr;01l ftle!lIi"isllatioli Act 0' 19i'9, as 1tI'I'I0"e!ee!, "Filill ell, W.S.€'I ,0,,,,, 1i!4Q1, III: IIlIiI. 'o'iolatioils of ltrese expo,lla;;s ale subject to 960616 an.iudl pSiiaities. -
Noise Is Widespread
NoiseNoise A definition (not mine) Electrical Noise S. Oberholzer and E. Bieri (Basel) T. Kontos and C. Hoffmann (Basel) A. Hansen and B-R Choi (Lund and Basel) ¾ Electrical noise is defined as any undesirable electrical energy (?) T. Akazaki and H. Takayanagi (NTT) E.V. Sukhorukov and D. Loss (Basel) C. Beenakker (Leiden) and M. Büttiker (Geneva) T. Heinzel and K. Ensslin (ETHZ) M. Henny, T. Hoss, C. Strunk (Basel) H. Birk (Philips Research and Basel) Effect of noise on a signal. (a) Without noise (b) With noise ¾ we like it though (even have a whole conference on it) National Center on Nanoscience Swiss National Science Foundation 1 2 Noise may have been added to by ... Introduction: Noise is widespread Noise (audio, sound, HiFi, encodimg, MPEG) Electrical Noise Noise (industrial, pollution) Noise (in electronic circuits) Noise (images, video, encoding) Noise (environment, pollution) it may be in the “source” signal from the start Noise (radio) it may have been introduced by the electronics Noise (economic => theory of pricing with fluctuating it may have been added to by the envirnoment source terms) it may have been generated in your computer Noise (astronomy, big-bang, cosmic background) Noise figure Shot noise Thermal noise for the latter, e.g. sampling noise Quantum noise Neuronal noise Standard quantum limit and more ... 3 4 Introduction: Noise is widespread Introduction (Wikipedia) Noise (audio, sound, HiFi, encodimg, MPEG) Electronic Noise (from Wikipedia) Noise (industrial, pollution) Noise (in electronic circuits) Noise (images, video, encoding) Electronic noise exists in any electronic circuit as a result of random variations in current or voltage caused by the random movement of the Noise (environment, pollution) electrons carrying the current as they are jolted around by thermal energy.energy Noise (radio) The lower the temperature the lower is this thermal noise. -
Understanding Noise Figure
Understanding Noise Figure Iulian Rosu, YO3DAC / VA3IUL, http://www.qsl.net/va3iul One of the most frequently discussed forms of noise is known as Thermal Noise. Thermal noise is a random fluctuation in voltage caused by the random motion of charge carriers in any conducting medium at a temperature above absolute zero (K=273 + °Celsius). This cannot exist at absolute zero because charge carriers cannot move at absolute zero. As the name implies, the amount of the thermal noise is to imagine a simple resistor at a temperature above absolute zero. If we use a very sensitive oscilloscope probe across the resistor, we can see a very small AC noise being generated by the resistor. • The RMS voltage is proportional to the temperature of the resistor and how resistive it is. Larger resistances and higher temperatures generate more noise. The formula to find the RMS thermal noise voltage Vn of a resistor in a specified bandwidth is given by Nyquist equation: Vn = 4kTRB where: k = Boltzmann constant (1.38 x 10-23 Joules/Kelvin) T = Temperature in Kelvin (K= 273+°Celsius) (Kelvin is not referred to or typeset as a degree) R = Resistance in Ohms B = Bandwidth in Hz in which the noise is observed (RMS voltage measured across the resistor is also function of the bandwidth in which the measurement is made). As an example, a 100 kΩ resistor in 1MHz bandwidth will add noise to the circuit as follows: -23 3 6 ½ Vn = (4*1.38*10 *300*100*10 *1*10 ) = 40.7 μV RMS • Low impedances are desirable in low noise circuits. -
Managing Noise and Preventing Hearing Loss at Work Code of Practice 2021 Page 2 of 54
Managing noise and preventing hearing loss at work Code of Practice 2021 PN12640 ISBN Creative Commons This copyright work is licensed under a Creative Commons Attribution-Noncommercial 4.0 International licence. To view a copy of this licence, visit creativecommons.org/licenses. In essence, you are free to copy, communicate and adapt the work for non-commercial purposes, as long as you attribute the work to Safe Work Australia and abide by the other licence terms. Managing noise and preventing hearing loss at work Code of Practice 2021 Page 2 of 54 Contents Foreword ................................................................................................................................... 4 1. Introduction ........................................................................................................................ 5 1.1 Who has health and safety duties in relation to noise? .......................................... 5 1.2 What is involved in managing noise and preventing hearing loss?........................ 7 1.3 Information, training, instruction and supervision ................................................... 8 2. Noise and its effects on health and safety ..................................................................... 9 2.1 How does hearing loss occur? ................................................................................ 9 2.2 How much noise is too much? ................................................................................ 9 2.3 Other effects of noise............................................................................................ -
Impact of Power Line Telecommunication Systems on Radiocommunication Systems Operating in the LF, MF, HF and VHF Bands Below 80 Mhz
