C TECHNICA ACTA A B C D E F G CHARGEDOMAIN SAMPLING OF HIGHFREQUENCY SIGNALS WITH EMBEDDED FILTERING. Sami Karvonen C 233 ACTA C 233.


 Anastasia Brooks
 2 years ago
 Views:
Transcription
1 C233etukansi.fm Page 1 Friday, December 23, :22 AM C 233 OULU 2006 UNIVERSITY OF OULU P.O. Box 7500 FI UNIVERSITY OF OULU FINLAND U N I V E R S I TAT I S S E R I E S SCIENTIAE RERUM NATURALIUM Professor Mikko Siponen HUMANIORA Professor Harri Mantila TECHNICA Professor Juha Kostamovaara ACTA U N I V E R S I T AT I S O U L U E N S I S Sami Karvonen E D I T O R S Sami Karvonen A B C D E F G O U L U E N S I S ACTA A C TA C 233 CHARGEDOMAIN SAMPLING OF HIGHFREQUENCY SIGNALS WITH EMBEDDED FILTERING MEDICA Professor Olli Vuolteenaho SCIENTIAE RERUM SOCIALIUM Senior assistant Timo Latomaa SCRIPTA ACADEMICA Communications Officer Elna Stjerna OECONOMICA Senior Lecturer Seppo Eriksson EDITOR IN CHIEF Professor Olli Vuolteenaho EDITORIAL SECRETARY Publication Editor Kirsti Nurkkala ISBN (nid.) ISBN (PDF) ISSN FACULTY OF TECHNOLOGY, DEPARTMENT OF ELECTRICAL AND INFORMATION ENGINEERING, UNIVERSITY OF OULU C TECHNICA
2
3 ACTA UNIVERSITATIS OULUENSIS C Technica 233 SAMI KARVONEN CHARGEDOMAIN SAMPLING OF HIGHFREQUENCY SIGNALS WITH EMBEDDED FILTERING Academic Dissertation to be presented with the assent of the Faculty of Technology, University of Oulu, for public discussion in Raahensali (Auditorium L 10), Linnanmaa, on January 27th, 2006, at 12 noon OULUN YLIOPISTO, OULU 2006
4 Copyright 2006 Acta Univ. Oul. C 233, 2006 Supervised by Professor Juha Kostamovaara Reviewed by Professor Saska Lindfors Professor Jiren Yuan ISBN (nid.) ISBN (PDF) ISSN OULU UNIVERSITY PRESS OULU 2006
5 Karvonen, Sami, Chargedomain sampling of highfrequency signals with embedded filtering Faculty of Technology, University of Oulu, P.O.Box 4000, FIN University of Oulu, Finland, Department of Electrical and Information Engineering, University of Oulu, P.O.Box 4500, FIN University of Oulu, Finland Acta Univ. Oul. C 233, 2006 Oulu, Finland Abstract Subsampling can be used in a radio receiver to perform signal downconversion and sampleandhold operations in order to relieve the operation frequency and bandwidth requirements of the subsequent discretetime circuitry. However, due to the inherent aliasing behaviour of wideband noise and interference in subsampling, and the difficulty of implementing appropriate bandpass antialiasing filtering at high frequencies, straightforward use of a low subsampling rate can result in significant degradation of the receiver dynamic range. The aim of this thesis is to investigate and implement methods for integrating filtering into highfrequency signal sampling and downconversion by subsampling to alleviate the requirements for additional frontend filters and to mitigate the effects of noise and outofband signal aliasing, thereby facilitating use in integrated highquality radio receivers. The chargedomain sampling technique studied here allows simple integration of both continuousand discretetime filtering functions into highfrequency signal sampling. Gated current integration results in a lowpass sin(x)/x(sinc(x)) response capable of performing builtin antialiasing filtering in baseband signal sampling. Weighted integration of several successive current samples can be further used to obtain an embedded discretetime finiteimpulseresponse (FIR) filtering response, which can be used for internal antialiasing and imagerejection filtering in the downconversion of bandpass signals by subsampling. The detailed analysis of elementary chargedomain sampling circuits presented here shows that the use of integrated FIR filtering with subsampling allows acceptable noise figures to be achieved and can provide effective internal antialiasing rejection. The new methods for increasing the selectivity of elementary chargedomain sampling circuits presented here enable the integration of advanced, digitally programmable FIR filtering functions into highfrequency signal sampling, thereby markedly relieving the requirements for additional antialiasing, image rejection and possibly even channel selection filters in a radio receiver. BiCMOS and CMOS IF sampler implementations are presented in order to demonstrate the feasibility of the chargedomain sampling technique for integrated antialiasing and imagerejection filtering in IF signal quadrature downconversion by subsampling. Circuit measurements show that this sampling technique for builtin filtering results in an accurate frequency response and allows the use of high subsampling ratios while still achieving a competitive dynamic range. Keywords: chargedomain, FIR filtering, quadrature downconversion, radio receivers, sampling, subsampling
6 Acknowledgements This thesis is based on research work carried out at the Electronics Laboratory of the Department of Electrical and Information Engineering, University of Oulu, during the years I wish to express my deepest gratitude to Professor Juha Kostamovaara, who has supervised this work, for his encouragement and guidance. I also thank my colleagues at the Electronics Laboratory for the pleasant working atmosphere and for their assistance. My family, relatives and friends deserve my warmest thanks for their support and patience during these years. I wish to thank professors Saska Lindfors and Jiren Yuan for examining this thesis, and Mr. Malcolm Hicks for revising the English of the manuscript. This work has been supported financially by the Graduate School in Electronics, Telecommunications and Automation (GETA) and the Academy of Finland, and the foundations Seppo Säynäjäkankaan tiedesäätiö, Tauno Tönningin säätiö, Emil Aaltosen säätiö, Nokia Oyj:n säätiö, Ulla Tuomisen säätiö, and PohjoisPohjanmaan rahasto, all of which are gratefully acknowledged. Oulu, December 2005 Sami Karvonen
7
8 List of original publications This thesis consists of an overview and the following seven publications: I II Karvonen S, Riley T & Kostamovaara J (2001) A low noise quadrature subsampling mixer. Proceedings of the International Symposium on Circuits and Systems (ISCAS'2001), Sydney, Australia, 4: Karvonen S, Riley T & Kostamovaara J (2002) Charge sampling mixer with ΔΣ quantized impulse response. Proceedings of the International Symposium on Circuits and Systems (ISCAS 2002), Phoenix, Arizona, USA, May 2002, 1: III Karvonen S, Riley T & Kostamovaara J (2003) On the effects of timing jitter in charge sampling. Proceedings of the International Symposium on Circuits and Systems (ISCAS 2003), Bangkok, Thailand, May 2528, 2003, 1: IV Karvonen S, Riley T & Kostamovaara J (2003) Highly linear Gm cell for high frequency applications. Proceedings of the Midwest Symposium on Circuits and Systems (MWSCAS 2003), Cairo, Egypt, Dec , 1: V Karvonen S, Riley T & Kostamovaara J (2005) A CMOS quadrature chargedomain sampling circuit with 66dB SFDR up to 100 MHz. IEEE Transactions on Circuits and Systems I: Regular Papers, 52(2): VI Karvonen S, Riley T, Kurtti S & Kostamovaara J (2005) A quadrature chargedomain sampler with embedded FIR and IIR filtering functions. Accepted for publication to IEEE Journal of SolidState Circuits in June, VII Karvonen S, Riley T & Kostamovaara J (2005) Chargedomain FIR sampler with programmable filtering coefficients. Accepted for publication to IEEE Transactions on Circuits and Systems II: Brief Papers in August, All the above publications were written by the author, who was also responsible for most of the work behind the papers. The design for the test circuit presented in Paper VI was done jointly by Thomas Riley, M.Sc., Sami Kurtti, M.Sc., and the author. The author performed all the measurements on the circuit. Thomas Riley also contributed to the
9 profound ideas on the circuit techniques described in Papers I, II, IV, V, and VI. These ideas were further developed by the author.
