Oversampling High Order

31
EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 1 EE247 Lecture 24 Oversampled ADCs Why oversampling? Pulse-count modulation Sigma-delta modulation 1-Bit quantization Quantization error (noise) spectrum SQNR analysis Limit cycle oscillations –2 nd order ΣΔ modulator Dynamic range Practical implementation Effect of various nonidealities on the ΣΔ performance EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 2 The Case for Oversampling Nyquist sampling: Oversampling: Nyquist rate f N = 2B Oversampling rate M = f s /f N >> 1 f s >2B + δ Freq B Signal “narrow” transition Sampler AA-Filter “Nyquist” ADC DSP = M Freq B Signal “wide” transition Sampler AA-Filter Oversampled ADC DSP f s f s f N f s >> f N ??

Transcript of Oversampling High Order

Page 1: Oversampling High Order

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 1

EE247Lecture 24

Oversampled ADCs– Why oversampling?– Pulse-count modulation– Sigma-delta modulation

• 1-Bit quantization• Quantization error (noise) spectrum• SQNR analysis• Limit cycle oscillations

– 2nd order ΣΔ modulator• Dynamic range • Practical implementation

– Effect of various nonidealities on the ΣΔ performance

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 2

The Case for OversamplingNyquist sampling:

Oversampling:

• Nyquist rate fN = 2B• Oversampling rate M = fs/fN >> 1

fs >2B +δFreqB

Signal

“narrow”transition

SamplerAA-Filter

“Nyquist”ADC DSP

=MFreqB

Signal

“wide”transition

SamplerAA-Filter

OversampledADC DSP

fs

fs fN

fs >> fN??

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 3

Nyquist v.s. Oversampled ConvertersAntialiasing

|X(f)|

frequency

frequency

frequency

fB

fB 2fs

fB fs

Input Signal

Nyquist Sampling

Oversampling

fS ~2fB

fS >> 2fB

fs

Anti-aliasing Filter

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 4

Oversampling Benefits• No stringent requirements imposed on analog

building blocks • Takes advantage of the availability of low

cost, low power digital filtering• Relaxed transition band requirements for

analog anti-aliasing filters• Reduced baseband quantization noise power• Allows trading speed for resolution

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 5

ADC ConvertersBaseband Noise

• For a quantizer with step size Δ and sampling rate fs :– Quantization noise power distributed uniformly across Nyquist

bandwidth ( fs/2)

– Power spectral density:

– Noise is aliased into the Nyquist band –fs /2 to fs /2

2 2

es s

e 1N ( f )

f 12 f

⎛ ⎞Δ= = ⎜ ⎟

⎝ ⎠

-fB f s /2-fs /2 fB

Ne(f)

NB

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 6

Oversampled ConvertersBaseband Noise

B B

B B

f f 2

B ef f s

2B

s

B s2

B0

B B0B B0

ss

B

1S N ( f )df df

12 f

2 f12 f

where for f f / 2

S12

2 f SS S

f Mf

where M oversampling rat io2 f

− −

⎛ ⎞Δ= = ⎜ ⎟

⎝ ⎠

⎛ ⎞Δ= ⎜ ⎟⎜ ⎟

⎝ ⎠

=

⎛ ⎞= =⎜ ⎟⎜ ⎟

⎝ ⎠= =

∫ ∫

-fB f s /2-fs /2 fB

Ne(f)

NB

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 7

Oversampled ConvertersBaseband Noise

2X increase in M3dB reduction in SB½ bit increase in resolution/octave oversampling

B B0B B0

ss

B

2 f SS S

f Mf

where M oversampling rat io2 f

⎛ ⎞= =⎜ ⎟⎜ ⎟

⎝ ⎠= =

To increase the improvement in resolution: Embed quantizer in a feedback loop

Predictive (delta modulation)Noise shaping (sigma delta modulation)

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 8

Pulse-Count Modulation

Vin(kT) Nyquist ADC

t/T0 1 2

OversampledADC, M = 8

t/T0 1 2

Vin(kT)

Mean of pulse-count signal approximates analog input!

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 9

Pulse-Count Spectrum

f

Magnitude

• Signal: low frequencies, f < B << fs• Quantization error: high frequency, B … fs / 2• Separate with low-pass filter!

