NguyenTrong Nhan1
ChaHyouk-Kyu1*
-
(Department of Electrical and Information Engineering, Seoul National University of
Science and Technology / Seoul, Korea
{18512108, hkcha}@seoultech.ac.kr
)
Copyright © The Institute of Electronics and Information Engineers(IEIE)
Keywords
SAR ADC, Neural recording system, Asynchronous logic, Biomedical device, Low-power
1. Introduction
In recent years, closed-loop neural system-on-chips (SoCs) with neural recording and
stimulation functions have been widely researched for implantable biomedical devices
[1]. These systems can improve patients’ quality of life and are capable of diagnosing
and treating various neurological conditions, such as Alzheimer’s disease, epilepsy,
and Parkinson’s disease. The neural recording path in neural SoCs is a data acquisition
and processing system that observes and understands the electrical activity of the
neural networks in the brain.
Fig. 1 shows a block diagram of a typical closed-loop neurostimulation system for seizure
treatment [2]. The analog-to-digital converter (ADC) in the neural recording path is an important
block that acts as an interface between the analog front-end (AFE) and the digital
signal-processing control unit. In such systems, low power consumption is very critical
as power resources may be limited in an implant environment, and high power consumption
may lead to excessive heating in the surroundings, causing tissue damage.
Neural signals include action potentials (APs or spikes) and local field potentials
(LFPs), which generally have a bandwidth ranging from 1 Hz to a few kHz. The amplitude
ranges from a few hundred ${\mu}$V to several mV. Therefore, the sampling rate of
the ADC does not need to be very high to achieve suitable performance. The successive
approximation register (SAR) ADC architecture is the best candidate in this context
due to its low power and simple architecture, so it was chosen for this work. A 10-bit
SAR ADC with a sampling rate of 250 kS/s was chosen after carefully considering the
tradeoff between the power consumption and ADC performance.
The rest of the paper is organized as follows. Section 2 presents the architecture
of the proposed SAR ADC. Section 3 discusses the design details of the key function
blocks in the ADC. Section 4 presents the key simulation results, followed by the
conclusions in Section 5.
Fig. 1. Block diagram of a closed-loop neural system-on-chip.
2. Proposed SAR ADC Architecture
Fig. 2 shows the architecture and timing diagram of the proposed 10-bit SAR ADC for
a neural recording system. To achieve good common-mode noise rejection, a fully differential
structure is used. A bootstrapped sampling circuit is used to improve the linearity
when the input signal ranges from 0 to 1 V. In addition, a modified V$_{\mathrm{CM}}$-based
switching scheme is used for a binary weighted capacitive digital-to-analog converter
(DAC) to reduce the switching energy.
The differential input signal is sampled on the top plates of the capacitor array,
so the MSB is determined directly without any switching activity. A dynamic comparator
compares the voltage on the top plate of the capacitor array. Asynchronous SAR control
logic stores the comparison results as digital output code and generates control signals
for the capacitor switching array. All 10 bits are determined successively until the
end of conversion (EOC). When the conversion is done, a time interval is allocated
for the comparator offset calibration process before a new conversion occurs.
Fig. 2. Architecture of the proposed 10-bit SAR ADC and timing diagram.
3. Key Functional Blocks
3.1 Bootstrapped Switch
In general, the performance of a sample and hold circuit directly and greatly impacts
the whole ADC. As the voltage scales down, the sampling circuit becomes a critical
part in the SAR ADC because of unwanted effects such as charge injection and clock
feedthrough. The bootstrap technique mitigates the problem of signal-dependent on-resistance
(R$_{\mathrm{on}}$) of the sampling switch. The on-resistance needs to be kept constant
during the sampling phase. When the sampling transistor operates in the deep-triode
region, the value of the on-resistance can be expressed as:
Fig. 3 shows the circuit schematic of the bootstrapped switch [3] used in the design. When the sampling clock SCLK is low, both M$_{2}$ and M$_{3}$
turn on and pre-charge the capacitor C$_{\mathrm{B}}$ to VDD. During the tracking
phase, SCLK goes high, and C$_{\mathrm{B}}$ acts as a battery between the gate and
source of M$_{\mathrm{s}}$, so the voltage V$_{\mathrm{GS}}$ is approximately 1 V.