10 List of symbols and abbreviations A/D analogueuetodigital BiCMOS bipolar CMOS, a semiconductor process containing both bipolar and CMOS transistors BW signal bandwidth CCD chargecoupled device CMOS complementary metaloxide semiconductor process containing both NMOS and PMOS transistors CMU current multiplier unit CR capacitorresistor CT continuoustime DT discretetime FIR finiteimpulseresponse GSM Groupe Spécial Mobile, Global System for Mobile Communications GBW gainbandwidth product I real channel IIR infiniteimpulseresponse IF intermediate frequency IMR image rejection ratio LO local oscillator LSB least significant bit MOS metaloxide semiconductor MSB most significant bit NF noise figure NMOS nchannel MOS OSR oversampling ratio PMOS pchannel MOS Q imaginary channel rms root mean square SC switchedcapacitor SFDR spuriousfree dynamic range
11 SiGe SNR RC RGC RF RX T THD A A 0 C in C o C s f B f c f p f s f s,fir G m h k k N N in N out R o R sw T f T i T s V in V out Z o σ t τ ω t silicongermanium signaltonoise ratio resistorcapacitor regulated cascode circuit structure radio frequency receive band temperature on the Kelvin scale total harmonic distortion input signal amplitude amplifier dc gain opamp input capacitance transconductance cell output capacitance sampling capacitance bandpass signal bandwidth bandpass signal or filter center frequency amplifier 3dB bandwidth (output) sampling frequency builtin FIR filter sampling frequency transconductance FIR filter tap coefficient for sample k Boltzmann s constant, integer FIR filter impulse response length input noise power output noise power transconductance cell output resistance sampling switch onresistance embedded FIR filter sampling period integration period sampling period input voltage signal output voltage signal output impedance standard deviation of timing jitter integrator dominant time constant opamp unitygain angular frequency
12 Contents Abstract Acknowledgements List of original publications List of symbols and abbreviations Contents 1 Introduction Motivation and aim of the research Organization of the thesis Subsampling circuits Frequency downconversion by subsampling Problems of subsampling Chargedomain sampling circuits Integrative chargedomain sampling Chargedomain sampling with embedded FIR filtering Elementary chargedomain FIR sampler configurations Contributions Publications Performance aspects and further developments Frequency response of chargedomain samplers Noise performance of chargedomain samplers Noise sampled during the integration phase Noise sampled during the reset phase Total sampled output noise and output SNR FIR sampler noise figure Further developments Discussion Conclusions...75 References Appendices
13
14 1 Introduction 1.1 Motivation and aim of the research The increasing of radio receiver integration level has been under intensive research for over a decade. The wellknown advantages of increased integration lie in lower manufacturing costs due to the smaller circuit area, and in the reduced need for external discrete components, usually also leading to decreased overall power consumption, which is especially important for handheld devices. Several new architectural solutions have been presented [1], [2], and already mature topologies, such as the direct conversion receiver, have been reused along with sensible circuitlevel solutions [3] to overcome the problems associated with the low integration level of traditional heterodyne receivers. The use of these architectures, along with conventional continuoustime (CT) analogue circuit design techniques, such as multiplying mixers, variable gain amplifiers and CT baseband filters, has resulted in highlyintegrated receiver chip implementations for widely used mobile phone standards such as GSM [4]. Receiver topologies based fundamentally on analogue signal processing nevertheless often require advanced technologies such as BiCMOS/SiGe BiCMOS for successful implementation, and may possess poor scalability for integration in the most modern submicrometer CMOS processes, which are required for costefficient realization of the baseband signal processing functions in the receiver [5]. A different, very straightforward solution for increasing the receiver integration level is to transfer the signal sampling and analoguetodigital (A/D) interface from the baseband to higher frequencies, i.e. to an IF, or optimally directly to RF, and to use a highspeed A/D converter to enable further signal processing to take place in the digital domain. As an inherent advantage, digital signal processing allows elimination of the nonidealities of analogue signal processing, such as device noise and nonlinearities, and of component mismatches. Technological progress towards diminished transistor feature size, especially in pure CMOS processes, also favours an increased level of digital signal processing in receiver implementation, since increasing switching speeds of MOS transistors allow dense integration of large amounts of highspeed digital logic on the same chip with the receiver frontend [5],[6],[7]. A fully softwaredefined radio [8], and even a partially programmable radio supporting multiple wireless standards would directly benefit from radio
15 14 architectures based mostly on digital signal processing and digital controllability. However, the brute force method of implementing a highresolution bandpass A/D converter at a high frequency not only imposes very demanding requirements on the dynamic range of the converter, but usually also results in markedly increased overall power dissipation in the receiver. Instead of directly converting a highfrequency bandpass signal into digital form, a subsampling frontend can be used to simultaneously perform the tasks of frequency downconversion and sampleandhold operation prior to A/D conversion at the downconverted frequency [9]. Since the operation frequency of discretetime (DT) signal processing blocks following the frontend sampler is decreased and their bandwidth constraints are relieved, the use of a subsampling downconverter can lead to decreased overall power dissipation but still allow the use of mostly discretetime and digital signal processing techniques to achieve a high integrability in an advanced CMOS technology. It has proved difficult, however, to realize the required appropriate bandpass antialiasing filtering and obtain adequate noise performance in highfrequency operation with conventional straightforward implementations of subsampling circuits [10], which has prevented their use in demanding wireless applications. The aim of this thesis is to investigate and implement methods for integrating filtering into highfrequency signal sampling and subsampling downconversion operation in order to mitigate the effects of noise and outofband signal aliasing and to relieve the requirements for additional CT antialiasing filters prior to the sampler, thereby enabling its use in highlyintegrated highquality radio receivers. The thesis specifically concentrates on a sampling technique based on gated integration of the signal current, or the accumulation of charge samples into a sampling capacitor and on the further processing of the integrated samples to create various DT filtering functions embedded into the sampling operation. In addition to internal antialiasing filtering, the chargedomain sampling technique investigated here can also be used for complex and imagerejection filtering to enable quadrature (I/Q) downconversion by subsampling, and, furthermore, even for partial channel selection filtering to relieve the requirements for additional subsequent filters in a radio receiver chain. 1.2 Organization of the thesis The thesis is organized as follows. The principle of frequency downconversion by subsampling is presented in Chapter 2, the latter part of which is devoted to discussing problems related to realizing adequate antialiasing filtering and achieving a high dynamic range with conventional elementary subsampling circuits. Chapter 3 presents the fundamentals of the chargedomain sampling technique and describes how the technique can be utilized to implement elementary antialiasing and imagerejection filtering functions embedded into highfrequency signal sampling and subsampling downconversion operation. The first part of Chapter 4 presents briefly the contents and contributions of the original publications, and the latter part discusses the performance of chargedomain sampling circuits in detail and provides some further developments and clarifications to the ideas described in the original papers. A discussion is given in Chapter 5, and the final conclusions are drawn in Chapter 6.