Report ITU-R SM.2158 (09/2009) Impact of power line telecommunication systems on radiocommunication systems operating in the LF, MF, HF and VHF bands below 80 MHz SM Series Spectrum management ii Rep. ITU-R SM.2158 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio-frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Annex 1 of Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http://www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Reports (Also available online at http://www.itu.int/publ/R-REP/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management Note: This ITU-R Report was approved in English by the Study Group under the procedure detailed in Resolution ITU-R 1. -
Chapter 11 Noise and Noise Rejection
CHAPTER 11 NOISE AND NOISE REJECTION INTRODUCTION In general, noise is any unsteady component of a signal which causes the instantaneous value to differ from the true value. (Finite response time effects, leading to dynamic error, are part of an instrument's response characteristics and are not considered to be noise.) In electrical signals, noise often appears as a highly erratic component superimposed on the desired signal. If the noise signal amplitude is generally lower than the desired signal amplitude, then the signal may look like the signal shown in Figure 1. Figure 1: Sinusoidal Signal with Noise. Noise is often random in nature and thus it is described in terms of its average behavior (see the last section of Chapter 8). In particular we describe a random signal in terms of its power spectral density, (x (f )) , which shows how the average signal power is distributed over a range of frequencies, or in terms of its average power, or mean square value. Since we assume the average signal power to be the power dissipated when the signal voltage is connected across a 1 Ω resistor, the numerical values of signal power and signal mean square value are equal, only the units differ. To determine the signal power we can use either the time history or the power spectral density (Parseval's Theorem). Let the signal be x(t), then the average signal power or mean square voltage is: T t 2 221 x(t) x(t)dtx (f)df (1) T T t 0 2 11-2 Note: the bar notation, , denotes a time average taken over many oscillations of the signal. -
Radiomic: Sound Sensing Via Mmwave Signals
RadioMic: Sound Sensing via mmWave Signals Muhammed Zahid Ozturk Chenshu Wu [email protected] [email protected] University of Maryland University of Maryland College Park, USA College Park, USA Origin Wireless Inc. Origin Wireless Inc. Greenbelt, USA Greenbelt, USA Beibei Wang K. J. Ray Liu [email protected] [email protected] University of Maryland University of Maryland College Park, USA College Park, USA Origin Wireless Inc. Origin Wireless Inc. Greenbelt, USA Greenbelt, USA ABSTRACT Soundproof wall Noisy room Quiet room UWHear Voice interfaces has become an integral part of our lives, with WaveEar the proliferation of smart devices. Today, IoT devices mainly RadioMic rely on microphones to sense sound. Microphones, however, have fundamental limitations, such as weak source separa- tion, limited range in the presence of acoustic insulation, and Mixed sounds Music only being prone to multiple side-channel attacks. In this paper, RadioMic Figure 1: An illustrative scenario of RadioMic we propose RadioMic, a radio-based sound sensing system to mitigate these issues and enrich sound applications. Ra- dioMic constructs sound based on tiny vibrations on active sources (e.g., a speaker or human throat) or object surfaces (e.g., paper bag), and can work through walls, even a sound- proof one. To convert the extremely weak sound vibration in the radio signals into sound signals, RadioMic introduces smart speakers like Amazon Alexa or Google Home can now radio acoustics, and presents training-free approaches for ro- understand user voices, control IoT devices, monitor the envi- bust sound detection and high-fidelity sound recovery. It then ronment, and sense sounds of interest such as glass breaking exploits a neural network to further enhance the recovered or smoke detectors, all currently using microphones as the sound by expanding the recoverable frequencies and reduc- primary interface. -
Preprocessing for Extracting Signal Buried in Noise Using Labview
Preprocessing for Extracting Signal Buried in Noise Using LabVIEW A Thesis report submitted towards the partial fulfillment of the requirements of the degree of Master of Engineering in Electronics Instrumentation and Control Engineering submitted by Nitish Sharma Roll No-800851013 Under the supervision of Dr. Yaduvir Singh Associate Professor, EIED and Dr. Hardeep Singh Assistant Professor, ECED DEPARTMENT OF ELECTRICAL AND INSTRUMENTATION ENGINEERING THAPAR UNIVERSITY PATIALA –– 147004 JULY 2010 i ii ABSTRACT Digital signals are used everywhere in the world around us due to its superior fidelity, noise reduction, and signal processing flexibility to remove noise and extract useful information. This unwanted electrical or electromechanical energy that distort the signal quality is known as noise, it can block, distort change or interfere with the meaning of a message in both human and electronic communication. Engineers are constantly striving to develop better ways to deal with noise disturbances as it leads to loss of useful information. The traditional method has been used to minimize the signal bandwidth to the greatest possible extent. However reducing the bandwidth limits the maximum speed of the data than can be delivered. Another, more recently developed scheme for minimizing the effect of noise is called digital signal processing. Digital filters are very much more versatile in their ability to process signals in a variety of ways and can handle low frequency signals accurately; this includes the ability of some types of digital filter to adapt to changes in the characteristics of the signal. Fast DSP processors can handle complex combinations of filters in parallel or cascade (series), making the hardware requirements relatively simple and compact in comparison with the equivalent analog circuitry.