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A ANALOG-TO-DIGITAL CONVERSION conversion can be thought of as a two-step process. First, IN THE EARLY TWENTY-FIRST CENTURY the input signal is sampled in time, usually at regularly spaced intervals; fsamp ¼ 1/T, where T ¼ sampling interval Analog-to-digital converters (ADCs) continue to be impor- (e.g., for fsamp ¼ 1 gigasample per second, T ¼ 1 ns). The tant components of signal-processing systems, such as those second step is to quantize (or digitize) the samples (usually for mobile communications, software radio, radar, satellite a voltage) in amplitude. The maximum signal range (full- communications, and others. This article revisits the state- scale input voltage) is divided into 2N subranges, where of-the-art of ADCs and includes recent data on experimental N ¼ the ADC’s resolution (number of output leads), (e.g., for converters and commercially available parts. Converter N ¼ 12 bits, a 1-Volt full-scale range is divided into 2N ¼ performances have improved significantly since previous 4096 levels). The least-significant bit (LSB) is 1 V / 2N ¼ 244 surveys were published (1999–2005). Specifically, aperture mV. Two potential purposes for these conversions are (1)to uncertainty (jitter) and power dissipation have both enable computer analysis of the signal and (2) to enable decreased substantially during the early 2000s. The lowest digital transmission of the signal. jitter value has fallen from approximately 1 picosecond in The limitations of ADCs in terms of both resolution and 1999 to <100 femtoseconds for the very best of current sampling rate are determined by the capability of the ADCs. In addition, the lowest values for the IEEE Figure integrated circuit (IC) process, as well as chip design tech- of Merit (which is proportional to the product of jitter and niques, used to manufacture them, and, were perceived as a power dissipation) have also decreased by an order of mag- limiting factor (1) to system performances as recently as nitude. For converters that operate at multi-GSPS rates, the 1999. However, more recent developments have demon- speed of the fastest ADC IC device technologies (e.g., InP, strated that significant progress has occurred with respect GaAs) is the main limitation to performance; as measured to converter performances, especially for sampling rates in by device transit-time frequency, fT, has roughly tripled the 100 megasamples/s (MSPS) range as well as in the since 1999. ADC architectures used in high-performance neighborhood of 1 gigasample/s. The purpose of this article broadband circuits include pipelined (successive approxi- is to provide an update to previous ADC surveys (1–3) and mation, multistage flash) and parallel (time-interleaved, to analyze the new results. filter-bank) with the former leading to lower power opera- The next section of this article summarizes the charac- tion and the latter being applied to high-sample rate con- terization and limitations of ADCs, and the section on ADC verters. Bandpass ADCs based on delta-sigma modulation performance update discusses how ADC performances are being applied to narrow band applications with ever have changed (improved) during the past 8 years. The increasing center frequencies. CMOS has become a main- next section covers Figures of Merit, and the section on stream ADC IC technology because (1) it enables designs high-performance ADC architectures discusses architec- with low power dissipation and (2) it allows for significant tures that are presently in use along with the advantages amounts of digital-signal processing to be included on-chip. conferred by increased ADC IC complexity. Then, perfor- DSP enables correction of conversion errors, improved mance trends and projections are discussed, and finally, the channel matching in parallel structures, and provides last section gives a summary and provides conclusions. filtering required for delta-sigma converters. Finally, a Appendix 1 contains a list of the more than 175 ADCs performance projection based on a trend in aperture jitter covered in this work. predicts 25 fs in approximately 10 years, which would imply performance of 12 ENOB at nearly 1-GHz bandwidth. PERFORMANCE CHARACTERIZATION AND LIMITATIONS INTRODUCTION One of the key parameters describing ADC performances is signal-to-noise plus distortion ratio, (SNDR), which is During the past three decades, especially the past 7–10 defined as the ratio of the root mean square signal ampli- years, the increasingly rapid evolution of digital inte- tude to the square root of the integral of the noise power grated circuit technologies, as predicted by Moore’s spectrum (including spurious tones) over the frequency Law, has led to ever more sophisticated signal-processing band of interest [e.g., for a Nyquist converter, the pertinent systems. These systems operate on a wide variety of con- band extends from 0 to one-half the sampling rate (fsamp/2)]. tinuous-time signals, which include speech, medical ima- Another way of expressing this ratio is in terms of