16 2 Subsampling circuits 2.1 Frequency downconversion by subsampling The wellknown Nyquist criterion sets the condition for a usable sampling rate for baseband (i.e. lowpass) signals. The minimum sampling frequency in baseband sampling is given by f s,min =2f B, where f B is the bandwidth of the baseband signal. The Nyquist criterion ensures that the spectral images of the sampled signal will not overlap in the frequency domain. In addition, since the whole frequency axis will be mapped onto the frequency region [f s /2, f s /2] in the sampling process, limiting of the input bandwidth of a lowpass sampler will prevent signals with frequencies higher than the Nyquist frequency f N =f s /2 from folding on top of the desired baseband signal, causing degradation in the signaltonoise ratio (SNR) of the sampled signal. In a practical radio receiver chain, the input bandwidth of the baseband sampler can be limited by a CT lowpass antialiasing filter that simultaneously acts as a channel selection filter prior to A/D conversion [4]. Due to operation at low frequencies, the required stopband attenuation is usually relatively easy to achieve with integrated filters. If necessary, it is possible to sample the signal at a higher rate than f s,min, i.e. to use some amount of oversampling, to further relieve the stopband suppression requirement for the lowpass antialiasing filter. In order to profit to a maximal extent from the benefits of digital signal processing, the received analogue signal should be digitized as early as possible in the receiver chain. However, transferring the A/D interface directly from the baseband to higher frequencies, e.g. to a high IF, by following the Nyquist criterion for lowpass signals would markedly increase the bandwidth and sampling frequency requirements of the A/D converter. In addition, since the bandwidth of a modulated bandpass signal is usually a fraction of its center frequency, this approach seems highly inefficient, as it is in principle advantageous to use a sampling frequency which is only twice the information bandwidth. Unlike baseband sampling circuits, downconversion circuits based on subsampling take advantage of the spectral aliasing resulting from violation of the Nyquist condition for baseband signals. The subsampling downconversion operation of a realvalued bandlimited bandpass signal is illustrated in Fig. 1.
17 16 f BW s 2 x(t) x(nt s ) (a) t=nt s X(f) f B (k+1)f s (k+½)f s f c kf s f s f s kf s f c (k+½)f s (k+1)f s f (b) f 0 X(e j2πfnts ) (k+½)f s f c kf s 3f s /2 f s f s /2 f 0 f 0 f s /2 f s 3f s /2 kf s f c (k+½)f s f (c) Fig. 1. Downconversion of a bandlimited realvalued bandpass signal by subsampling. (a) Subsampler block diagram. (b) Spectrum of the bandlimited bandpass signal. (c) Spectrum of the subsampled signal. As with a baseband sampler, the input bandwidth of a subsampler must also be limited by an antialiasing filter. In subsampling, however, a bandpass filter is used to select the desired signal band around a desired center frequency f c prior to the sampling operation. The spectrum of the bandlimited realvalued bandpass signal is shown in Fig. 1 (b). As a result of sampling at a rate lower than twice the highest frequency component of the bandpass input signal, the signal spectrum is downconverted to a new, lower center frequency f 0 =f c kf s and is replicated in the frequency domain at intervals of the subsampling frequency f s. It is easy to conclude from the idealized spectrum of the subsampled signal shown in Fig. 1 (c) that, in order to avoid overlapping of the spectral replicas and thereby degradation of the receiver SNR, the bandwidth of a realvalued bandpass signal must theoretically be strictly limited to f B f s /2. In addition, the center frequency f c of the signal must be selected so that its lower f L =f c f B /2 and higher f H =f c +f B /2 band edges reside in between two adjacent multiples of half of the sampling frequency f s /2. The condition for the appropriate f s can be formulated mathematically as [11] 2f H k f 2f L s k , (1)
18 17 where k= 1,..., f H f B. The notation x denotes the largest integer x. It should be emphasized that without the proper bandpass antialiasing filtering, any unwanted signal, including noise and interference, situated at the frequency kf s ±f 0, k=integer, would be downconverted on top of the wanted signal due to subsampling. In general, for all modulated bandpass signals excluding simple amplitude modulation, the generation of quadrature, i.e. real (I) and imaginary (Q), components is required at the latest in conjunction with downconversion to dc in order to avoid information loss due to overlapping of the signal s negative and positive frequency content. In subsampling downconversion of realvalued bandpass signals, overlapping of the negative and positive frequency components is avoided by performing downconversion to a new center frequency near dc and by selecting the sampling frequency appropriately according to (1). The generation of quadrature components prior to downconversion by subsampling, or within the subsampling operation itself, enables direct downconversion to dc and simultaneous ideal extension of the bandwidth of the bandpass signal to be equal to the subsampling frequency. Direct downconversion of a bandlimited bandpass signal to dc by subsampling is illustrated in Fig. 2. BW f s Hilbert transform/ complex filtering t=nt s x I (nt s ) x(t) x c (t)=x I (t)+jx Q (t) π Δφ = 2 x c (nt s )=x I (nt s )+jx Q (nt s ) t=nt s x Q (nt s ) (a) X(f) f B X c (f) f c f c =kf s f (b) f c f s f s f c =kf s f (c) X c (e j2πfnts ) f c =kf s 3f s /2 f s f s /2 f s /2 f s 3f s /2 f c =kf s f (d) Fig. 2. Quadrature downconversion of a bandlimited realvalued bandpass signal by subsampling. (a) Subsampler block diagram. (b) Bandlimited realvalued bandpass signal. (c) Complex bandpass signal. (d) Spectrum of the subsampled complex signal.
