Continuous Time Sigma Delta Modulators and VCO ADCs Pieter Rombouts - - PowerPoint PPT Presentation

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Continuous Time Sigma Delta Modulators and VCO ADCs Pieter Rombouts Electronics and Information Systems Lab., Ghent University, Belgium Pavia, March 2017 P. Rombouts (Ghent University) CTSDMs and VCO ADCs Pavia 2017 1 / 80 Outline Sigma


slide-1
SLIDE 1

Continuous Time Sigma Delta Modulators and VCO ADCs

Pieter Rombouts

Electronics and Information Systems Lab., Ghent University, Belgium

Pavia, March 2017

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 1 / 80

slide-2
SLIDE 2

Outline

1

Sigma Delta Modulation

2

Continuous Time Sigma Delta Modulation

3

FoM Confusion

4

VCO ADC

5

Conclusion

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 2 / 80

slide-3
SLIDE 3

A/D converter: traditional interpretation

U I

converts analog value into digital number of bits n

◮ quantisation step q:

q = Vref /2n

error within ±q/2 staircase I/O

◮ static nonlinearity ◮ INL or DNL

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 3 / 80

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SLIDE 4

A/D converter: other interpretation

U I

U I Q

converts analog signal into digital signal quantisation eror Q

◮ (white) noise signal ◮ like other noise contributions ◮ number of bits not essential ⋆ large enough

Leave margin for other noise sources

⋆ effective bits

quantisation noise variance σ2

Q = q2

12

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 4 / 80

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SLIDE 5

Core concept 1: Oversampling

spectrum spectrum 0.1 0.2 0.3 0.4 0.5 signal white noise 0.1 0.2 0.3 0.4 0.5 frequency/fsample frequency/fsample

Oversampling ratio: OSR = fS 2f0

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 5 / 80

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SLIDE 6

Core concept 1: Oversampling

spectrum spectrum 0.1 0.2 0.3 0.4 0.5 signal white noise 0.1 0.2 0.3 0.4 0.5 frequency/fsample frequency/fsample

ideal digital filter after quantizer

◮ averaging mechanism ◮ number of bits has increased ◮ less noise ◮ filters signal as well ⋆ not Nyquist-rate anymore!

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 6 / 80

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SLIDE 7

Core concept 1: Oversampling

spectrum spectrum 0.1 0.2 0.3 0.4 0.5 signal white noise 0.1 0.2 0.3 0.4 0.5 frequency/fsample frequency/fsample

quantisation noise variance σ2

Q =

q2 12OSR ∼ 1 OSR 3dB/octave improvement

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 7 / 80

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SLIDE 8

The Σ∆ control loop

(a) (b)

  • quant

Vin Vin

+ +

  • D

H

  • +

D Q

H

DAC

ideal DAC filter

◮ discrete time ◮ continuous time

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 8 / 80

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SLIDE 9

The Σ∆ control loop

(a) (b)

  • quant

Vin Vin

+ +

  • D

H

  • +

D Q

H

DAC

D = H 1 + H Vin + 1 1 + H Q for low frequencies H ≈ ∞ − → D ≈ Vin nullator

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 9 / 80

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SLIDE 10

The Σ∆ control loop

D = H 1 + H Vin + 1 1 + H Q

  • error

input signal is also filtered for low frequencies NTF =

1 1+H ≈ 0

for high frequencies NTF =

1 1+H = 0

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 10 / 80

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SLIDE 11

Core concept 2: ”Noise” Shaping

NTF(z) DC

freq.

fsample/2 1

for high frequencies NTF =

1 1+H = 0

spectral shaping

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 11 / 80

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SLIDE 12

Core concept 2: “Noise” Shaping

(a) (b)

DC

freq.

fsample/2 DC

freq.

fsample/2 signal shaped noise

noise spectrum has the shape of NTF combine with oversampling − → most noise vanishes

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 12 / 80

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SLIDE 13

Σ∆ Modulators

(a) (b)

  • quant

Vin Vin

+ +

  • D

H

  • +

D Q

H

DAC

quantizer

◮ very few bits ◮ accuracy from oversampling + noise shaping ◮ 1 bit

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 13 / 80

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SLIDE 14

Σ∆ Modulators

(a) (b)

  • quant

Vin Vin

+ +

  • D

H

  • +

D Q

H

DAC

1-bit quantizer

◮ simple ◮ inherent linear ◮ noise is not white ⋆ tones ⋆ stability

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 14 / 80

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SLIDE 15

Σ∆ Modulators

(a) (b)