the ging, sonar, radar, electronic warfare, instrumentation, effective number of bits (ENOB) which is obtained from à consumer electronics, telecommunications (terrestrial SNDR(dB)¼ 20 log10(SNDR) by Ref. 4. and satellite), and mobile telecommunications (cell phones and associated networks). SNDRðdBÞ1:76 ENOB ¼ ð1Þ Analog-to-digital converters (ADCs) are the circuits 6:02 that convert these and other continuous-time signals to discrete-time, binary-coded form, that is, from human- This expression includes the effects of all losses asso- recognizable form to computer-recognizable form. Such a ciated with the subject ADC, which include equivalent 1 Wiley Encyclopedia of Computer Science and Engineering, edited by Benjamin Wah. Copyright # 2008 John Wiley & Sons, Inc. 2 ANALOG-TO-DIGITAL CONVERSION IN THE EARLY TWENTY-FIRST CENTURY input-referred thermal noise, ENOBthermal, aperture Some converters have ERBW values well beyond fsamp/2, uncertainty (jitter) noise, ENOBaperture, and comparator and,asnotedabove,implytheycanbeusedinundersampling ambiguity, ENOBambig, (1), as well as distortion induced mode. Because this type of operation involves sampling by spurious tones. If we were dealing with a loss-free, upper Nyquist zones, an antialiasing filter (AAF) must be distortion-free ADC, then the value of ENOB obtained placed in the signal path and in front of the converter to from Equation (1) would equal the number of output leads prevent contamination by unwanted out-of-zone signals. N, and it would correspond to the (intrinsic) quantization This Process results in using the ADC as a bandpass con- noise case. Expressions for ENOB for thermal noise, jitter, verter in which the passband of the AAF defines the band of and comparator ambiguity losses (each acting separately) interest, and, through the natural mixing property of the are given below: sampling process, the passband is shifted to baseband. The 2 appropriate value of ENOB for the bandpass case is the Vpp 1=2 ENOBthermal ¼ log2ð Þ À 1 ð2Þ midband value. An example would be sampling at 100 12kTRefffsig MSPS while using an AAF that covers the band 100 MHz þdto150MHz-d(thirdzone),wheredisdeterminedfromthe 1 AAF skirts and is large enough to keep out unwanted signals ENOBaperture ¼ log2ð Þ1 ð3Þ 2p fsigta and/or tones. In addition, delta-sigma (DS) converters (modulator followed by digital decimation filter) are coming more into p fT ENOBambiguity ¼ À 1:1 ð4Þ use for bandpass [intermediate frequency (IF) and radio 13:9fsig frequency (RF) sampling] conversion as well as (well- established) lowpass (baseband sampling). These ADCs Here, Vpp is the maximum peak-to-peak input voltage are each characterized, in this study, as having an effective presented to the ADC, k is Boltzmann’s constant, T is sampling rate ¼ 2  DS passband (determined by the the semiconductor substrate temperature in kelvins, Reff modulator 3-dB bandwidth), and an ERBW ¼ DS passband. is the effective input resistance, fsig is the analog input Continuous time DS ADCs do not usually require AAFs (it is frequency, ta is the rms aperture jitter, and fT is the transit- built-into the DS architecture) whereas discrete-time DS time frequency associated with the transistors used in the ADCs do. Again, the midband value of ENOB applies here. given ADC IC process technology. Two-tone intermodulation distortion (IMD) of ADCs is It is noted that for Nyquist ADCs, fsig in Equations (2)–(4) particularly relevant for receiver applications. One excites can be replaced by fsamp/2, and the resulting expressions an ADC with two sinusoids of equal amplitude but with would correspond closely, apart from one small numerical different frequencies, f1 and f2, and observes spurious tones difference in Equation (3), to those presented in Ref. 1 with in the FFT spectrum of the ADC output. The strongest such ENOB replacing B , where x is thermal or aperture or x x tone is usually second- (Æ f1 Æ f2) or third-order (Æ f1 Æ 2f2, ambiguity.However,fornon-Nyquistoperation,(e.g.,under- or Æ 2f1 Æ f2). Unfortunately, whereas IMD data are sampling),Equations (2)–(4) shouldbeusedaswritten above reported in the literature, no standard set of conditions because fsig can be different (greater) than fsamp/2. Hence, are available for IMD evaluation, which makes compari- these expressions are more general than those in Ref. 1. sons between ADCs somewhat difficult. Hence, IMDs must Another important ADC characteristic is spurious-free be evaluated by the prospective user for the intended appli- dynamic range (SFDR), which when expressed in dBc, is cation. the difference of the input signal magnitude and the largest spurious tone in the frequency-band of interest. The quan- tity SFDR bits is analogous to ENOB and is defined by ADC PERFORMANCE UPDATE SFDR bits ¼ SFDRðdBcÞ=6:02 ð5Þ Figure 1 shows ENOB as a function of analog input frequency (Fig. 1a) and of sampling rate (Fig. 1b) for A complete characterization of an ADC includes measuring state-of-the-art ADCs (as of late 2007).
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