cmos switched-capacitor circuits: recent advances in bio

ASU August 17, 2011

CMOS Switched-Capacitor Circuits: Recent Advances in Bio-Medical and

RF Applications

David J. Allstot

Univ. of WashingtonDept. of Electrical Engineering

Seattle, WA 98195-2500

ASU August 17, 2011

2010: 4.6 B subscribers

2012: 1 B WiFi US mobile phones: Use yearly

energy of 638,000 US Homes

Emit 6K tons CO2

Demand increases with newer data phones

PA is dominant energy hog

Motivation

PAMetropolitan Seattle Area

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ASU August 17, 2011

CMOS PA Trends: Pout

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J.S. Walling, S.S. Taylor and D.J. Allstot, “A class-G supply modulator and class-E PA in 130 nm CMOS,” IEEE JSSC, pp. 2339-2347, Sept. 2009. S.-M. Yoo, J.S. Walling, E.C. Woo and D.J. Allstot, “A switched-capacitor power amplifier for EER/Polar transmitters,” IEEE ISSCC Dig. Tech. Papers, pp. 428-429, 2011.

ASU August 17, 2011

CMOS PA Trends: PAE

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ASU August 17, 2011

Outline

Challenges in CMOS RF PA Design Switched-Capacitor PA Solution Analog-domain Compressed Sensing for

Bio-signal Acquisition

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2

=2

V Vout

DD SAT

L

PR

VDD

VDD Scaling

Impedance Transformation

Challenge: Max Power Out

RL=

50

Vout1 : n

Ropt=

RL/n2

45 nm CMOS 1W, VDD = 1.0 V VSAT = 0.2 V Ropt 0.3 Parasitic R Limit)

Linear PAs

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ASU August 17, 2011

Linear Power Amplifiers– AM Signals (i.e., non-

Constant Envelope)

– Class-A:

– Class-B:– Class-AB– Class-C: Peak = 100%

@ Pout = 0 (Attractive for Body Area Networks)

Challenge: Efficiency

= L

DC

PP

2V= 0.5 out

DDV

2

=4

out

DD

VV

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ASU August 17, 2011

ON

OFF

Switching Power Amplifiers– PM and FM Signals

(i.e., Constant Envelope)

Class D, E, F, etc. Zero-V Switching

– Rise in vD delayed until switch OFF

– vD = 0 @ switch ON dvD/dt = 0 @ switch

OFF

Ideal = 100%

Impedance Transformer & Wave-Shaping Network

= = 0DC D DP v i

Challenge: EfficiencyClass-E PA

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ASU August 17, 2011

0 0.2 0.4 0.6 0.8 10

20

40

60

80

100

Normalized Envelope (V)

Ocu

rren

ces

(%)

0 0.2 0.4 0.6 0.8 10

5

10

15

20

25


Ocu

rren

ces

(%)

0 0.2 0.4 0.6 0.8 10

5

10

15

20

25


Ocu

rren

ces

(%)

FM QAM 64-QAMSpectral vs. Energy Efficiency

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ASU August 17, 2011

Linearization Techniques Feedforward Feedback LINC – Linear Amp with Nonlinear Components EER – Envelope Elimination and Restoration

– Can use highly-efficient switching PA; e.g., Class-E

– Pout VDD for Switching PA– Split signal into envelope (A) & phase () paths– Improved overall efficiency– Distortion from delay mismatches in A & paths

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ASU August 17, 2011

A

Kahn EER Technique (1952)

Polar conversion in DSP using CORDIC Algorithm DAC and supply modulator needed

Original Kahn

Modern Kahn

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ASU August 17, 2011

LDO = Low-dropout Reg.

iout

LDO Modulator & Efficiency

LDO

Overall efficiency is product of supply modulator and PA efficiencies

Increased over Linear PA

LDO Characteristics– Vout ≈ ENVin

–––

out out outP v iDD outDCP v i

/ /out DC out DDP P v V

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ASU August 17, 2011

Dual-Supply Modulator

Class-G: Spectral vs. Energy Efficiency Small envelope:

Use Vdd/x Large envelope:

Use Vdd

Extend to more than two power supplies? Class-H?