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 10

Oversampled ADCPredictive Coding

• Quantize the difference signal rather than the signal itself• Smaller input to ADC Buy dynamic range• Only works if combined with oversampling• 1-Bit digital output• Digital filter computes “average” N-Bit output

+

_vIN

DOUT

Predictor

ADC

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 11

Oversampled ADC

Decimator:• Digital (low-pass) filter• Removes quantization error for f > B• Provides most anti-alias filtering• Narrow transition band, high-order• 1-Bit input, N-Bit output (essentially computes “average”)

fs= MfN

FreqB

Signal“wide”

transition

SamplerAnalogAA-Filter

E.g.Pulse-CountModulator

Decimator“narrow”transition

fs1= M fN

DSP

Modulator DigitalAA-Filter

fs2= fN+ δ

1-Bit Digital N-BitDigital

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 12

Modulator

• Objectives:– Convert analog input to 1-Bit pulse density stream– Move quantization error to high frequencies f >>B– Operates at high frequency fs >> fN

• M = 8 … 256 (typical)….1024• Since modulator operated at high frequencies need to

keep circuitry “simple”

ΣΔ = ΔΣ Modulator

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 13

Sigma- Delta ModulatorsAnalog 1-Bit ΣΔ modulators convert a continuous time analog input vIN into a 1-Bit sequence dOUT

H(z)+

_vIN dOUT

Loop filter 1b Quantizer (comparator)

fs

DAC

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 14

Sigma-Delta Modulators• The loop filter H can be either switched-capacitor or continuous time• Switched-capacitor filters are “easier” to implement + frequency

characteristics scale with clock rate• Continuous time filters provide anti-aliasing protection• Loop filter can also be realized with passive LC’s at very high frequencies

H(z)+

_vIN

dOUT

fs

DAC

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 15

Oversampling A/D Conversion

• Analog front-end oversampled noise-shaping modulator• Converts original signal to a 1-bit digital output at the high rate of

(2MXB)• Digital back-end digital filter

• Removes out-of-band quantization noise• Provides anti-aliasing to allow re-sampling @ lower sampling rate

1-bit@ fs

n-bit@ fs /M

Input Signal Bandwidth

B=fs /2MDecimation

FilterOversampling

Modulator

fs

fs = sampling rateM= oversampling ratio

fs /M

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 16

1st Order ΣΔ ModulatorIn a 1st order modulator, simplest loop filter an integrator

+

_vIN dOUT∫

H(z) =z-1

1 – z-1

DAC

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 17

1st Order ΣΔ ModulatorSwitched-capacitor implementation

Vi

-

+

φ1 φ2 φ2

1,0dOUT

+Δ/2

-Δ/2

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 18

1st Order ΔΣ Modulator

• Properties of the first-order modulator:– Analog input range is equal to the DAC reference– The average value of dOUT must equal the average value of vIN– +1’s (or –1’s) density in dOUT is an inherently monotonic function of vIN

linearity is not dependent on component matching– Alternative multi-bit DAC (and ADCs) solutions reduce the quantization error

but loose this inherent monotonicity & relaxed matching requirements

+

_vIN

dOUT

∫-Δ/2≤vIN≤+Δ/2

DAC-Δ/2 or +Δ/2

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 19

1st Order ΣΔ Modulator

Instantaneous quantization error

Tally of quantization error

1-Bitquantizer

1-Bit digital output stream,

-1, +1

Implicit 1-Bit DAC+Δ/2, -Δ/2

(Δ = 2)

Analog input-Δ/2≤Vin≤+Δ/2

3Y

2Q

1X

Sine Wave

z -1

1-z -1Integrator Comparator

• M chosen to be 8 (low) to ease observability

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 20

1st Order Modulator Signals

T = 1/fs = 1/ (M fN)

X analog inputQ tally of q-errorY digital/DAC output

Mean of Y approximates X

0 10 20 30 40 50 60

-1.5

-1

-0.5

0

0.5

1

1.5

Time [ t/T ]

Am

plitu

de

1st Order Sigma-DeltaXQY

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 21

ΣΔ Modulator Characteristics• Quantization noise and thermal noise (KT/C)

distributed over –fs /2 to +fs /2Total noise within signal bandwidth reduced by

1/M• Very high SQNR achievable (> 20 Bits!)• Inherently linear for 1-Bit DAC• To first order, quantization error independent

of component matching• Limited to moderate & low speed

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 22

Output Spectrum• Definitely not white!