19 18 The realvalued bandlimited bandpass signal x(t) of Fig. 2 (b) is translated into a complex bandpass, also known as analytic, signal x c (t) in Fig. 2 (c) by suppressing the negative (i.e. image band) frequency content of the signal. A perfect attenuation of the image signal components could ideally be achieved using the Hilbert transform, which shifts the phase of all input frequency components of the Q branch by 90 degrees [12]. The impulse response of the ideal Hilbert transform is noncausal, however, and therefore not physically realizable with practical circuits. In practice, the negative frequencies can be suppressed by some form of complex filtering, such as CT complex bandpass filters [13]. Since integrated complex bandpass filters passing only the positive portion of the desired signal are difficult to implement at the high input frequencies involved in subsampling, complex bandstop filters that merely reject the image band frequencies realized with a simple passive RCCR network [14], or with asymmetric polyphase networks [15], are usually preferred. After image rejection, the complex bandpass signal can be directly quadrature downconverted to dc by selecting the k th multiple of the subsampling frequency be equal to the center frequency of the signal, i.e., kf s =f c. The spectrum of the subsampled complex signal is shown in Fig. 2 (d), inspection of which reveals that when direct downconversion to dc by subsampling is employed, the bandwidth of the complex bandpass signal can ideally be equal to the subsampling frequency without any overlapping of the sampled signal spectral replicas. In practice, however, the achievable rejection of the image signal band, or image rejection ratio (IMR), is limited by the constraints of the physical quadrature generation method, and also circuit mismatches. The finite IMR results in aliasing of the attenuated image band signal on top of the desired signal, resulting in degradation in the output SNR. The negative frequency content of the realvalued bandpass signal can also be rejected within the subsampling operation itself. In quadrature generation methods based on the secondorder sampling principle [16],[17],[18], the I channel samples are taken at time instants nt s at a sampling rate f s =1/Τ s. As in the subsampling of a complex bandpass signal, shown in Fig. 2, f s determines the spectral location of the sampled signal and can be chosen appropriately in order to achieve downconversion by subsampling. The Q channel samples are acquired at the same sampling rate f s, but with a delay ΔΤ in relation to the I channel samples at time instants nt s ΔT. When ΔT fulfils the condition [18] 2k ± 1 ΔT = , k = 0123,,,,, (2) 4f c the sampled I and Q channel components of the bandpass input signal with a center frequency f c have the same amplitude and a phase difference of 90 degrees at f c, hence ideally yielding the perfect Hilbert transform for the signal component at f c. For input frequencies other than f c, the phase difference of the sampled I and Q components deviates from the desired 90 degrees, resulting in finite rejection of the image signal. The effects of an imperfect Hilbert transform in secondorder sampling can minimized if the signal bandwidth is relatively small compared with f c [17]. It is worth noticing that in principle, since the phase error arising from the constant ΔT between the quadrature channel samples is known in advance, it is also possible to perform compensating phaseshifting filtering in
20 19 the digital domain to minimize its effects [19]. However, due to timing mismatches in analogue sampler implementations, ΔT can be different from the desired value, hence resulting in an unknown phase error and degradation of IMR. It should be noted that delaying the acquisition of the Q channel samples in secondorder sampling can be thought of as an elementary DT complex filtering operation embedded into the sampling process. The ideal builtin complex filtering function of the secondorder sampler can be described with the transfer function H c () f = 1 + j e j2πfδt (3) which has a single notch over the image band at f c, as illustrated by the magnitude response in Fig. 3. Hence, when used for subsampling, the whole secondorder sampling process can be described as a combination of two sequential signal processing operations: elementary imagerejecting complex filtering due to the time delay between the two quadrature channel samples, and quadrature downconversion of the filtered signal by subsampling Amplitude [db] f c 0 f c Frequency Fig. 3. Ideal magnitude response of a simple secondorder sampling circuit. 2.2 Problems of subsampling Whereas in baseband sampling the realization of appropriate antialiasing filtering is relatively straightforward and easily achieved with integrated lowpass filters, the achievement of adequate bandpass antialiasing filtering in subsampling can result in a need for expensive offchip filters. In addition to attenuating strong interfering signals near unwanted multiples of the subsampling frequency, the bandpass antialiasing filter also has to suppress the wideband noise present at the input of the sampler before the subsampling operation causes it to fold on the Nyquist band of the sampling frequency. To obtain a deeper insight into the problem of achieving adequate noise performance in subsampling, let us consider the noise figure of the simple voltagedomain subsampler described in Fig. 4 (a). Ideally the input bandwidth the simple subsampler would be limited by a steep bandpass
21 20 NBW=B neq f s V out (nt s )+N out V in +N in N out (f), log j2πfr on C s + 1 Z o <<R on 4kTR on R on (a) C s f s /2 f s 2f s 3f s 4f s 5f s 6f s f (b) Fig. 4. (a) A simple voltagedomain subsampling circuit. (b) Aliasing of wideband thermal noise in subsampling. antialiasing filter passing only the desired bandpass signal spectrum of bandwidth f B. In practice, the realization of such a filter at RF would require a very high filter quality factor (f c /f B ) of the order of several thousands, which is not realizable with integrated components. In addition, to enable downconversion of multiple channels with different center frequencies by changing the subsampling frequency, the narrowband antialiasing filter bandwidth would have to be tunable. Hence, a practical bandpass antialiasing filter can merely be used to select the receive (RX) band of the input signal at RF. Provided that the impedance Z o seen towards the output of the bandpass antialiasing filter is small compared with the onresistance R on of the sampling switch, and the ontime of the sampling switch is long compared with the time constant R on C s of the sampling loop [20], the rms noise power at the output of the sampler of Fig. 4 (a) can be approximated with kt N out( rms) C s B neq N in, (4) where B neq is the noise bandwidth of the frontend filter and N in =V 2 n,in (f) represents the wideband noise at the input of the sampler, which is assumed for simplicity to have a white spectral density. The sampled output noise consists of the kt/c noise component attributable to the thermal noise V 2 n,ron (f)=4ktr on of the sampling switch and the wideband frontend noise filtered by the antialiasing filter. A narrowband bandpass antialiasing filter with B neq << would clearly minimize the contribution of the frontend noise to the output noise of the subsampler. To consider only the intrinsic noise figure of the simple subsampler, let us assume that no additional antialiasing filter is used at the frontend of the sampler. In such a case both the wideband input noise N in of the sampler and the thermal noise 4kTR on of the sampling
The front end of the receiver performs the frequency translation, channel selection and amplification of the signal.
Many receivers must be capable of handling a very wide range of signal powers at the input while still producing the correct output. This must be done in the presence of noise and interference which occasionally
More informationIntroduction to Receivers
Introduction to Receivers Purpose: translate RF signals to baseband Shift frequency Amplify Filter Demodulate Why is this a challenge? Interference (selectivity, images and distortion) Large dynamic range
More informationFILTER CIRCUITS. A filter is a circuit whose transfer function, that is the ratio of its output to its input, depends upon frequency.