  • quant

Vin Vin

+ +

  • D

H

  • +

D Q

H

DAC

multi-bit quantizer

◮ better performance ◮ DAC needs linearization ⋆ DEM ⋆ calibration ◮ always larger area

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 15 / 80

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SLIDE 16

Σ∆ Modulators

(a) (b)

  • quant

Vin Vin

+ +

  • D

H

  • +

D Q

H

DAC

filter

◮ cascade of integrators ◮ order: design parameter ⋆ trade-off complexity-performance ◮ special design techniques ⋆ Richard Schreier’s toolbox

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 16 / 80

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SLIDE 17

1st order, 1bit Σ∆ Modulator

Typical circuit

+

  • C

Vref Vin

bi

C

+

  • bi

D Q clk

switched cap devices can be very small

◮ also C ◮ (thermal) noise ↓ due to oversampling

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 17 / 80

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SLIDE 18

High Order Σ∆ Modulators

Cascade of integrators with feedback

DAC 1 z -1 b2 1 z -1 c2

  • g1
  • a3

b3 b4

  • a2

c3 u(n) v(n) y(n) x3(n) x2(n 1 z -1 b1 c1 x1(n)

  • a1

without extra feed ins

◮ high swing on internal nodes ◮ ‘poor’ distortion performance

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 18 / 80

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SLIDE 19

High Order Σ∆ Modulators

Cascade of integrators with feedforward

DAC 1 z -1 b2 1 z -1 c3

  • g1

b3 b4 a3 u(n) v(n) y(n) x3(n) x2(n 1 z -1 b1 c2 x1(n)

  • c1

a2 a1

without extra feed ins

◮ negligible swing on internal nodes ◮ excellent distortion performance

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 19 / 80

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SLIDE 20

Σ∆ ADC

Sigma Delta modulator

lowpass filter

Vin anti-aliasing

prefilter

f < f

cutoff S

fS 2f0 Dout f = f

cutoff

analog digital decimation filter

several filters in chain

◮ simple anti-aliasing filter ◮ no sample-to-sample correspondence

number of bits in Dout high enough

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 20 / 80

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SLIDE 21

Σ∆ ADC

Sigma Delta modulator

lowpass filter

Vin anti-aliasing

prefilter

f < f

cutoff S

fS 2f0 Dout f = f

cutoff

analog digital decimation filter

scientific literature

◮ without filters ◮ accuracy calculated from ideal filter

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 21 / 80

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SLIDE 22

OSR

Low OSR?

◮ keep fs feasable ◮ need many quantizer bits ◮ need high order filter ◮ minimum 8

High OSR?

◮ small devices ⋆ noise is filtered ◮ low filter order ◮ 1-bit quantiser

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 22 / 80

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SLIDE 23

Outline

1

Sigma Delta Modulation

2

Continuous Time Sigma Delta Modulation

3

FoM Confusion

4

VCO ADC

5

Conclusion

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 23 / 80

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SLIDE 24

CTSDM vs DTSDM

Σ∆ modulators

◮ oversampling and noise shaping ◮ high-accuracy

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 24 / 80

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SLIDE 25

CTSDM vs DTSDM

Discrete-time

◮ versatile ◮ “simple” design ◮ easy to “abuse”

standard cell IP core

Continuous-time

◮ potential for higher speed ◮ potential for lower power ◮ anti-aliasing ◮ non-trivial design (needs tuning) ◮ performance and stability depend on fclk ◮ common myth: sensitive to clock jitter

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 25 / 80

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SLIDE 26

Continuous Time Σ∆ modulator

. . .

Vin(s) fs Dout(z) ZOH(s) ZOH(s) a1 sTs aN sTs

. . .

Σ Σ

Σ

− quant

closed feedback loop

◮ cascade of integrators with feedback ◮ cascade of integrators with feedforward . . .

loop filter = continuous time sampler inside loop

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 26 / 80

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SLIDE 27

Continuous Time Σ∆ modulator

Linearized model

. . .

Vin(s) fs Dout(z) ZOH(s) ZOH(s) a1 sTs aN sTs

. . .

Σ Σ

Σ

Σ Q

  • utput contains two contributions

◮ Input signal ◮ Quantisation noise

superposition

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 27 / 80

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SLIDE 28

Quantization noise

...

f s Dout(z) ZOH(s) ZOH(s) a1 sTs aN sTs

...