• Skewed towards higher frequencies

• Notice the distinct tones

• dBWN (dB White Noise) scale sets the 0dB line at the noise per bin of a random -1, +1 sequence

Input

0 0.1 0.2 0.3 0.4 0.5-50

-40

-30

-20

-10

0

10

20

30

Frequency [ f /fs]

Am

plitu

de

[ dB

WN

]

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 23

Quantization Noise Analysis

• Sigma-Delta modulators are nonlinear systems with memory difficult to analyze directly

• Representing the quantizer as an additive noise source linearizes the system

Integrator

ΣQuantizer

Model

QuantizationError e(kT)

x(kT) y(kT)1

1H( )1

zzz

−=+ Σ

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 24

Signal Transfer Function

( )

1

1

0

H( )1

zzz

H jjωωω

−=+

=

Signal transfer function low pass function:

IntegratorH(z)Σ

x(kT)y(kT)

-

Frequency

Mag

nitu

de

f0

( )

( )0

1

1 1

( ) ( ) Delay( ) 1 ( )

Sig

Sig

H j s

Y z H zH z zX z H z

ωω

=+

= = = ⇒+

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 25

Noise Transfer FunctionQualitative Analysis

2eqv

22

0n

fv f⎛ ⎞× ⎜ ⎟⎝ ⎠

Σvi

-vo0

jωω

22 2

0eq n

fv v f⎛ ⎞= × ⎜ ⎟⎝ ⎠

Σvi -vo0

jωω

Frequencyf0

2nv

Σvi

-vo0

jωω

2 2

0eq n

fv v f⎛ ⎞= × ⎜ ⎟⎝ ⎠

• Input referred-noise zero @ DC (s-plane)

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 26

STF and NTF

Signal transfer function:1( ) ( )STF Delay

( ) 1 ( )Y z H z zX z H z

−= = = ⇒+

Noise transfer function:

erentiator Diff 1)(1

1)()(NTF 1 ⇒−=

+== −z

zHzEzY

Integrator

ΣQuantizer

Model

QuantizationError e(kT)

x(kT) y(kT)1

1H( )1

zzz

−=+ Σ

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 27

Noise Transfer Function

( )( )

( ) ( )

( ) ( )

1

/ 2 / 2/ 2

/ 2

/ 2 / 2

/ 2

( ) 1 1 ( ) 1 ( )

( ) (1 )=22

2 sin / 2

2 sin / 2

2sin / 2

where 1/Thus:

( ) =2 sin / 2 =2 sin /

( )

j T j Tj T j T

j T

j T j

j T

s

s

y

Y zNTF zE z H z

e eNTF j e e

e j T

e e T

T e

T f

NTF f T f f

N f

ω ωω ω

ω

ω π

ω π

ω

ω

ω

ω

ω π

−− −

− −

− −

= = = −+

⎛ ⎞−= − ⎜ ⎟⎝ ⎠

=

= × ⎡ ⎤⎣ ⎦

= ⎡ ⎤⎣ ⎦=

= 2( ) ( )eNTF f N f

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 28

First Order ΣΔ ModulatorNoise Transfer Characteristics

( )

2

2

( ) ( ) ( )

4 sin /

y e

s

N f NTF f N f

f fπ

=

=

Noi

se S

hapi

ng F

unct

ion

FrequencyfB fN fs /2

First-Order Noise Shaping

Low-passDigital Filter

Key Point:Most of quantization noise pushed out of frequency band of interest

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 29

First Order ΣΔ ModulatorSimulated Noise Transfer Characteristic

0 0.1 0.2 0.3 0.4 0.5-50

-40

-30

-20

-10

0

10

20

30

Frequency [f/fs]

Ampl

itude

[ d

BW

N ]

Simulated output spectrumComputed NTF

Signal

( ) 2( ) 4 sin /y sN f f fπ=

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 30

Quantizer Error• For quantizers with many bits

• Let’s use the same expression for the 1-Bit case

• Use simulation to verify validity

• Experience: Often sufficiently accurate to be useful, with enough exceptions to be very careful

( )12

22 Δ=kTe

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 31

First Order ΣΔ ModulatorIn-Band Quantization Noise

( )( ) ( )

( ) ( )

( )

