|Passive wireless microsystems typically harvest their operational
power from radio-frequency waves emitted by their base station. The
absence of bulky batteries not only minimizes the physical dimension
and cost of these microsystems, it also removes the need for maintenance.
As a result, these Microsystems can be embedded in products or
implanted in living bodies permanently to provide identification, to
carry out micron-scale measurement and to execute a micron-scale
control action that otherwise not possible. Attributive to their small size,
wireless accessibility, programmability, low-cost, and maintenance-free
operation, passive wireless microsystems have found a broad range
of emerging applications include implantable bio-Micro-ElectroMechanical-
Systems (MEMS pressure sensors [1,2], retinal prosthetic
devices [3-6], swallowable capsule endoscopy [7-9], multi-site pressure
sensors for wireless arterial flow characterization , embedded
micro-strain sensors for product performance and safety monitoring,
wireless temperature sensors for human body and environmental
monitoring [11-14]. Radio-Frequency Identification (RFID) tags for
object tracking in logistics automation [15,16] and replacing bar codes
in retailing, e-tickets, e-passports, and low-cost high-security product
authentication keys to replace existing product authentication means
such as holograms, water-marks, invisible barcodes, security threads,
chemical, and DNA markers that are often too costly to be used for
general goods  to name a few. The performance of passive wireless
microsystems is subject to the effect of the imperfections common to
all integrated circuits such as process spread, supply voltage fluctuation,
and Process-Voltage-Temperature (PVT) variation. The permanent
placement of these microsystems in products or living bodies, the finite
operational power, and the possible exposure to the harsh environment
in which passive wireless microsystems reside impose stringent
constraints on both the design and calibration of these microsystems
to ensure a reliable operation, proper functionality, and an adequate
accuracy. The physical inaccessibility of these microsystems when
embedded in products or implanted in living bodies mandates that
their calibration be conducted wirelessly from their base station prior
to their intended operation. This paper briefly examines the need
for, challenges encountered in, and possible solutions for the remote
calibration of passive wireless microsystems.
|Calibration of Power Harvesting
|The amount of the operational power that a passive wireless
microsystem often possesses sets the maximum distance over which
a reliable communication between the passive wireless microsystem
and its base station can be established. It also limits the complexity
subsequently the functionality of the microsystem. The efficiency that a
microsystem converts the energy of an incoming radio-frequency wave
to electrical power limits the amount of the power that the microsystem
can harvest from the radio-frequency wave for a given time interval,
and is determined by the efficiency of the antenna, the accuracy of the
impedance matching network between the antenna and the voltage
multiplier, the voltage gain of the impedance matching network, and
the efficiency of the voltage multiplier where ac-to-dc rectification takes place. The physical dimension of the antenna sets the maximum
voltage that the antenna can generate. The power efficiency of a voltage
multiplier is dominated by the loss of rectifying devices [18-20]. It can be
improved by either employing Schottky diodes, native MOSFET (Metal
Oxide Semiconductor Field Effect Transistors) diodes, or by boosting
the voltage at the input of the multiplier using passive resonators . A
passive resonator, typically an LC network that resonates at the carrier
frequency, is usually inserted between the antenna and the voltage
multiplier to perform both impedance matching for maximizing
power transfer from the antenna and voltage boosting for maximizing
the power efficiency of the downstream voltage multiplier [22-24].
The power efficiency of voltage multipliers can be further improved
by employing a step-up transformer between the antenna and the
voltage multiplier with its secondary winding resonating at the carrier
frequency . The quality factor of the resonator should be maximized
in order to maximize its output voltage subsequently the efficiency of
the downstream voltage multiplier. Arising from process spread and
the effect of the change of the environment in which the microsystem
resides, the resonant frequency of the resonator exhibits a large degree
of uncertainty. As a result, a small deviation of the resonating frequency
of the resonating network from the carrier frequency will result in a
large drop of the output voltage of the resonator. This is echoed with
a large reduction of the power efficiency of the downstream voltage
multipliers. It is highly desirable to have an automatic on-board tuning
mechanism that adjusts the resonating frequency of the resonator such
that the resonator will resonate at the desired carrier frequency.
|Calibration of System Clocks
|The operation of both the baseband units of a passive wireless
microsystem and the backscattering up-link from the microsystem to
its base station are controlled by its system clock. To ensure a reliable
communications between the microsystem and its base station, a
stringent constraint on the frequency of the system clock exists.