A minimal length is chosen for M$_{\mathrm{s}}$ to reduce the on-resistance, while
a moderate width is chosen to avoid large parasitic and charge injection.
Fig. 3. The circuit schematic of the bootstrapped switch.
3.2 Capacitive DAC
The proposed 10-bit capacitive DAC is illustrated in Fig. 4. Each capacitor is split into two equal fractions (C$_{1}$ to C-$_{9}$), so the common
mode voltage V$_{\mathrm{CM}}$ is generated internally. Only one of the split capacitors
in each bit cycle needs to switch, which makes the DAC settling faster.
In this structure, the modified version of a V$_{\mathrm{CM}}$-based switching scheme
is used for high power efficiency [4]. In the original V$_{\mathrm{CM}}$-based scheme [5], the total number of capacitors is reduced by half in comparison to a conventional
switching scheme, which is 512C for a single-ended side. However, this number is still
too big and results in a large area on a chip and high power consumption. The number
of capacitors in the modified version is reduced much more to only a quarter (256C)
of the capacitors necessary in a conventional switching scheme.
In the modified version of the V$_{\mathrm{CM}}$-based switching scheme, the conversion
procedure is the same as in the original scheme except for the last significant bit.
Fig. 5 shows the switching sequence of this scheme for a 3-bit ADC. In the sampling phase,
the input signals V$_{\mathrm{ip}}$ and V$_{\mathrm{in}}$ are stored on the top plate
of the capacitor array. V$_{\mathrm{CM}}$ is generated by connecting each divided
capacitor part to V$_{\mathrm{ref}}$ and ground. In the conversion phase, the switching
process is the same as in the original scheme for the first 9 bits. To determine the
LSB, the LSB capacitor of the P-side array just needs to be changed, whereas the N-side
array remains unchanged. The waveform of the implemented switching scheme is illustrated
in Fig. 6.
When using this scheme, the total switching energy is approximately 85.083CV$_{\mathrm{ref}}$$^{2}$
for 10-bit resolution. This is only 6.24\% of the energy consumption of the conventional
scheme and half of energy of the V$_{\mathrm{CM}}$-based scheme. Fig. 7 compares the energy consumption of the three switching schemes.
Fig. 4. The proposed 10-bit capacitive DAC with a modified VCM-based switching scheme.
Fig. 5. Example of 3-bit modified VCM-based switching scheme.
Fig. 6. Waveform of the modified VCM-based switching scheme.
Fig. 7. Switching energy versus output code.
3.3 SAR Control Logic
In this SAR ADC, asynchronous control logic is used to avoid using a high-speed clock
generator. As illustrated in Fig. 8, the CLKC generator consists of a comparator, 3-input NAND gate, and delay cell.
The comparator acts as an inverter with respect to its input clock CLKC, and the NAND
gate is an inverter controlled by the EOC signal. Conceptually, this structure makes
up a three-stage ring oscillator [6]. After the falling edge of the sampling clock, oscillation starts, and 10 successive
CLKC signals are generated. Each bit cycle is triggered at the rising edge of CLKC.
Incomplete settling error may heavily degrade the SAR ADC performance, so a variable
delay is designed for the first three largest weighted capacitors to allocate longer
time for the DAC to fully settle.
As shown in Fig. 9, a SAR shift register implemented by dynamic logic [7] is used to reduce the power consumption. It consists of 10 bit-slice unit, for which
the data is clocked by the READY_B signal. In the conversion phase, whenever a comparison
is ready, the bit-slice generates a CYCLE signal to control the DAC switch. Simultaneously,
the comparator outputs OUTP and OUTN are loaded, latched, and generate the digital
output DOUT[9:0]. Fig. 9(c) shows the DAC control logic for both capacitor arrays.
Fig. 8. Asynchronous clock generator.