2

2

2

1

2 2

2

2 2

2 2

3

1

4 sin / for 1

1 2sin12

13 12

jfT

fsM

fsM

s

B

Y Q z eB

s

Y

NTF z z

NTF f f f M

S S f NTF z df

fT dff

SM

π

π

π

π

=−

= −

= >>

=

Δ≅

Δ→ ≈

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 32

Dynamic Range

M DR16 33 dB32 42 dB

1024 87 dB

2

2 2

3

32

32 2

peak signal power10log 10logpeak noise power

1 sinusoidal input, 12 2

13 129

29 910log 10log 30log

2 2

3.4 30l

X

Y

X

Y

X

Y

SDRS

S STF

SM

S MS

DR M M

DR dB

π

π

π π

⎡ ⎤⎡ ⎤= = ⎢ ⎥⎢ ⎥⎣ ⎦ ⎣ ⎦

Δ⎛ ⎞= =⎜ ⎟⎝ ⎠

Δ=

=

⎡ ⎤ ⎡ ⎤= = +⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎣ ⎦

= − + + og M

2X increase in M 9dB (1.5-Bit) increase in dynamic range

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 33

Oversampling and Noise Shaping

• ΣΔ modulators have interesting characteristics– Unity gain for input signal VIN– Large in-band attenuation of quantization noise injected at quantizer

input– Performance significantly better than 1-Bit noise performance possible

for frequencies << fs

• Increase in oversampling (M = fs/fN >> 1) improves SQNR considerably– 1st order ΣΔ: DR increases 9dB for each doubling of M– To first order, SQNR independent of circuit complexity and accuracy

• Analysis assumes that the quantizer noise is “white”– Not true in practice, especially for low-order modulators– Practical modulators suffer from other noise sources also

(e.g. thermal noise)

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 34

DC Input

• DC input A = 1/11

• Doesn’t look like spectrum of DC at all

• Tones frequency shaped the same as quantization noise

More prominent at higher frequencies

Seems like periodic quantization “noise”

0 0.1 0.2 0.3 0.4 0.5-50

-40

-30

-20

-10

0

10

20

30

Frequency [ f /fs ]

Am

plitu

de

[ dB

WN

]

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 35

Limit Cycle

-111+110-19+18-17+16-15+14-13+12+11

DC input 1/11 Periodic sequence:

0 10 20 30 40 50

-0.4

-0.2

0

0.2

0.4

0.6

Time [t/T]

Out

put

First order sigma-delta, DC input

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 36

Limit Cycle

In-band spurious tone with f ~ DC input

• Problem: quantization noise is periodic•Solution:

Use dithering: randomizes quantization noise- Thermal noise acts as dither

Second order loop

Noi

se S

hapi

ng F

unct

ion

FrequencyfB fN fs /2

First-Order Noise Shaping

Ideal Low-passDigital Filter

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 37

1st Order ΣΔ Modulator

( )1 1( ) ( ) 1 ( ) Y z z X z z E z− −= + −

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 38

2nd Order ΣΔ Modulator

• Two integrators• 1st integrator non-delaying• Feedback from output to both integrators• Tones less prominent compared to 1st order

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 39

2nd Order ΣΔ Modulator

( )

( )1 1 2

21 1 1

Recursive drivation: 2

Using the delay operator : ( ) ( ) 1 ( )

n n n n nY X E E E

z Y z z X z z E z

− − −

− − −

= + − +

= + −

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 40

2nd Order ΣΔ ModulatorIn-Band Quantization Noise

( )

( ) ( )( )

( )

1

1

21

2

44

11

1

2 sin / for 1s

zH zz

G

NTF z z

NTF f

f f Mπ

=−

=

= −

=

= >>

( ) ( )

( )

