Analog and Telecommunication Electronics - polito.it · Analog and Telecommunication Electronics D6...

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Politecnico di TorinoElectronic Eng. Master Degree

Analog and Telecommunication Electronics

D6 - High speed A/D converters» Spectral performance analysis» Undersampling techniques» Sampling jitter» Interleaving ADC» Dithering

AY 2015-16

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Lesson D6: high speed ADC

• Spectral performance analysis

• Undersampling techniques

• Sampling jitter

• Interleaving ADC

• Dithering

• References:– Application Report SLAA510 – January 2011– ADC Input Noise: Is No Noise Good Noise?

Analog Dialogue, - Febr 2006

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SNRt and ENOB

• Each unit in the ADC chain introduces errors and noise– Aliasing, quantization, sampling jitter– Other errors (amplifier, mux, …)

• Actual accuracy depends from all these elements– Key parameter: total Signal/Noise ratio: SNRt

– Not just the bit number N of the A/D

• ENOB = (SNRt - 1,76)/6 = SNR/6 - 0,3– Represents the number of actually useful bits of the ADC (sys)

• ENOB is always less then N– ENOB = N-1, N-2 .. good system design– ENOB < N-3 .. bad system design

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AD systems glossary (similar to ampl.)

• SNR: Signal-to-Noise Ratio. – Ps/Pn, excluding DC and first five harmonics (sometime first 9).

• SFDR: Spurious Free Dynamic Range. – Ps/Ph (Ph is the highest spur).

• THD: Total Harmonic Distortion. – Ps/Pd (Pd is the power of the first five (or 9) harmonics)

• SINAD: SIgnal to Noise And Distortion (SNRT for ADC). – Ps/(Pn+Pd) (no DC)

• Can be specified in – dBc (dB to carrier, reference is the fundamental), or – dBfs (dB to full scale, fundamental extrapolated to full-scale).

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Aliasing: Spectrum folding

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Folding of harmonics

spuriousHarm 2 Harm 3

Foldedharmonics

Fundamental

Harm 6

Largestspurious

(Ph)SFDR

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Spectral view of ADC parameters

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Spectral view of SFDR

Spurious Harm 2 Harm 3

Foldedharmonics

Fundamental

Harm 6

LargestspuriousSFDR

H2

Fundamental

3 4 5 6

3

Fs

Fs/2

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Oversampling

• Sampling at a rate far higher than the Nyquist limit – Example: 3 kHz audio signal (Nyquist = 6 kS/s)

8 kS/s Nyquist sampling; 1 MS/s Oversampling

• Oversampling sends aliased spectra far from baseband – Reduced aliasing noise, folded from first alias– Relaxed specifications on the anti-alias input filter

• Quantization noise is spread over a wider band (0 - Fs)– Reduced spectral density of quantization noise

• Higher bit rate (more samples/s)– Can be reduced with digital filtering

• Move complexity from analog digital domain

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Oversampling vs. Nyquist

X(ω)f

FS10

Main spectrum (baseband) First alias

2FS1

Second alias

X(ω)

f

FS20

First alias

Oversampling

Quantization noise (0-Fs1 band)

Nyquist

Quantization noise (0-Fs2 band)

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Oversampling vs. Nyquist filtering

X(ω)f

FS10 2FS1

X(ω)

f

FS20

Oversampling

Nyquist Steep filter

Smooth filter

Different filters:same quantization noise power (after reconstruction filter)

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Oversampling vs. Nyquist noise

X(ω)f

FS10 2FS1

Nyquist Steep filter

Same filter:reduced quantization noise power (after reconstruction filter)

X(ω)

f

FS20

Oversampling Steep filter

Removed quantization noise

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Which is the actual limit ?

• Actual Nyquist rule:– A signal must be sampled at least

twice the signal BANDWIDTH

– Example: a 1 GHz carrier, 100 kHz BW signal can be safely sampled at Fs > 200 ks/s

– Spectrum is folded around K Fs/2

• Less stringent specs for RF A/D converters– Sampling rate related with bandwidth, not carrier

• Tight specs for the S/H– sampling jitter related with carrier, not bandwidth

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Filter for Nyquist sampling

A/D

Complex analog LP filter

NYQUIST

X(ω)f

FS0 2FSFS/2

Spectrum segment folded to baseband (aliasing noise)

Steep antialias filter, to limit aliasing noise

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Oversampling: more simple filter

X()

FS20

Complex, steep digital filter:- reduce noise- reduce bit rate (decimation)

Alias is far away; antialias analogfilter can be simple

f

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Filters with oversampling

A/D

Simple analog filter

Complex digital filterCan reduce the bit rate (decimation)

NYQUIST

OVERSAMPLING

Complex analog LP filter

A/D

Move complexity from the analog to the digital domain

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Oversampling: noise shaping

In ΣΔ ADC noise power is moved to HF, with lower power density in baseband

X(ω)

f

FS20

Noise shaping

Shaped quantization noise

X(ω)

f

FS20

Oversampling Reconstruction filter

Flat quantization noise

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“Standard” sampling

• Sample at (at least) 2 x signal frequency– Keeps aliases out of useful band– Standard technique: signal rebuilt with low-pass filter

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Undersampling

• Sample at 2 x signal bandwidth(can be far less than signal frequency)

– Aliases arise, but out of useful band– Signal can be rebuilt with bandpass filter; no informatin loss

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Undersampling - correct

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Undersampling – not correct

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ADC example

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Block diagram

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Electrical characteristic

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Output signal spectrum

• Sampling rate 500 Ms/s (MSPS)

SFDR

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Undersampling

Sampling: 500 Ms/s < NyquistIn-band Alias (500-300)

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Intermodulation

• Input signal:• Fin1: 65,1 MHz• Fin2: 70,1 MHz

– Sideband at 65,1 – 570,1 + 5

– Higher sidebandat 65,1 – 1070,1 + 10

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Spurious Free Dynamic Range

dbFullScale: error referred to full scale (SNR independent from signal level)

dbCarrier: error referred to carrier(SNR depends on signal level)

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Clock jitter

• High speed ADC need “precise” sampling– low clock jitter differential clock– Effect of clock jitter: SNRj = -20 log10 2π Fin Tj

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Lesson D6 – final test

• Describe the limits of undersampling techniques.

• Plot spectrum of undersampled sinewave, with no distortion and with some distortion.

• Which parameters contribute to total sampling jitter?

• Describe the interleaving ADC technique and related benefits.

• Describe the averaging ADC technique and related benefits.

• Why dithering can improve ADC performance?

Analog and Telecommunication Electronics - polito.it · Analog and Telecommunication Electronics D6...

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