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ASU August 17, 2011

0 0.2 0.4 0.6 0.8 10

20

40

60

80

100

Vout (V)

Dra

in E

ffici

ency

(%)

Class-G

Class-B

OFDM PDF

0 0.2 0.4 0.6 0.8 10

2

4

6

8

10

Prob

abili

ty (%

)

Avg. Class-B

Class-G: Spectral vs. Energy Efficiency

Avg. Class-G

Overall efficiency is product of class-G modulator and class-E PA efficiencies

Ideally 5X higher average than linear PA for this probability density function

Class-E

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ASU August 17, 2011

Class-E PA and Driver

Interstage tuning inductors reduce driver powerDriver taper of 2 – custom stages

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ASU August 17, 2011

130nm Class-G PA

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Class-G Static Measurements

0 0.2 0.4 0.6 0.8 10

200

400

600

800

1000

Input Envelope2 (V2)

Out

put P

ower

(mW

)

0 0.2 0.4 0.6 0.8 10

16

32

48

64

80

PAE

(%)

0 0.2 0.4 0.6 0.8 10

20

40

60

80

Normalized Envelope (V)Ef

ficie

ncy

(%)

0 0.2 0.4 0.6 0.8 10

2

4

6

8

Prob

abili

ty (%

)

Class G PAE64QAM OFDM PDFTheory Avg PAEMeas. Avg PAE

64 QAM OFDM Symbol Period = 4 s

Theoretical avg. PAE = 24% Measured avg. PAE = 22%

Freq = 2 GHz

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ASU August 17, 2011

Class-G Dynamic Measurement

-80 -60 -40 -20 0 20 40 60 80-80

-60

-40

-20

0

Frequency Offset (MHz)N

orm

. Out

put P

ower

(dB

)

rms EVM = 2.5% Freq = 2 GHz

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ASU August 17, 2011

• DAC, supply modulator functions combined – No supply modulator: Higher efficiency and

smaller area• Multiple unit current-cell-based PAs as DAC

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PA based on digital modulation Unit current cells[Kavousian, et al., ISSCC 2007 ] [Presti, et al., JSSC 2009]

Digitally-Modulated PA

ASU August 17, 2011

• Accuracy / Efficiency Tradeoff• Accurate current cell requires high rout

– Cascode more headroom: Lower efficiency• Extra resolution required for predistortion• Efficiency:

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OUTOUT

OUT

DC

OUTIdeal P

VP

PP

Nonlinear VOUT

Input Code

V OU

T

Linear

Saturated

Current-Cell-Based PA

ASU August 17, 2011

Switched-Capacitor Basics

• Energy is lost w/ precharge and reset• No energy lost in charge redistribution w/o precharge

(b) Charge Redistribution w/o precharge

(a) Precharge and Reset

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ASU August 17, 2011

SCPA in Polar Transmitter

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ASU August 17, 2011

Basic SCPA Concept

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• SC technique can be used for voltage generation• Easy to split into capacitor bank (small area & loss)

– Resonant frequency maintained (Constant C)Constant envelope

Good efficiency

ASU August 17, 2011

Switched-Capacitor PA

• Capacitor can be arrayed– Single capacitor can be split into many– Each capacitor is switched to VDD or GND– Constant resonant frequency– RF Switched-Capacitor DAC

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Constant Capacitance

ASU August 17, 2011

Thevenin Equivalent Circuit

• Digitally-controlled output voltage• Constant top-plate capacitance vs. the

number of switched capacitors

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CU=C1=C2=Cn=CN= NC

Constant Capacitance = C

ASU August 17, 2011

Output Power

Pout delivered to ROUT

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• VOUT n/N

• POUT (n/N)2

• 4/ for 1st harmonic component

RV

Nn DD

22

2

2

POUT =DDV

Nn

4

21

VOUT =

ASU August 17, 2011

Power Dissipated in SC

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• Charging & discharging with switch→ CV2f dynamic power

• Assume fast tr,tf with constant current through L

• Effective switched capacitance varies with envelope code

ASU August 17, 2011

Ideal Efficiency

• Higher efficiency with higher QLoaded

• Higher QLoaded:- Smaller Capacitance- Less CV2f dynamic power- Efficiency tradeoff due to L & switch

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fCRRfLQ Loaded

2

12SCOUT

OUT

PPP

LoadedQnNnn

n)(4

42

2

ASU August 17, 2011

Ideal vs. Practical

Normalized POUT (dBm)