The system clock of a passive wireless microsystem can be directly
generated from the carrier [21,26]. The need for frequency dividers to
lower the clock frequency to the baseband frequency, typically in kHz
or low MHz ranges, increases the power consumption. The modulation
index must also be small to ensure a continuous flow of RF power to the
microsystem. Baseband clock can also be obtained from the envelope of
the carrier extracted from the received RF wave to take the advantage
of its low power consumption and the fact that most passive wireless microsystems operate at a rather low frequency [26-28]. A common
constraint of clock generation from either the carrier or the envelope
is that the clock is available only when the down link is active, severely
limiting the operation of the microsystem. It is generally preferred
from a low-power and robustness point of view to generate the system
clock of the microsystem locally using an on-chip oscillator, often a
ring oscillator or a relaxation oscillator, to take advantage of their low
power consumption and a large frequency tuning range. Arising from
the effect of process spread, supply voltage fluctuation, and temperature
variation, the frequency of the local oscillator usually exhibits a high
degree of uncertainty. The timing reference required for calibrating
the frequency of the local oscillator comes from the base station. The
clock of the passive wireless microsystem in [11,12] is generated using
an local on-chip LC oscillator that is injection-locked to the carrier of
the RF wave from the base station to take the advantage of the high
frequency accuracy of injection-locking. This also allows the use
of a radio-frequency signal with a small modulation index thereby
maximizing the amount of power flowing from the base station to the
passive wireless microsystem. The downside of injection-lock based
frequency calibration is a small lock range. Injection-locked activeinductor
LC oscillators with devices operating in the sub-threshold
mode exhibit a large frequency tuning range with an ultra low level
of power consumption, offering an alternative . As compared
with injection-locking, phase-locked loops provide a larger frequency
lock range and superior frequency accuracy, however, at the cost of
high power consumption . In  a remote frequency calibration
technique using envelope based injection-locking was proposed
with significantly reduced power consumption. Integrating feedback
that integrates the difference between the reference frequency and
the frequency of the local oscillator not only ensures high frequency
accuracy but also retains the control voltage for a sufficiently long
time after the injection signal is removed. The frequency of the local
oscillator can also be calibrated using digital trimming [19,31-34].
A key advantage of frequency calibration using digital trimming
is its large frequency tuning range, only upper-bounded only by the
frequency tuning range of the oscillator. The need for a successive
approximation registers, a digital-to-analog converter, and other logic
for pulse counting, comparison, and control makes it difficult to lower
the power consumption.
|Calibration of analog-to-digital converters
|Analog-to-Digital Converters (ADCs) are an essential block of
passive wireless microsystems. Various ADCs are available, the lowpower
constraint of passive wireless microsystems, however, only
warrants a few architectures of ADCs viable for these microsystems.
Charge redistribution successive approximation ADCs, time-to-digital
ADCs, and incremental sigma-delta ADC offer the intrinsic advantage
of low-power consumption. They are strong candidates for passive
|Charge redistribution successive approximation ADCs have found
increasing applications in passive wireless microsystems due to their low
power consumption and a high accuracy [35-36]. Multi-stage binary
weighted capacitor arrays are often used in construction of DACs to
minimize both silicon and dynamic power consumption [37-38]. This,
however, is at the expense of deteriorating performance mainly caused
by the inaccuracy of the bridge capacitors connecting two adjacent
capacitor arrays and the bottom-plate parasitic capacitance of the
bridge capacitors [39-43]. The offset of the comparator also affects the
accuracy of the ADCs. The SNDR (Signal-to-Noise Dynamic Range)
and SFDR (Spure-Free Dynamic-Range) of a non-calibrated charge redistribution successive approximation ADC could be 10 dB and 20 dB
lower respectively as compared with those of its calibrated counterpart
. The effect of the inaccuracy of the bridge capacitors and that of its
bottom-plate parasitic capacitance of these capacitors can be mitigated
by adjusting the capacitance on both sides of the bridge capacitors .