FILTER CIRCUITS Introduction Circuits with a response that depends upon the frequency of the input voltage are known as filters. Filter circuits can be used to perform a number of important functions in
More informationADCS OF SDR PARAMETERS, DESIGN CONSIDERATIONS AND IMPLEMENTATIONS. Presented by Spectrum Signal Processing and Intersil Corporation August 2011
ADCS OF SDR PARAMETERS, DESIGN CONSIDERATIONS AND IMPLEMENTATIONS Presented by Spectrum Signal Processing and Intersil Corporation August 2011 1 SIMPLY SMARTER Company Overview Intersil Headquarters: Milpitas,
More informationPerformance of an IF sampling ADC in receiver applications
Performance of an IF sampling ADC in receiver applications David Buchanan Staff Applications Engineer Analog Devices, Inc. Introduction The concept of direct intermediate frequency (IF) sampling is not
More information5 Signal Design for Bandlimited Channels
225 5 Signal Design for Bandlimited Channels So far, we have not imposed any bandwidth constraints on the transmitted passband signal, or equivalently, on the transmitted baseband signal s b (t) I[k]g
More informationDIGITALTOANALOGUE AND ANALOGUETODIGITAL CONVERSION
DIGITALTOANALOGUE AND ANALOGUETODIGITAL CONVERSION Introduction The outputs from sensors and communications receivers are analogue signals that have continuously varying amplitudes. In many systems
More informationSimplify communication system design while increasing available bandwidth
Simplify communication system design while increasing available bandwidth Clarence Mayott  July 13, 2015 Introduction In modern communications systems, the more bandwidth that is available, the more information
More informationImplementation of Digital Signal Processing: Some Background on GFSK Modulation
Implementation of Digital Signal Processing: Some Background on GFSK Modulation Sabih H. Gerez University of Twente, Department of Electrical Engineering s.h.gerez@utwente.nl Version 4 (February 7, 2013)
More informationUnderstand the effects of clock jitter and phase noise on sampled systems A s higher resolution data converters that can
designfeature By Brad Brannon, Analog Devices Inc MUCH OF YOUR SYSTEM S PERFORMANCE DEPENDS ON JITTER SPECIFICATIONS, SO CAREFUL ASSESSMENT IS CRITICAL. Understand the effects of clock jitter and phase
More informationCONVERTERS. Filters Introduction to Digitization DigitaltoAnalog Converters AnalogtoDigital Converters
CONVERTERS Filters Introduction to Digitization DigitaltoAnalog Converters AnalogtoDigital Converters Filters Filters are used to remove unwanted bandwidths from a signal Filter classification according
More informationTechniques for Extending RealTime Oscilloscope Bandwidth
Techniques for Extending RealTime Oscilloscope Bandwidth Over the past decade, data communication rates have increased by a factor well over 10X. Data rates that were once 1Gb/sec and below are now routinely
More informationTCOM 370 NOTES 994 BANDWIDTH, FREQUENCY RESPONSE, AND CAPACITY OF COMMUNICATION LINKS
TCOM 370 NOTES 994 BANDWIDTH, FREQUENCY RESPONSE, AND CAPACITY OF COMMUNICATION LINKS 1. Bandwidth: The bandwidth of a communication link, or in general any system, was loosely defined as the width of
More informationAnalog to Digital, A/D, Digital to Analog, D/A Converters. An electronic circuit to convert the analog voltage to a digital computer value
Analog to Digital, A/D, Digital to Analog, D/A Converters An electronic circuit to convert the analog voltage to a digital computer value Best understood by understanding Digital to Analog first. A fundamental
More informationT = 1 f. Phase. Measure of relative position in time within a single period of a signal For a periodic signal f(t), phase is fractional part t p
Data Transmission Concepts and terminology Transmission terminology Transmission from transmitter to receiver goes over some transmission medium using electromagnetic waves Guided media. Waves are guided
More informationImpedance 50 (75 connectors via adapters)
VECTOR NETWORK ANALYZER PLANAR TR1300/1 DATA SHEET Frequency range: 300 khz to 1.3 GHz Measured parameters: S11, S21 Dynamic range of transmission measurement magnitude: 130 db Measurement time per point:
More informationCMOS SampleandHold Circuits
CMOS SampleandHold Circuits ECE 1352 Reading Assignment By: Joyce Cheuk Wai Wong November 12, 2001 Department of Electrical and Computer Engineering University of Toronto 1. Introduction Sampleandhold
More informationAN837 APPLICATION NOTE
APPLICATION NOTE One Technology Way P.O. Box 916 Norwood, MA 262916, U.S.A. Tel: 781.329.47 Fax: 781.461.3113 www.analog.com DDSBased Clock Jitter Performance vs. DAC Reconstruction Filter Performance
More informationBasics on Digital Signal Processing
Basics on Digital Signal Processing Introduction Vassilis Anastassopoulos Electronics Laboratory, Physics Department, University of Patras Outline of the Course 1. Introduction (sampling quantization)
More informationDepartment of Electrical and Computer Engineering BenGurion University of the Negev. LAB 1  Introduction to USRP
Department of Electrical and Computer Engineering BenGurion University of the Negev LAB 1  Introduction to USRP  11 Introduction In this lab you will use software reconfigurable RF hardware from National
More informationby Anurag Pulincherry A THESIS submitted to Oregon State University in partial fulfillment of the requirements for the degree of Master of Science
A Continuous Time Frequency Translating Delta Sigma Modulator by Anurag Pulincherry A THESIS submitted to Oregon State University in partial fulfillment of the requirements for the degree of Master of
More informationAN756 APPLICATION NOTE One Technology Way P.O. Box 9106 Norwood, MA 020629106 Tel: 781/3294700 Fax: 781/3268703 www.analog.com
APPLICATION NOTE One Technology Way P.O. Box 9106 Norwood, MA 020629106 Tel: 781/3294700 Fax: 781/3268703 www.analog.com Sampled Systems and the Effects of Clock Phase Noise and Jitter by Brad Brannon
More informationApproximation of an ideal bandpass filter using an Npath filter with overlapping clocks and harmonic rejection
Faculty of Electrical Engineering, Mathematics & Computer Science Approximation of an ideal bandpass filter using an Npath filter with overlapping clocks and harmonic rejection L. C. Fortgens MSc. Thesis
More informationCRP718 RF and Microwave Measurements Laboratory
CRP718 RF and Microwave Measurements Laboratory Experiment MW2 Handout. Updated Jan 13, 2011 SPECTRUM ANALYZER BASED MEASUREMENTS (groups of 2 may omit part 2.1, but are advised to study the procedures
More informationMaximizing Receiver Dynamic Range for Spectrum Monitoring
Home Maximizing Receiver Dynamic Range for Spectrum Monitoring Brian Avenell, National Instruments Corp., Austin, TX October 15, 2012 As consumers continue to demand more data wirelessly through mobile
More informationCologne Chip DIGICC TM. CODEC Technology. Technology Background
DIGICC TM CODEC Technology Technology Background Technology Background 5 November 2004 Cologne AG Eintrachtstrasse 113 D  50668 Köln Germany Tel.: +49 (0) 221 / 91 240 Fax: +49 (0) 221 / 91 24100 http://www.cologne.com
More informationFirst and Second Order Filters
First and Second Order Filters These functions are useful for the design of simple filters or they can be cascaded to form highorder filter functions First Order Filters General first order bilinear transfer
More informationThe Effective Number of Bits (ENOB) of my R&S Digital Oscilloscope Technical Paper
The Effective Number of Bits (ENOB) of my R&S Digital Oscilloscope Technical Paper Products: R&S RTO1012 R&S RTO1014 R&S RTO1022 R&S RTO1024 This technical paper provides an introduction to the signal
More informationFUNDAMENTALS OF MODERN SPECTRAL ANALYSIS. Matthew T. Hunter, Ph.D.