Practical Efficiency

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CLOCKDRSWCOUTSC

OUT

PPPPPP

OUTSC

OUTIdeal PP

P

• Practical implementation:− Lossy inductor: → − SW parasitic R: → − SW parasitic C: − Switch driver:− Clock distribution:

fVCNnP DDSWSWC2)/(

fVCP DDCLOCKCLOCK2

fVCNnP DDDRDR2)/(

Benefit from scaling

Idea

l (%

)

Prac

tical

(%

)

ASU August 17, 2011

CMOS Switch as Voltage Source

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0.250.50.751

n/N

CB

Volta

ge

(CB

)

AM-PM AM-AM

time 1/fs0

0

VDD

• Faster switch improves both AM-AM and AM-PM distortion performance (e.g., better with CMOS scaling)

ASU August 17, 2011

6-bit Switched-Capacitor Array

• Split into 4-bit unary and 2-bit binary arrays• Additional bits possible

– More unary/binary bits or C-2C ladder• Unit-cell switch and switch-driver

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ASU August 17, 2011

Switch Implementation

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• Cascode More output power with same Rout

• Total supply voltage of 2VDD

• All thin-gate devices

• Separate driver voltage ranges for NMOS & PMOS

ASU August 17, 2011

Switched-Capacitor PA Schematic

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C= 8.2pF

Bandpass Matching Network

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• 90 nm RF LP CMOS process (MIM cap and UTM)

Output Matching Network

Capacitor A

rray

Switch,Drivers,Logic & Bypass Capacitor

1430 m

730 m

Chip Microphotograph

ASU August 17, 2011

PA Measurement: Pout & PAE

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• 6-bit implementation • Fewer Pdriver at backoff• Peak = 45%

ASU August 17, 2011

AM-AM & AM-PM / Pout vs. Freq.

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• Different impedance seen from source depending on input code

• Scaling friendly

• Peak Pout ≥ 24dBm• Peak ≥ 45%

ASU August 17, 2011

Constellation / Spectral Mask

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• 64 QAM/OFDM• EVM = 2.9%

• Pout = 17.7 dBm

ASU August 17, 2011

Reference Degani, et. al.ISSCC 2008

Presti, et. al.JSSC 2009

Xu, et. al. ESSCIRC 2010

Walling, et. al.JSSC 2009 This work

Architecture Class-AB DPACurrent Cell Outphasing Class-G Switched-

CapacitorProcess 90nm 0.13um 32nm 0.13um 90nm

Power Supply 3.3V 1.2V/2.1V 2V 3.3V 1.5V/3VPeak Power 25 dBm 25 dBm 25.1 dBm 29.3 dBm 25 dBm

Peak Efficiency 50% 47% 40.6% 69% 45%

Avg. Power(OFDM) 15.5 dBm 15.3 dBm 18.6 dBm 19.6 dBm 17.7 dBm

Avg. Efficiency(OFDM) 19% 22% 18.1% 22.6% 27%

Output Matching NW N/A Ext.

MatchingOn-Chip

BalunOn-Chip Matching

On-Chip Matching

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Performance Comparison

• What’s next? Class-G SCPA in package – high PAE.

ASU August 17, 2011

Outline

Motivation for Compressed Sampling (CS) Compressed Sampling and three key ideas CS reconstruction Experimental Procedures and Results Conclusions

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ASU August 17, 2011

Body Area Network Many wireless sensors linked to personal Smartphone, etc. Personal mobile units linked to Dr. via internet/cellular network Dr. feedback for real-time control of detail vs. energy efficiency

Reduce data rates to increase sensor lifetime and energy efficiency40

Motivation for Compressed Sampling

ASU August 17, 2011

Compressed Sampling Sensor System

Ultra-low power CS analog front-end (AFE) RF power amplifier is energy hog; ADC is energy piglet CS reduces data rates with commensurate energy

savings for PA, ADC, etc; i.e., only [Y] is digitized and transmitted

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LNA ADCPower

Amplifier

Antenna

CS AFEElectrode

Compressed Sampling Bio-Signal Acquisition System

Sensor

x(t) [Y]

Compressed Data RateFeedback


Intuition for CS – Conventional


Intuition for CS – Group Sampling

• R. Dorfman, “The detection of defective members of large populations,” The Annals of Mathematical Statistics, vol. 14, no. 4, pp. 436-440, Dec. 1943.

• M. Sobel and P.A. Groll, “Group testing to eliminate efficiently all defectives in a binomial sample,” Bell System Technical Journal, vol. 38, no. 5, pp. 1179-1252, Sept. 1959.