Σ Σ

Σ

Σ Q

Σ

ZOH(s) H(s) f s Heq(z) Dout(z)

Q

equivalent discrete time loop filter Heq(z)

◮ fully equivalent ◮ impulse invariant transform of H(s) ◮ CT - DT relationship: z = esTclk

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 28 / 80

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SLIDE 29

Quantization noise

Σ

ZOH(s) H(s) f s Heq(z) Dout(z)

Q

1 Heq + 1 · Q = NTF · Q equivalent to DT Σ∆ modulator

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 29 / 80

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SLIDE 30

Quantization noise

Σ

ZOH(s) H(s) f s Heq(z) Dout(z)

Q

remarks

◮ theory = mature ⋆ e.g. c2d function in matlab ◮ Heq depends on Dac-pulse ◮ Heq depends on fs ◮ Heq sensitive to analog imperfections ⋆ ‘excess’ loop delay ⋆ parasitic (opamp) poles

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 30 / 80

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SLIDE 31

Continuous Time Σ∆ modulator

Linearized model

. . .

Vin(s) fs Dout(z) ZOH(s) ZOH(s) a1 sTs aN sTs

. . .

Σ Σ

Σ

Σ Q

  • utput contains two contributions

◮ Input signal ◮ Quantisation noise

superposition

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 31 / 80

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SLIDE 32

Input signal

...

V

in(s)

f s Dout(z) ZOH(s) ZOH(s) a1 sTs aN sTs

...

Σ Σ

Σ

V

in(s)

Dout(z) G(s) f s

Σ

ZOH(s) H(s) f s Heq(z)

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 32 / 80

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SLIDE 33

Input signal

V

in(s)

Dout(z) G(s) f s

Σ

ZOH(s) H(s) f s Heq(z)

V

in(s)

D

  • ut(z)

G(s) f s V

in(s)

D

  • ut(z)

G(s) f s

AAF(s) NTF(z) NTF(z)

equivalent to filter AAF(s) = G(s) · NTF(z = esTclk) followed by sampler

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 33 / 80

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SLIDE 34

Anti-Aliasing in CTSDM

AAF(s) = G(s)NTF(z) Double filter effect in alias bands (around nfclk)

◮ G(S) lowpass filter ◮ NTF(z) notches at nfclk

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 34 / 80

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SLIDE 35

Anti-Aliasing in CTSDM

2−8 2−7 2−6 2−5 2−4 2−3 2−2 2−1 20 21

  • 100
  • 50

50 f/fs Amplitude response (dB) NTFeq(esTs) G(s) AAF(s) N = 2 a1 = 0.3246 a2 = 0.6667

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 35 / 80

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SLIDE 36

Feedback vs Feedforward

. . .

Vin(s) fs Dout(z) ZOH(s) ZOH(s) a1 sTs aN sTs

. . .

Σ Σ

Σ

− quant

cascade of integrators with feedback

◮ double anti-aliasing: G(s) and NTF ⋆ less stringent prefiltering requirements ◮ large internal signal swing ⋆ more demanding opamps ◮ ADC itself = power hungry but system may be more

efficient

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 36 / 80

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SLIDE 37

Feedback vs Feedforward

Vin

  • +

+ a1 sT quant an sT T H (s)

DAC

a2 sT D

+ +

cascade of integrators with feedforward

◮ single anti-aliasing: NTF but G(s) does not filter ⋆ stringent pre-filtering requirements ◮ small internal signal swing ⋆ no demanding opamps ◮ ADC itself = efficient but system may be power hungry

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 37 / 80

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SLIDE 38

Noise and power

Vin

  • +

+ a1 sT quant an sT T H (s)

DAC

a2 sT D

+ +

First stage noise dominates

◮ later stages scaled ⋆ lower power ⋆ still negligible noise

First stage power dominates as well

◮ increasing order ⇒ moderate impact on power

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 38 / 80

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SLIDE 39

Circuit Noise

Ev 2

n = 4kTReff · B

noise sees anti-aliasing filter

◮ only in band noise ◮ no kT/C noise

in theory much better than SC

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 39 / 80

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SLIDE 40

‘Excess’ Loop delay

CTSDM problems

Vin

  • +

+ a1 sT quant an sT T H (s)

DAC

a2 sT D

+ +

parasitic loop delay also parasitic poles

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 40 / 80

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SLIDE 41

‘Excess’ Loop delay

CTSDM problems Σ

c1 sTs

− Vin(s)