FUNDAMENTALS OF MODERN SPECTRAL ANALYSIS Matthew T. Hunter, Ph.D. AGENDA Introduction Spectrum Analyzer Architecture Dynamic Range Instantaneous Bandwidth The Importance of Image Rejection and AntiAliasing
More informationMaking Accurate Voltage Noise and Current Noise Measurements on Operational Amplifiers Down to 0.1Hz
Author: Don LaFontaine Making Accurate Voltage Noise and Current Noise Measurements on Operational Amplifiers Down to 0.1Hz Abstract Making accurate voltage and current noise measurements on op amps in
More informationECE1371 Term Paper RF Receiver Systems and Circuits Dennis Ma
ECE1371 Term Paper RF Receiver Systems and Circuits Dennis Ma I. Introduction In the past decade, portable wireless communication systems have experienced tremendous growth. Such rapid growth has created
More informationRF SYSTEM DESIGN OF TRANSCEIVERS FOR WIRELESS COMMUNICATIONS
RF SYSTEM DESIGN OF TRANSCEIVERS FOR WIRELESS COMMUNICATIONS Qizheng Gu Nokia Mobile Phones, Inc. 4y Springer Contents Preface xiii Chapter 1. Introduction 1 1.1. Wireless Systems 1 1.1.1. Mobile Communications
More informationWireless Communication and RF System Design Using MATLAB and Simulink Giorgia Zucchelli Technical Marketing RF & MixedSignal
Wireless Communication and RF System Design Using MATLAB and Simulink Giorgia Zucchelli Technical Marketing RF & MixedSignal 2013 The MathWorks, Inc. 1 Outline of Today s Presentation Introduction to
More informationOptimizing IP3 and ACPR Measurements
Optimizing IP3 and ACPR Measurements Table of Contents 1. Overview... 2 2. Theory of Intermodulation Distortion... 2 3. Optimizing IP3 Measurements... 4 4. Theory of Adjacent Channel Power Ratio... 9 5.
More informationFrequency Response of Filters
School of Engineering Department of Electrical and Computer Engineering 332:224 Principles of Electrical Engineering II Laboratory Experiment 2 Frequency Response of Filters 1 Introduction Objectives To
More informationHow PLL Performances Affect Wireless Systems
May 2010 Issue: Tutorial Phase Locked Loop Systems Design for Wireless Infrastructure Applications Use of linear models of phase noise analysis in a closed loop to predict the baseline performance of various
More informationLoop Bandwidth and Clock Data Recovery (CDR) in Oscilloscope Measurements. Application Note 13046
Loop Bandwidth and Clock Data Recovery (CDR) in Oscilloscope Measurements Application Note 13046 Abstract Time domain measurements are only as accurate as the trigger signal used to acquire them. Often
More informationMeasurement of Adjacent Channel Leakage Power on 3GPP WCDMA Signals with the FSP
Products: Spectrum Analyzer FSP Measurement of Adjacent Channel Leakage Power on 3GPP WCDMA Signals with the FSP This application note explains the concept of Adjacent Channel Leakage Ratio (ACLR) measurement
More informationRadio and Television (E522)
Benha Faculty of Engineering Electrical Engineering Department 5 th Year Telecommunication Final Exam: 26 May 2012 Examiner: Dr. Hatem ZAKARIA Time allowed: 3 Hours Radio and Television (E522) Answer All
More informationIntroduction to Digital Audio
Introduction to Digital Audio Before the development of highspeed, lowcost digital computers and analogtodigital conversion circuits, all recording and manipulation of sound was done using analog techniques.
More informationPrecision Fully Differential Op Amp Drives High Resolution ADCs at Low Power
Precision Fully Differential Op Amp Drives High Resolution ADCs at Low Power Kris Lokere The op amp produces differential outputs, making it ideal for processing fully differential analog signals or taking
More informationDelta Sigma Data Conversion in Wireless Transceivers
302 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 50, NO. 1, JANUARY 2002 Delta Sigma Data Conversion in Wireless Transceivers Ian Galton, Member, IEEE Invited Paper Abstract Highperformance
More informationVideo Feedthrough. A common source of RF distortion in pulsemodulated RF sources
Video Feedthrough El Toro 68C/69B Microwave Synthesizers Application Note A common source of RF distortion in pulsemodulated RF sources Introduction Video feedthrough is a very misunderstood term, which
More informationThe counterpart to a DAC is the ADC, which is generally a more complicated circuit. One of the most popular ADC circuit is the successive
The counterpart to a DAC is the ADC, which is generally a more complicated circuit. One of the most popular ADC circuit is the successive approximation converter. 1 2 The idea of sampling is fully covered
More informationElectronic Communications Committee (ECC) within the European Conference of Postal and Telecommunications Administrations (CEPT)
Page 1 Electronic Communications Committee (ECC) within the European Conference of Postal and Telecommunications Administrations (CEPT) ECC RECOMMENDATION (06)01 Bandwidth measurements using FFT techniques
More informationSIMULTANEOUS A/D DATA ACQUISITION
BENEFITS OF SIMULTANEOUS DATA ACQUISITION MODULES When choosing a data acquisition board, many different selection criteria are used. Speed, resolution, accuracy, and number of channels are all important
More informationMotorola Digital Signal Processors
Motorola Digital Signal Processors Principles of SigmaDelta Modulation for Analogto Digital Converters by Sangil Park, Ph. D. Strategic Applications Digital Signal Processor Operation MOTOROLA APR8
More informationTSEK03: Radio Frequency Integrated Circuits (RFIC)
TSEK03: Radio Frequency Integrated Circuits (RFIC) Lecture 6: Mixers (cont) Ted Johansson, EKS, ISY ted.johansson@liu.se Overview 2 Razavi: Chapter 6.16.3, pp. 343398. Lee: Chapter 13. 6.1 Mixers general
More informationDigital to Analog Converter. Raghu Tumati
Digital to Analog Converter Raghu Tumati May 11, 2006 Contents 1) Introduction............................... 3 2) DAC types................................... 4 3) DAC Presented.............................
More informationSwitchedCapacitor Circuits. Basic Building Blocks
SwitchedCapacitor Circuits David Johns and Ken Martin University of Toronto (johns@eecg.toronto.edu) (martin@eecg.toronto.edu) University of Toronto 1 of 60 Basic Building Blocks Opamps Ideal opamps usually
More informationConditioning and Correction of Arbitrary Waveforms Part 2: Other Impairments
From September 2005 High Frequency Electronics Copyright 2005 Summit Technical Media Conditioning and Correction of Arbitrary Waveforms Part 2: Other Impairments By Mike Griffin and John Hansen Agilent
More informationSpikeBased Sensing and Processing: What are spikes good for? John G. Harris Electrical and Computer Engineering Dept
SpikeBased Sensing and Processing: What are spikes good for? John G. Harris Electrical and Computer Engineering Dept ONR NEUROSILICON WORKSHOP, AUG 12, 2006 Take Home Messages Introduce integrateandfire
More informationAdvantages of High Resolution in High Bandwidth Digitizers
Advantages of High Resolution in High Bandwidth Digitizers Two of the key specifications of digitizers are bandwidth and amplitude resolution. These specifications are not independent  with increasing
More informationchapter Introduction to Digital Signal Processing and Digital Filtering 1.1 Introduction 1.2 Historical Perspective
Introduction to Digital Signal Processing and Digital Filtering chapter 1 Introduction to Digital Signal Processing and Digital Filtering 1.1 Introduction Digital signal processing (DSP) refers to anything
More informationUnderstanding Phase Noise in RF and Microwave Calibration Applications.