Fig. 9. SAR control logic (a) Shift register, (b) Circuit schematic of a bit-slice, (c) DAC control logic.
3.4 Comparator
Fig. 10 shows a diagram of the two-stage dynamic comparator [8]. During the reset phase (CLK=0), transistors M$_{5}$ and M$_{\mathrm{6}}$ pre-charge
nodes Fp and Fn to VDD and cause M$_{12}$ and M$_{14}$ to discharge output nodes Vop
and Von to ground. In the regeneration phase (CLK=1), M$_{5}$ and M$_{6}$ turn off,
which causes nodes Fp and Fn to discharge from VDD with different rates and yields
a voltage difference. The two cross-coupled inverters begin to regenerate when the
voltage at nodes Fp and Fn are not high enough for M$_{12}$ and M$_{14}$ to keep discharging
outputs to ground. The cascode transistors M$_{3}$ and M$_{4}$ are added to help mitigate
the kickback noise that occurs while nodes Fp and Fn discharge.
For every bit comparison to be correct, calibration of the comparator’s offset is
inevitable for a SAR ADC. One common way to cancel out the offset in the dynamic comparator
is to add one more differential pair parallel to the main input pair. The offset can
be eliminated by applying an appropriate DC value to this pair. There are various
ways to generate this DC voltage. For low power design, a capacitive DAC that does
not consume static power is exploited for offset calibration.
The offset calibration scheme uses a binary weight capacitor array. Fig. 11 shows a diagram of the offset calibration part. As a compromise between area and
accuracy, a 5-bit DAC is used for this approach (CAL-DAC). Two bit-slices are added
to start the calibration. After all 10 bits are determined, CAL_EN goes high, and
the calibration process is begun by shorting the two inputs of the comparator (DACp
and DACn) to V$_{\mathrm{CM}}$ to determine the polarity of the offset voltage. If
the offset is positive, the capacitor array is connected to CAL-N to compensate for
the N-side while CAL-P is shorted to GND, and if the offset is negative, the array
is connected to CAL-P.
The circuit was implemented using a 2-to-1 multiplexer. To control the calibration
process, simple digital logic was implemented. After the CAL_START signal goes high,
a 5-bit counter starts running to generate digital calibration bits CAL[4:0]. The
asynchronous clock generator is also used for the calibration. The value of V_CAL
on the top plate of the DAC gradually increases until the output of the comparator
flips, which means that the offset is calibrated.
At this time, EOC goes high and stops the counter. Immediately, the calibration bit
CAL[4:0] is then stored in a register to prepare for the next conversion. In the sampling
phase, the top plate of CAL-DAC is shorted to ground for resetting. During normal
conversion, the calibration digital code that was previously stored in the register
is loaded and applied to CAL-DAC.
Fig. 10. Circuit schematic of two-stage dynamic com-parator.
Fig. 11. Comparator offset calibration (a) Binary-weight capacitor array, (b) Calibration logic, (c) Calibration timing.
4. Simulation Results
The 10-bit SAR ADC was implemented using 180-nm CMOS technology and occupies an active
area of 385 x 385 ${\mathrm{\mu}}$m$^{2}$. Fig. 12 shows the layout capture of the designed SAR ADC. The comparator and two bootstrapped
switches are placed on the left, while the SAR logic and calibration logic are located
on the right and below the capacitive DACs.
Metal-insulator-metal (MIM) capacitors were used for the DAC. Each unit capacitor
value is 21.2 fF with an area of 4x4 um$^{2}$. This value is chosen to satisfy the
matching consideration and the kT/C noise requirement. DC analysis was performed using
a slow ramp signal with a resolution of 100 samples/code, as shown in Fig. 13. The SAR ADC achieves a peak differential non-linearity (DNL) and integral non-linearity
(INL) of +0.38/-0.37 LSB and +0.41/-0.35 LSB, respectively.