Σ

c2 sTs c3 sTs

a3

Σ

fs Vout(z) a2 a1 d HDAC(s) z−1 z− 1

2

− g e−sτ HDAC(s)

parasitic loop delay

◮ make loop delay explicit ◮ add compensation path

also for parasitic poles

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 41 / 80

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SLIDE 42

Process variations

CTSDM problems Σ

c1 sTs

− Vin(s)

Σ

c2 sTs c3 sTs

a3

Σ

fs Vout(z) a2 a1 d HDAC(s) z−1 z− 1

2

− g e−sτ HDAC(s)

large errors on RC products

◮ tune ◮ robust design

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 42 / 80

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SLIDE 43

Slew rate

CTSDM problems

  • pamp not allowed to slew

injection of quantisation noise

◮ multi-bit ◮ some filtering (e.g. FIR)

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 43 / 80

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SLIDE 44

Jitter

CTSDM problems Σ

c1 sTs

− Vin(s)

Σ

c2 sTs c3 sTs

a3

Σ

fs Vout(z) a2 a1 d HDAC(s) z−1 z− 1

2

− g e−sτ HDAC(s)

jitter in outer feedback DAC

◮ directly affects performance ◮ depends on DAC pulse

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 44 / 80

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SLIDE 45

Jitter

CTSDM problems

clock

ZOH

clock

ZOH ZOH

white jitter

◮ catastrophical ◮ solution: multi-bit, FIR etc.

lowpass jitter (= reality)

◮ no big deal

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 45 / 80

slide-46
SLIDE 46

CTSDM vs DTSDM

Continuous-time

◮ inherent anti-aliasing ⋆ no noise aliasing

cfr kT/C noise in switched cam

⋆ better power-noise trade off ◮ common myth ⋆ sensitive to clock jitter

⇒ not as bad as widely assumed

◮ facts ⋆ performance and stability depend on fclk ⋆ non-trivial design

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 46 / 80

slide-47
SLIDE 47

Outline

1

Sigma Delta Modulation

2

Continuous Time Sigma Delta Modulation

3

FoM Confusion

4

VCO ADC

5

Conclusion

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 47 / 80

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SLIDE 48

Figure of Merit

Need for FOM

◮ difficult to compare ADC architectures ◮ different Peak SNDR, Power, Bandwidth, Technology,

area

◮ which architecture for new design?

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 48 / 80

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SLIDE 49

Figure of Merit

Walden’s FOM (1999) FOMW = P 2ENOB 2 BW

◮ pJ/conversion code (or pJ/conversion step) ◮ intended to reduce variables ◮ no justification ◮ used for many years ◮ but meaningless . . .

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 49 / 80

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SLIDE 50

Justifying Walden’s FOM?

FOMW = P 2ENOB 2 BW in good design: P ∼ BW

◮ OK

P ∼ 2N

◮ ???

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 50 / 80

slide-51
SLIDE 51

Justifying Walden’s FOM?

P ∼ 2N ??? flash 2N comparators

◮ OK if comparator power

constant

comparator accuracy ∼ 2−N

◮ comparator power ∼ 2N ◮ comparator power ∼ 22N

  • ops . . .

Vin + + + +

  • D

D D D Q Q Q Q clk clk clk clk

Vref 1 1 1

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 51 / 80

slide-52
SLIDE 52

Impedance Scaling laws

I R (a) W L C V 2I R/2 2W L 2C V (b)

start from best design possible need 3dB better SNR

◮ scale impedances: factor 2

power: factor 4 per bit

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 52 / 80

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SLIDE 53

FOM confusion

FOMW = P 2ENOB 2 BW Walden fixed (scaling laws) FOMW ,fixed = P 22·ENOB 2 BW all high accuracy designs were rated bad . . . SAR’s were overrated . . .

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 53 / 80

slide-54
SLIDE 54

FOM confusion

FOMW ,corrected = P 22·ENOB 2 BW Walden fixed (scaling laws)