2

2

2

2

24

4 2

5

1 2sin12

15 12

jfT

fsM

fsM

B

Y Q z eB

s

S S f NTF z df

fT dff

M

π

π

π

=−

=

Δ≅

Δ≈

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 41

Quantization Noise2nd Order ΣΔ Modulator

Noi

se S

hapi

ng F

unct

ion

FrequencyfB fs /2

First-Order Noise Shaping

Ideal Low-passDigital Filter

2nd -Order Noise Shaping

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 42

2nd Order ΣΔ Modulator Dynamic Range

M DR16 49 dB32 64 dB

1024 139 dB

2

4 2

5

54

54 4

peak signal power10log 10logpeak noise power

1 sinusoidal input, 12 2

15 1215

215 1510log 10log 50log

2 2

11.1

X

Y

X

Y

X

Y

SDRS

S STF

SM

S MS

DR M M

DR dB

π

π

π π

⎡ ⎤⎡ ⎤= = ⎢ ⎥⎢ ⎥⎣ ⎦ ⎣ ⎦

Δ⎛ ⎞= =⎜ ⎟⎝ ⎠

Δ=

=

⎡ ⎤ ⎡ ⎤= = +⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎣ ⎦

= − + 50log M+

2X increase in M 15dB (2.5-bit) increase in DR

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 43

2nd Order ΣΔ Modulator Example

M 256=28 to allow some margin & also for ease of digital filter implementation

Sampling rate (2x20kHz + 5kHz)M = 12MHz

•Digital audio application•Signal bandwidth 20kHz•Resolution 16-bit

min

16 98 Dynamic Range

11.1 50log153

bit dB

DR dB MM

− →

= − + +=

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 44

Higher Order ΣΔ Modulator Dynamic Range

2X increase in M (6L+3)dB or (L+0.5)-bit increase in DR

( )

( )

( )

( )

1 1

2

2 2

2 1

2 12

2 12

2

( ) ( ) 1 ( ) , L order

1 sinusoidal input, 12 2

12 1 123 2 1

23 2 1

10log2

3 2 110log 2

2

L

X

L

Y L

LXL

Y

LL

L

Y z z X z z E z

S STF

SL M

LS MS

LDR M

LDR

π

π

π

π

− −

+

+

+

⎛ ⎞⎜ ⎟⎝ ⎠

⎡ ⎤⎢ ⎥⎢ ⎥⎣ ⎦

⎡ ⎤⎢ ⎥⎢ ⎥⎣ ⎦

= + − → ΣΔ

Δ= =

Δ=+

+=

+=

+= + ( )1 10 logL M+ × ×

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 45

ΣΔ Modulator Dynamic RangeAs a Function of Modulator Order

• Potential stability issues for L >2

L=2

L=3

L=1

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 46

Tones in 1st Order & 2nd Order ΣΔ Modulator

• Higher oversampling ratio lower tones

• 2nd order much lower tones compared to 1st

• 2X increase in M decreases the tones by 6dB for 1st order loop and 12dB for 2nd order loop

Ref: B. P. Brandt, et al., "Second-order sigma-delta modulation for digital-audio signal acquisition,"

IEEE Journal of Solid-State Circuits, vol. 26, pp. 618 - 627, April 1991.R. Gray, “Spectral analysis of quantization noise in a single-loop sigma–delta modulator with dc

input,” IEEE Trans. Commun., vol. 37, pp. 588–599, June 1989.

6dB

12dB 2nd Order ΣΔ Modulator

1st Order ΣΔ Modulator

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 47

2nd Order ΣΔ ModulatorSwitched-Capacitor Implementation

IN Dout

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 48

Switched-Capacitor Implementation 2nd Order ΣΔPhase 1

•Sample inputs•Compare output of 2nd integrator•At the end of phase1, S3 opens prior to S1 opening

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Switched-Capacitor Implementation 2nd Order ΣΔPhase 2

• Enable feedback from output to input of both integrators• Integrate• Reset comparator• At the end of phase2 S4 opens before S2

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 50

ΣΔ ImplementationPractical Design Considerations

• Internal nodes scaling & clipping

• Finite opamp gain & linearity

• Capacitor ratio errors

• KT/C noise

• Opamp noise

• Power dissipation considerations

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 51

Switched-Capacitor Implementation 2nd Order ΣΔNodes Scaled for Maximum Dynamic Range

• Modification (gain of ½ in front of integrators) reduce & optimize required signal range at the integrator outputs ~ 1.7x input full-scale (Δ)

Ref: B.E. Boser and B.A. Wooley, “The Design of Sigma-Delta Modulation A/D Converters,” IEEE J. Solid-State Circuits, vol. 23, no. 6, pp. 1298-1308, Dec. 1988.

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 52

2nd Order ΣΔ ModulatorSwitched-Capacitor Implementation

C2=2C1

• The ½ loss in front of each integrator implemented by choice of:

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EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 53

2nd Order ΣΔEffect of Integrator Maximum Signal Handling Capability on SNR

• Effect of 1st Integrator maximum signal handling capability on converter SNRRef: B.E. Boser and B.A. Wooley, “The Design of Sigma-Delta Modulation A/D Converters,”

IEEE J. Solid-State Circuits, vol. 23, no. 6, pp. 1298-1308, Dec. 1988.