The effect of the offset of the comparator can also be compensated
by using the dynamic offset control technique  to avoid the
power penalty of current array-based offset compensation  and
the speed penalty of capacitor array-based offset compensation .
Compensation can be made programmable from the base station with
the challenge that the compensating circuitry must remain in action
for the time duration in which microsystems completes analog-todigital
conversion even if the calibrating signals from the base station
|Oscillator-based time-do-digital ADCs employ a timing oscillator
whose frequency is constant and a sensing oscillator whose frequency
is a linear function of the input. For temperature measurement, the
sensing oscillator is a PTAT (Proportional-To-Absolute-Temperature)
oscillator whose frequency is proportional to temperature [49-51].
The accuracy of oscillator-based time-to-digital ADCs depends upon
the frequency accuracy of the timing oscillator and the linearity of the
sensing oscillator. The dynamic range of the ADC depends upon the
ratio of the frequency of the sensing oscillator to that of the timing
oscillator. It is also determined by the frequency tuning range of the
sensing oscillator. Both can be adjusted remotely from the base station.
The PTAT core can also be tuned remotely from the base station by
varying the biasing current or other parameters. As compared with
oscillator-based time-to-digital ADCs, delay-line based time-to-digital
ADCs offer a key advantage of low power consumption, attribute to the
absence of the power-consuming oscillator. The pulse width of the pulse
generator is directly proportional to temperature, and is measured by
a cyclic time-to-digital converter. The accuracy of the ADC depends
upon the linearity of the PTAT line, the characteristics of the timing
line, the temperature-dependent pulse width, and the minimum delay
of the cyclic time-to-digital converter. The larger the pulse width and
the smaller the delay of the cyclic converter, the better the resolution. To
calibrate the ADC, the accuracy of the delay of the timing line needs to
be calibrated first. This can be achieved by using a DLL with its reference
from the base station. The delay of the cyclic time-to-digital converter
can also be tuned from the base station so as to adjust the resolution
of the ADC. It should be noted that although integrating ADCs such
as single-slope and dual-slope ADCs offer an excellent resolution, the
need for a ramp generator and a comparator makes the reduction of the
power consumption of these ADCs a rather difficult task.
|Incremental sigma-delta ADCs provide a high absolute accuracy
in sample-by-sample conversion . They provide precision
conversion with high linearity obtained from the resetting of the
integrator and a low offset due to the S/H of the input that allows a
convenient deployment of offset compensation. In addition, the order
of digital filtering for incremental ADCs is the same as the order of the
incremental ADCs and is much lower as compared with that for sigmadelta
ADCs, greatly reducing power consumption. The main drawback
of first-order incremental sigma-delta ADCs is their low conversion
speed. High-order incremental ADCs lower the conversion time
without sacrificing resolution [53-56]. Similar to conventional sigmadelta
ADCs, incremental ADCs are subject to the effect of the offset
of the integrator caused by both mismatches and the charge injection
of MOSFET switches . The effect of the offset can be eliminated
remotely from the base station using the approaches depicted earlier.
|The need for the remote calibration of passive wireless microsystems,
the challenges encountered, and potential solutions have been explored
in this editorial. Remote calibrations of power harvesting, system clock
generation and analog-to-digital conversion have been addressed.
Research in this fast-evolving field is only in its infancy. An intensive
research is needed in search for ultra-low power techniques and their
silicon implementation for remote calibration of passive wireless
microsystems from the base station.
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