Understanding Phase Noise in RF and Microwave Calibration Applications. Speaker/Author: Paul C. A. Roberts Fluke Precision Measurement Ltd. Hurricane Way Norwich, NR6 6JB, United Kingdom. Tel: +44 (0)1603
More informationModule 4. Contents. Digital Filters  Implementation and Design. Signal Flow Graphs. Digital Filter Structures. FIR and IIR Filter Design Techniques
Module 4 Digital Filters  Implementation and Design Digital Signal Processing. Slide 4.1 Contents Signal Flow Graphs Basic filtering operations Digital Filter Structures Direct form FIR and IIR filters
More informationReconfigurable Low Area Complexity Filter Bank Architecture for Software Defined Radio
Reconfigurable Low Area Complexity Filter Bank Architecture for Software Defined Radio 1 Anuradha S. Deshmukh, 2 Prof. M. N. Thakare, 3 Prof.G.D.Korde 1 M.Tech (VLSI) III rd sem Student, 2 Assistant Professor(Selection
More informationDigitaltoAnalog Conversion
ANALOG.PPT(01/10/2009) 4.1 Lecture 10 DigitaltoAnalog Conversion Objectives Understand how a weightedresister DAC can be used to convert numbers with binary or nonbinary bit weightings Understand the
More informationObjectives: to get acquainted with active filter circuits and parameters, design methods, build and investigate active LPF, HPF and BPF.
Laboratory of the circuits and signals Laboratory work No. 4 ACTIVE FILTERS Objectives: to get acquainted with active filter circuits and parameters, design methods, build and investigate active LPF, HPF
More informationLAB 12: ACTIVE FILTERS
A. INTRODUCTION LAB 12: ACTIVE FILTERS After last week s encounter with op amps we will use them to build active filters. B. ABOUT FILTERS An electric filter is a frequencyselecting circuit designed
More informationCMOS Analog IC Design Page
CMOS Analog IC Design Page 10.54 NYQUIST FREQUENCY ANALOGDIGITAL CONVERTERS The sampled nature of the ADC places a practical limit on the bandwidth of the input signal. If the sampling frequency is f
More informationAgilent AN 1315 Optimizing RF and Microwave Spectrum Analyzer Dynamic Range. Application Note
Agilent AN 1315 Optimizing RF and Microwave Spectrum Analyzer Dynamic Range Application Note Table of Contents 3 3 3 4 4 4 5 6 7 7 7 7 9 10 10 11 11 12 12 13 13 14 15 1. Introduction What is dynamic range?
More informationApplication Note Noise Frequently Asked Questions
: What is? is a random signal inherent in all physical components. It directly limits the detection and processing of all information. The common form of noise is white Gaussian due to the many random
More informationANALYZER BASICS WHAT IS AN FFT SPECTRUM ANALYZER? 21
WHAT IS AN FFT SPECTRUM ANALYZER? ANALYZER BASICS The SR760 FFT Spectrum Analyzer takes a time varying input signal, like you would see on an oscilloscope trace, and computes its frequency spectrum. Fourier's
More informationRF SYSTEM DESIGN OF TRANSCEIVERS FOR WIRELESS COMMUNICATIONS
RF SYSTEM DESIGN OF TRANSCEIVERS FOR WIRELESS COMMUNICATIONS RF SYSTEM DESIGN OF TRANSCEIVERS FOR WIRELESS COMMUNICATIONS Qizheng Gu Nokia Mobile Phones, Inc. Q  Springer Gu, Qizheng, 1936 RF system
More informationPart I: Operational Amplifiers & Their Applications
Part I: Operational Amplifiers & Their Applications Contents Opamps fundamentals Opamp Circuits Inverting & Noninverting Amplifiers Summing & Difference Amplifiers Integrators & Differentiators Opamp
More informationPCM Encoding and Decoding:
PCM Encoding and Decoding: Aim: Introduction to PCM encoding and decoding. Introduction: PCM Encoding: The input to the PCM ENCODER module is an analog message. This must be constrained to a defined bandwidth
More informationAVR127: Understanding ADC Parameters. Introduction. Features. Atmel 8bit and 32bit Microcontrollers APPLICATION NOTE
Atmel 8bit and 32bit Microcontrollers AVR127: Understanding ADC Parameters APPLICATION NOTE Introduction This application note explains the basic concepts of analogtodigital converter (ADC) and the
More informationUnderstanding Mixers Terms Defined, and Measuring Performance
Understanding Mixers Terms Defined, and Measuring Performance Mixer Terms Defined Statistical Processing Applied to Mixers Today's stringent demands for precise electronic systems place a heavy burden
More informationHigh Sensitivity Receiver Applications Benefit from Unique Features in 16bit 130Msps ADC
High Sensitivity Receiver Applications Benefit from Unique Features in 16bit 130Msps ADC RF IN RF BPF IF BPF LTC2208 ADC DDC/DSP LO1 ADC Driver Wireless receiver design requires extreme care in dealing
More informationMODULATION Systems (part 1)
Technologies and Services on Digital Broadcasting (8) MODULATION Systems (part ) "Technologies and Services of Digital Broadcasting" (in Japanese, ISBN4339622) is published by CORONA publishing co.,
More informationA/D Converter based on Binary Search Algorithm
École Polytechnique Fédérale de Lausanne Politecnico di Torino Institut National Polytechnique de Grenoble Master s degree in Micro and Nano Technologies for Integrated Systems Master s Thesis A/D Converter
More informationTaking the Mystery out of the Infamous Formula, "SNR = 6.02N + 1.76dB," and Why You Should Care. by Walt Kester
ITRODUCTIO Taking the Mystery out of the Infamous Formula, "SR = 6.0 + 1.76dB," and Why You Should Care by Walt Kester MT001 TUTORIAL You don't have to deal with ADCs or DACs for long before running across
More informationRF Network Analyzer Basics
RF Network Analyzer Basics A tutorial, information and overview about the basics of the RF Network Analyzer. What is a Network Analyzer and how to use them, to include the Scalar Network Analyzer (SNA),
More informationFilter, Attenuator, Preamplifier, Preselector.  or Barefoot?