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 54

2nd Order ΣΔEffect of Integrator Maximum Signal Handling Capability on SNR

• Effect of 2nd Integrator maximum signal handling capability on SNRRef: B.E. Boser and B.A. Wooley, “The Design of Sigma-Delta Modulation A/D Converters,”

IEEE J. Solid-State Circuits, vol. 23, no. 6, pp. 1298-1308, Dec. 1988.

Page 28: Oversampling High Order

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 55

2nd Order ΣΔEffect of Integrator Finite DC Gain

Vi

-

+

φ1 φ2

aVo

Cs

CI( )

( )

1

1

1

1

1

1

111

ideal

Finit DC Gain

Cs zH zCI z

a zCsaCs CIH zCI

a zCsaCI

= ×−⎛ ⎞⎜ ⎟⎜ ⎟

+ +⎜ ⎟⎝ ⎠= ×⎛ ⎞⎜ ⎟+− ⎜ ⎟

+ +⎜ ⎟⎝ ⎠

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 56

2nd Order ΣΔEffect of Integrator Finite DC Gain

• Low integrator DC gain Increase in total in-band noise • Can be shown: If a > M (oversampling ratio) Insignificant degradation in

SNR• Normally DC gain designed to be >> M in order to suppress nonlinearities

f0 /a

a

0P1 aω=

a

( )log H s Ideal Integ. (a=infinite)

Integrator magnitude response

Max signal level

Page 29: Oversampling High Order

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 57

2nd Order ΣΔEffect of Integrator Finite DC Gain

• Example: a =2M 0.4dB degradation in SNRRef: B.E. Boser and B.A. Wooley, “The Design of Sigma-Delta Modulation A/D Converters,”

IEEE J. Solid-State Circuits, vol. 23, no. 6, pp. 1298-1308, Dec. 1988.

M / a

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 58

2nd Order ΣΔEffect of Integrator Overall Integrator Gain Inaccuracy

• Gain of ½ in front of integrators determined by ratio of C1/C2

• Effect of inaccuracy in ratio of C1/C2 inspected by simulation

Page 30: Oversampling High Order

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 59

2nd Order ΣΔEffect of Integrator Overall Gain Inaccuracy

• Simulation show gain can vary by 20% w/o loss in performanceConfirms insensitivity of ΣΔ to component variations

• Note that for gain >0.65 system becomes unstable & SNR drops rapidly

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 60

2nd Order ΣΔEffect of Integrator Nonlinearities

2 32 3

2 32 3

v( kT T ) u(kT ) v( kT )

With non-linearity added:

v( KT T ) u(kT ) .....u(kT ) u(kT )v( kT ) ....v( kT ) v( kT )

α αβ β

⎡ ⎤ ⎡ ⎤⎣ ⎦ ⎣ ⎦

⎡ ⎤ ⎡ ⎤⎣ ⎦ ⎣ ⎦

+ = +

+ = + +

+ + + +

Ref: B.E. Boser and B.A. Wooley, “The Design of Sigma-Delta Modulation A/D Converters,” IEEE J. Solid-State Circuits, vol. 23, no. 6, pp. 1298-1308, Dec. 1988

Delay

Ideal Integrator

u(kT) v(kT)

Page 31: Oversampling High Order

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 61

2nd Order ΣΔEffect of Integrator Nonlinearities

Ref: B.E. Boser and B.A. Wooley, “The Design of Sigma-Delta Modulation A/D Converters,” IEEE J. Solid-State Circuits, vol. 23, no. 6, pp. 1298-1308, Dec. 1988.

• Simulation for single-ended topology• Even order nonlinearities can be significantly attenuated by using

differential circuit topologies

2 20.01, 0 .02,0.05, 0.1%

α β= =

EECS 247 Lecture 24: Oversampling Data Converters © 2005 H. K. Page 62

2nd Order ΣΔEffect of Integrator Nonlinearities

Ref: B.E. Boser and B.A. Wooley, “The Design of Sigma-Delta Modulation A/D Converters,” IEEE J. Solid-State Circuits, vol. 23, no. 6, pp. 1298-1308, Dec. 1988.

• Simulation for single-ended topology• Odd order nonlinearities (3rd in this case)

3 30.05, 0.2, 1%

α β= =

6dB 1=Bit