◮ not used

correct FOM: Schreier’s FOM (2005) FOMS = Peak SNDR + 10log10 BW P

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 54 / 80

slide-55
SLIDE 55

Outline

1

Sigma Delta Modulation

2

Continuous Time Sigma Delta Modulation

3

FoM Confusion

4

VCO ADC

5

Conclusion

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 55 / 80

slide-56
SLIDE 56

VCO-ADC: drivers

+ + + + + +

Ctrl N stages

Vdd Ctrl W 2W

main inverters aux inverters

4x 4x 1x 1x

vin+ vin- vout- vout+

quest for more digital ADC’s

◮ ring oscillators ◮ ‘digital’ signals ◮ no opamps

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 56 / 80

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SLIDE 57

VCO-ADC naive

VCO1 V

in

reset counter

kv fc

D

f s f s f s f s

accuracy ∼

fVCO fs

◮ e.g. 6-bit for fs = 1GHz, fVCO = 64GHz,

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 57 / 80

slide-58
SLIDE 58

VCO-ADC equivalent

VCO1 V

in

reset counter

kv fc

D

f s f s f s f s

VCO1 V

in

counter

kv fc

D

f s f s

I

1 - z-1 D

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 58 / 80

slide-59
SLIDE 59

VCO-ADC in phase domain

VCO1 V

in

counter

kv fc

D

f s f s

I

D VCO1

in

quant

kv fc

D

f s f s

I

D V

in

kv fc

D

s s I

D

in

1/s

kv fc

D

s

f s

I

1 - z-1 D + 1 - z-1

phase = integral of frequency edge occurs when phase = n · 2π phase information is quantized with step = 2π

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 59 / 80

slide-60
SLIDE 60

VCO-ADC in phase domain

V

in

kv fc

D

f s f s

I

D

in

1/s

kv fc

D

f s f s

I

D + + Q 1 - z-1

D(z) ∼

  • Vin
  • 1 − z−1

s ∗ +

  • 1 − z−1
  • NTF

Q like 1st order CTSDM

◮ anti-aliasing ◮ noise shaping ◮ boost accuracy by oversampling

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 60 / 80

slide-61
SLIDE 61

multi-phase VCO-ADC

+ + + + + +

Ctrl N stages

Vdd Ctrl W 2W

main inverters aux inverters

4x 4x 1x 1x

vin+ vin- vout- vout+

untill now 1 VCO output

◮ ring oscillator has N output phases

use all N VCO-phases

◮ now phase transition at 2π/N ◮ quantization error: N times smaller ◮ higher effective number of bits

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 61 / 80

slide-62
SLIDE 62

multi-phase VCO-ADC

use all N VCO-phases counter triggered by N clock inputs?

◮ use parallelism

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 62 / 80

slide-63
SLIDE 63

multi-phase VCO-ADC

VCO V

in

reset counter D

f s f s f s f s

reset counter

f s f s f s f s

reset counter

f s f s f s f s

adder

E.g. N = 64 phases, fs = 1GHz, fVCO = 1GHz,

◮ equivalent fs = 1GHz, fVCO = 64GHz, ◮ 6-bit

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 63 / 80

slide-64
SLIDE 64

multi-phase VCO-ADC

VCO V

in

reset counter D

f s f s f s f s

reset counter

f s f s f s f s

reset counter

f s f s f s f s

adder

Reset counter?

◮ special case: 1 bit counter ◮ possible if fVCO ≤ fs

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 64 / 80

slide-65
SLIDE 65

1-bit counter for VCO-ADCs

clk D Q

VCO[i] DFF

clk D Q ^

Dout

^

fs

+1 +1 +1

> <

(a) (b)

VCO3 CLK

Dout TS

> <

TS t t t

> <

TS

reacts on both edges

◮ effectively fVCO,eff = 2fVCO

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 65 / 80

slide-66
SLIDE 66

multi-phase VCO-ADC

ff w2(t) D Q D Q fs D Q D Q fs D Q D Q fs wM(t) w1(t) x(t)

+

... ...

y[n] M-phases ring oscillator Readout circuit (xM)

2 important properties

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 66 / 80

slide-67
SLIDE 67

multi-phase VCO-ADC

ff w2(t) D Q D Q fs D Q D Q fs D Q D Q fs wM(t) w1(t) x(t)

+

... ...

y[n] M-phases ring oscillator Readout circuit (xM)

  • utput = barrel shifted thermometer encoded

◮ inherent DWA ◮ can drive unit element DAC ◮ summation = ‘thermometer to binary” coder

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 67 / 80

slide-68
SLIDE 68

multi-phase VCO-ADC

ff w2(t) D Q D Q fs D Q D Q fs D Q D Q fs wM(t) w1(t) x(t)

+

... ...

y[n] M-phases ring oscillator Readout circuit (xM)

condition on fVCO:

◮ 0 < fVCO < fs/2

typical sizing:

◮ free running fVCO,0 = fs/4 ◮ KV for full scale swing ◮ some tuning

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 68 / 80

slide-69
SLIDE 69

VCO-ADC challenges

higher order noise shaping

◮ current research

VCO non-linearity

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 69 / 80

slide-70
SLIDE 70

VCO-ADC with high-order noise shaping

Current work at UGent ‘digital’ 3rd order VCO ADC

◮ prototype in 65 nm CMOS ◮ 12bits@10MHz (with digital calibration) ◮ 11bits@10MHz (without digital calibration) ◮ 3.5 mW ◮ 0.01 mm2

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 70 / 80

slide-71
SLIDE 71

VCO-ADC challenges

higher order noise shaping VCO non-linearity

◮ best: 11-bit linearity (UGent) ◮ other solutions ⋆ digital (self)-calibration ⋆ swing reduction ⋆ embed in Sigma Delta Loop

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 71 / 80

slide-72
SLIDE 72

Ghent University linear VCO circuit

ring oscillator VCO non-linearity

+ + + + + +

Ctrl N stages

Ring-Osc

Vin Ctrl R1 R2 Vdd

  • A. Babaie-Fishani and P. Rombouts,

“Highly linear VCO for use in VCO-ADCs,” Electron. Lett. 2016.

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 72 / 80

slide-73
SLIDE 73

Ghent University linear VCO circuit

ring oscillator VCO non-linearity

0.2 0.4 0.6 0.8 1 100 150 200 250 300 350 400 450 500

(a) Input voltage [volt] VCO Frequency [MHz]

0.2 0.4 0.6 0.8 1 −3 −2 −1 1 2 3

(b) Input voltage [volt] VCO Frequency error [MHz]

almost 12 bit linearity in pseudo differential configuration some noise penalty

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 73 / 80

slide-74
SLIDE 74

digital (self)-calibration

ring oscillator VCO non-linearity

Dout

non-linearity

f( )

  • versampling

noise-shaping modulator digital non-linearity correction

f-1( ) Ddec

decimation

V

in

look-up table

◮ nonlinearity is smooth ◮ can be very small (11 points excellent results)

some calibration mechanism

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 74 / 80

slide-75
SLIDE 75

Input swing reduction

ring oscillator VCO non-linearity

VCO reset counter f s

kv , fc

+ − V

in

ADCf DACf + Dout(z)

0-1 mash structure

◮ aux ADC and DAC ⋆ uncritical ◮ sensitive to mismatch

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 75 / 80

slide-76
SLIDE 76

VCO-ADC in sigma delta loop

ring oscillator VCO non-linearity

VCO reset counter Dout(z) f s

kv , fc

loop filter +

  • DAC

V

in

embed in Sigma Delta Loop

◮ Original work by Perrott’s group ◮ input signal of VCO still large

for e.g. 2nd order loop filter

◮ 3rd order noise shaping ◮ 2nd order suppression of VCO nonlinearity

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 76 / 80

slide-77
SLIDE 77

Phase domain VCO-ADC

VCO in feedback loop

VCO2

kv , fc

  • ut

VCO1

kv , fc

Vin +

  • PD

+

  • VCO2

kv , fc

VCO1

kv , fc

+

  • PD

+

  • register

f s

sampler

Dout(z) + − DAC V

in

VCO performs integration

◮ pseudo differential

Phase detector

◮ can be largely digital

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 77 / 80

slide-78
SLIDE 78

Phase domain VCO-ADC

VCO in feedback loop

VCO2

kv , fc

VCO1

kv , fc

+

  • PD

+

  • register

f s

sampler

Dout(z) + − DAC V

in

VCO performs integration

◮ pseudo differential

Phase detector

◮ can be largely digital ◮ can be multi-phase

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 78 / 80

slide-79
SLIDE 79

VCO-ADC in sigma delta loop

ring oscillator VCO non-linearity

VCO2

kv , fc

VCO1

kv , fc

+

  • PD

+

  • register

f s

sampler

Dout(z) DAC loop filter +

  • V

in

for e.g. 2nd order loop filter

◮ 3rd order noise shaping ◮ input signal of VCO small ◮ 3rd order suppression of VCO nonlinearity

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 79 / 80

slide-80
SLIDE 80

Conclusion

Review of

1

Sigma Delta Modulation

2

Continuous Time Sigma Delta Modulation

3

FoM Confusion

4

VCO ADC

5

Conclusion

  • P. Rombouts (Ghent University)

CTSDMs and VCO ADCs Pavia 2017 80 / 80