TECHNOTE No. 7 Joe Carr's Radio TechNotes Filter, Attenuator, Preamplifier, Preselector  or Barefoot? Joseph J. Carr Universal Radio Research 6830 Americana Parkway Reynoldsburg, Ohio 43068 1 Filter,
More informationwhere T o defines the period of the signal. The period is related to the signal frequency according to
SIGNAL SPECTRA AND EMC One of the critical aspects of sound EMC analysis and design is a basic understanding of signal spectra. A knowledge of the approximate spectral content of common signal types provides
More informationThe output signal may be of the same form as the input signal, i.e. V in produces V out
What is an amplifier? Operational Amplifiers A device that takes an input (current, voltage, etc.) and produces a correlated output Input Signal Output Signal Usually the output is a multiple of the input
More informationTx/Rx A highperformance FM receiver for audio and digital applicatons
Tx/Rx A highperformance FM receiver for audio and digital applicatons This receiver design offers high sensitivity and low distortion for today s demanding highsignal environments. By Wayne C. Ryder
More informationChapter 3 DiscreteTime Fourier Series. by the French mathematician Jean Baptiste Joseph Fourier in the early 1800 s. The
Chapter 3 DiscreteTime Fourier Series 3.1 Introduction The Fourier series and Fourier transforms are mathematical correlations between the time and frequency domains. They are the result of the heattransfer
More informationRF System Design and Analysis Software Enhances RF Architectural Planning
From April 2010 High Frequency Electronics Copyright 2010 Summit Technical Media, LLC RF System Design and Analysis Software Enhances RF Architectural Planning By Dale D. Henkes Applied Computational Sciences
More informationL AND S BAND TUNABLE FILTERS PROVIDE DRAMATIC IMPROVEMENTS IN TELEMETRY SYSTEMS
L AND S BAND TUNABLE FILTERS PROVIDE DRAMATIC IMPROVEMENTS IN TELEMETRY SYSTEMS Timothy J. Wurth, Jason Rodzinak NuWaves Engineering, 122 Edison Drive, Middletown OH, USA 45044 ABSTRACT Meeting the filtering
More informationModern Definition of Terms
Filters In the operation of electronic systems and circuits, the basic function of a filter is to selectively pass, by frequency, desired signals and to suppress undesired signals. The amount of insertion
More informationEE 311: Electrical Engineering Junior Lab Active Filter Design (SallenKey Filter)
EE 311: Electrical Engineering Junior Lab Active Filter Design (SallenKey Filter) Objective The purpose of this experiment is to design a set of secondorder SallenKey active filters and to investigate
More informationFREQUENCY RESPONSE AND PASSIVE FILTERS LABORATORY. We start with examples of a few filter circuits to illustrate the concept.
FREQUENCY RESPONSE AND PASSIVE FILTERS LABORATORY In this experiment we will analytically determine and measure the frequency response of networks containing resistors, AC source/sources, and energy storage
More informationApplication Note 9. Digital FIR Decimator & Analog Lowpass
Application Note 9 App Note Application Note 9 Highlights Multirate FIR Design Cascade Analog Lowpass Circuit Optimization Comb Filter Correction Sin(x)/x Correction n Design Objective 16:1 FIR Decimation
More informationContinuousTime Converter Architectures for Integrated Audio Processors: By Brian Trotter, Cirrus Logic, Inc. September 2008
ContinuousTime Converter Architectures for Integrated Audio Processors: By Brian Trotter, Cirrus Logic, Inc. September 2008 As consumer electronics devices continue to both decrease in size and increase
More informationVisual System Simulator White Paper
Visual System Simulator White Paper UNDERSTANDING AND CORRECTLY PREDICTING CRITICAL METRICS FOR WIRELESS RF LINKS Understanding and correctly predicting cellular, radar, or satellite RF link performance
More informationLABORATORY EXPERIMENT. Infrared Transmitter/Receiver
LABORATORY EXPERIMENT Infrared Transmitter/Receiver (Note to Teaching Assistant: The week before this experiment is performed, place students into groups of two and assign each group a specific frequency
More informationRSP Firmware Functional Specification
Embedded Processing Applications RSP Firmware Functional Specification Verified: Name Signature Date Rev.nr. Accepted: Work Package Manager System Engineering Manager Program Manager W.H. Lubberhuizen
More informationAchieving New Levels of Channel Density in Downstream Cable Transmitter Systems: RF DACs Deliver Smaller Size and Lower Power Consumption
Achieving New Levels of Channel Density in Downstream Cable Transmitter Systems: RF DACs Deliver Smaller Size and Lower Power Consumption Introduction By: Analog Devices, Inc. (ADI) Daniel E. Fague, Applications
More informationLecture 3: Quantization Effects
Lecture 3: Quantization Effects Reading: 6.76.8. We have so far discussed the design of discretetime filters, not digital filters. To understand the characteristics of digital filters, we need first
More informationOutline. Analog to Digital Converters. Overview of architectures for implementing analog to digital conversion INF4420
INF4420 Analog to Digital Converters Jørgen Andreas Michaelsen Spring 2013 1 / 34 Outline Overview of architectures for implementing analog to digital conversion Spring 2013 Analog to Digital Converters
More informationIntroduction to IQdemodulation of RFdata
Introduction to IQdemodulation of RFdata by Johan Kirkhorn, IFBT, NTNU September 15, 1999 Table of Contents 1 INTRODUCTION...3 1.1 Abstract...3 1.2 Definitions/Abbreviations/Nomenclature...3 1.3 Referenced
More informationBandwidth Limitations.
The HP 71910A widebandwidth receiver extends modular spectrum analyzer operation for more effective measurements on modern communications and radar signals. Bandwidth Limitations. FrequencyDomain Limitations.
More informationOutline. SwitchedCapacitor Circuits. Introduction (why and how) Integrators and filters Gain circuits Noise and charge injection INF4420
INF4420 SwitchedCapacitor Circuits Jørgen Andreas Michaelsen Spring 2013 1 / 42 Outline Introduction (why and how) Integrators and filters Gain circuits Noise and charge injection Spring 2013 SwitchedCapacitor
More informationMonolithic Crystal Filters 2 Quartz resonator internally coupled utilizing piezoelectric effect.
The following describes filter types, what they do and how they perform. Along with definitions and detailed graphs, we are hopeful this information is both useful and informative. Filter Types Monolithic
More informationTime and Frequency Domain Equalization
Time and Frequency Domain Equalization Presented By: Khaled Shawky Hassan Under Supervision of: Prof. Werner Henkel Introduction to Equalization Nonideal analogmedia such as telephone cables and radio
More informationFrequency Synthesizer Architecture Design for DRM and DAB Receiver
Progress In Electromagnetics Research Symposium, Hangzhou, China, March 2428, 2008 59 Frequency Synthesizer Architecture Design for DRM and DAB Receiver Jianzheng Zhou 1,2 and Zhigong Wang 1 1 Institute
More informationNonData Aided Carrier Offset Compensation for SDR Implementation
NonData Aided Carrier Offset Compensation for SDR Implementation Anders Riis Jensen 1, Niels Terp Kjeldgaard Jørgensen 1 Kim Laugesen 1, Yannick Le Moullec 1,2 1 Department of Electronic Systems, 2 Center
More information&"#' ( "#' )*! #+ #,# 1" 1! 2"# ' 6! #* #!"#" +" )$# # # "#$#$ '2 2 ## #1##9 # # ##2 #( # 8##! #9# 9@8!( " " "32#$#$2#9 # "#!#1#$#$#9 '29# # #9$
!"## $#!%!"# &"#' ( "#' )*! #+ #,# "##!$ +./0 1" 1! 2"# # &1!"#" (2345&1 #$6.7 &89$## ' 6! #* #!"#" +" 1##6$ "#+# #& :1# # $ #$#;1)+#1#+
More information