ASU August 17, 2011

Intuition – II: Sub-Nyquist Sampling

Intuitive explanation of three key ideas Nyquist sample a sinusoid; i.e., 2 samples/period Only 2 amplitude values (i.e., looks like sawtooth

waveform) How to get enough amplitude values to infer sinusoid?

WW

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ASU August 17, 2011

WW

r1 r2

Key Idea #1: Randomize Sampling Multiply original analog samples by random weights to obtain

many more analog amplitudes45


ASU August 17, 2011

W

r1 r2

r3

r4

r5

r6

r7 r8

W

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Key Idea #2: Reconstruction (e.g., 8! possible solutions) Key Idea #3: Optimization assuming known class of signal; e.g.,

sinusoid). 8! Solutions—CS finds best with high probability. What about compression?


ASU August 17, 2011

Formal Compressed Sampling

[X]NX1

[Y]MX1

[X]: Analog input sample vector (e.g., N = 16) []: Measurement matrix of (e.g., 6-bit Gaussian or

Uniform) random coefficients (M rows and N columns) [Y]: Compressed analog output vector (e.g., M = 8) Compression Factor C = N/M (e.g., C = 2)

[]MXN

[Y] = [Φ][X]

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ASU August 17, 2011

Compressed Sampling - I

[X]NX1 = [X1, …, XN]

[Y]MX1 = [Y1, …, YM]

[X]16X1; []8X16; [Y]8X1; C = 2 []8X16 is Measurement Matrix;

e.g., Gaussian or Uniform random coefficients each quantized to n = 6 bits

Multiply and sum for each Yi is a Random Linear Projection [Y] is a compressed analog signal with global information Typically K < M < N (i.e., signal is sparse such as ECG)

[]MXN = [11, …, N ][[[

]]]M1, …, N

…

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1 11

Niii

Y X

K = 3

[Y] = [Φ][X]

ASU August 17, 2011

Compressed Sampling - II

[X]1024X1: Analog samples from ECG signal [Y]256X1: Compressed analog output signal []256X1024: Measurement Matrix C = 4X in this example; (C = 2X – 16X possible

for ECG)

[X]

[Y]

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ASU August 17, 2011

CS Reconstruction

Reconstruction/optimization of compressed signal (e.g., Smartphone) [Φ] is non-square and non-invertible; under-determined system with

many solutions Optimize exploiting knowledge of signal; e.g., ECG bio-signals are

time-domain sparse50

LNA DAC

Antenna

Baseband DSPCS Optimization/ Reconstruction

Compressed Sensing Bio-Signal Reconstruction System

y(t)

Original Nyquist Data Rate

ASU August 17, 2011

Accuracy Requirments for ECG

AAMI—American Institute for Advancement of Medical Instrumentation (Standards Vary)

Ambulatory Quality ECG—8-10 bits (48-60 dB) Diagnostic Quality ECG—10-12 bits (60-72 dB)

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Accuracy depends on: Compression Factor, C = N/M PDF of random coefficients and # bits Algorithm—Convex Optimization with L1 Norm

CS Reconstruction - II

[X]

[Y]

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Sparsity vs. Compressibility

Theoretical Limit: M > K log(N/K) with K nonzero input samples (Heuristic: M > 2K)

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50 60 70 80 90 100

Sparsity (%)

2

6

10

14

18

22 Compression Factor, C = N/M

ASU August 17, 2011

Quantization of Random Coefficients - I

Gaussian []: Choose n = 6 bits for C = 2X – 16X 54

ASU August 17, 2011

Switched-Capacitor CS CODER

For ECG signal: BW = 2 KHz fS = 4 KHz C = 100 fF PDYN ≈ 0.4 nW

C-2C in MDAC/ADC

[Y] = [Φ][X]

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LNA ADC PowerAmplifier

Antenna

CS AFEElectrode

Compressed Sensing Bio-Signal Acquisition System

Sensor

Ultra-low Power Analog Circuits

SC Multiplying Digital-Analog

Converter

ASU August 17, 2011

CS-ADC Chip-photo

IBM8RF 0.13 µm CMOS3 mm x 3 mm

M = 64N=128 to 1024

Testing Underway: Expect ~ 1 uW total power with C = 16

ASU August 17, 2011

Thank you very much!

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cmos switched-capacitor circuits: recent advances in bio

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