The dynamic performance of the SAR ADC is shown in Fig. 14. The 1024-point fast Fourier transform (FFT) spectrum at 1.22 kHz sinusoid signal
indicates a signal-to-noise-and-distortion ratio (SNDR) of 60.29, which results in
an effective number of bits (ENOB) of 9.72. The spurious-free dynamic range (SFDR)
result is of 72.93 dB.
The power breakdown chart is shown in Fig. 15. The analog parts, digital circuits, and capacitive DACs account for the total power
consumptions, which is 4.5 ${\mathrm{\mu}}$W with a 1-V supply. The figure-of-merit
(FoM) of the ADC is obtained using the following equation:
The FoM of the proposed SAR ADC is 19.92 fJ/conversion-step. Table 1 presents a summary of the performance in comparison with that of other 10-bit SAR
ADCs. The proposed ADC shows good FoM performance with a small area.
Fig. 12. Layout of the SAR ADC (without pad).
Fig. 13. Static performance of the SAR ADC.
Fig. 14. Dynamic performance at 250 kS/s with 1.22-kHz sine wave input (1024-point FFT).
Fig. 15. Power breakdown of each block.
Table 1. Performance summary and comparison.
Parameters
|
[5]
|
[6]
|
This work
|
Process (nm)
|
90
|
180
|
180
|
Resolution (bits)
|
10
|
10
|
10
|
Power supply (V)
|
1.2
|
1.8
|
1
|
Sampling rate (kS/s)
|
100000
|
32000
|
250
|
SNDR/SFDR (dB)
|
56.6/71
|
59.6/71.1
|
60.29/72.93
|
ENOB (bits)
|
9.1
|
9.6
|
9.72
|
DNL (LSB)
|
+0.79/-0.27
|
-
|
+0.38/-0.37
|
INL (LSB)
|
+0.86/-0.78
|
-
|
+0.41/-0.35
|
Power (µW)
|
3000
|
1380
|
4.2
|
FoM (fJ/conv-step)
|
55
|
61
|
19.92
|
Layout area (µm${^2}$)
|
670x270
|
-
|
385 x 385
|
5. Conclusion
In this paper, a low-power 10-bit SAR ADC was proposed for neural recording applications.
A modified V$_{\mathrm{CM}}$-based switching scheme and asynchronous SAR control logic
were applied to help reduce the power consumption. The ADC was implemented using 180-nm
CMOS technology and consumes 4.2 ${\mathrm{\mu}}$W with a 1-V power supply. The dynamic
performance showed an SNDR of 60.29 dB and SFDR of 72.93 when operating at 250 kS/s,
as well as an ENOB of 9.72 bits and FoM of 19.92 fJ/conv-step.
ACKNOWLEDGMENTS
This research was funded by the Basic Science Research Program through the National
Research Foundation of Korea (NRF), which is funded by the Ministry of Science and
ICT (MSIT; NRF-2018R1C1B6003088), as well as the Institute of Information & Communications
Technology Promotion (IITP) grant, which is also funded by the MSIT (No. 2017-0-00659).
The chip fabrication and EDA tool were supported by the IC Design Education Center
(IDEC).
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Author
Trong Nhan Nguyen received his B.S. degree in electronics and communi-cations engineering
from HCMC University of Technology, Vietnam, in 2018. He received his M.S. degree
in electrical and information engineering at Seoul National University of Science
and Technology, Seoul, in 2020. His research interests include the design of low-power
data converters for biomedical applications.
Hyouk-Kyu Cha received B.S. and Ph.D. degrees in electrical engineering at Korea Advanced
Institute of Science and Technology (KAIST), Daejeon, Korea, in 2003 and 2009, respectively.
From 2009 to 2012, he was a Scientist with the Institute of Microelectronics (IME),
Agency for Science, Tech-nology, and Research (A*STAR), Singapore, where he was involved
in research and development for analog/RF ICs for biomedical applications. Since 2012,
he has been with the Department of Electrical and Information Engineering, Seoul National
University of Science and Technology, Seoul, Korea, where he is now an Associate Professor.
His research interests include low-power CMOS analog/RF IC and system design for implantable
and wearable biomedical devices.