It is interesting to think about how many sensors surround an average person in their day-to-day lives. Even the most commonly used smartphones store at least five different sensors in it. Those sensors enable a smartphone to sense its surroundings for real-time location and changes in motion. High-end smartphones go even further and have an additional 20 or more types of sensors to detect data such as distance and biometric signs. Smartwatches—another commonly used device—have about 10 different types of sensors. A ballpark estimation thus shows that an average person who carries these smart devices interacts with about 30 sensors a day. Considering that there are several billions of smart devices that are used around the world, there are trillions of sensors that are functioning worldwide on any given day.
In this latest article from our series with the DGIST faculty, Professor Junghyup Lee of the Department of Electrical Engineering and Computer Science will introduce sensor systems that are ubiquitous around us. The article discusses how sensor systems detect data from its environment and converts them into digital signals that computers can store and process. There will also be an emphasis on sensor interface circuits which can be implemented using semiconductor technologies.
The Two Pillars of a Sensor System: Sensor Devices and Sensor Interfaces
Figure 1. The various inputs and outputs of a sensor interface circuit
The sensors that are widely used today are generally referred to as sensor systems that consist of a sensor device and sensor interface. This system detects physical, chemical, and biological data from the environment such as temperature, humidity, motion, pressure, physical contact, and gas to convert into electrical signals.
Various types of sensor devices have been developed with consideration of different principles, structures, and materials that have different targets to be sensed. Temperature sensors, for example, are further classified into different types such as resistance temperature detectors (RTD) and thermocouples based on the measuring methods used, and there are far more types of temperature sensor devices when considering additional factors such as component materials and structures. But even if these sensor devices are divided into many different types, their outputs are ultimately determined by one of four electrical components of voltage, current, resistance, or capacitance. In summary, a sensor device converts a variety of data from the physical world into an analog signal that is in the form of one of these four electrical components.
Afterwards, a sensor interface circuit converts the electrical analog signals from the sensor devices into digital signals for hardware like CPUs, GPUs, monitors, and transceivers to use for signal processing, analysis, and transmission. There are four different types of sensor interface circuits depending on the output of the sensor device: analog-to-digital converters (ADC), current-to-digital converters (CDC), resistance-to-digital converters (RDC), and capacitance-to-digital converters (CDC). As for ADCs, they make digital signals from voltage analog signal.
Even though sensor interface circuits do not require large bandwidths to read signals deriving from physical, chemical, and biological data due to these signals primarily existing in frequencies of tens of kHz or less, it becomes necessary to accurately read very small but meaningful signals amidst the presence of large, external noise. As an example, brainwave signals measure only a few microvolts (μV). However, on the other hand, a 220V power cable nearby can cause a noise signal measuring 60 Hz which equates to several hundred millivolts (mV). In order to accurately detect such small signals like brainwaves in the presence of large distractions like a power cable, sensor interface circuits are very much required to have a wide input range, good linearity, low noise capabilities, and high resolution. Consequently, it is important for sensor systems to also possess the characteristic of low power consumption. In addition to a large number of sensors being found in mobile devices like the latest smartphones, sensor systems need to be readily applied to low-power systems such as Internet of Things (IoT) or Internet of Everything (IoE) products.
Semiconductor-Based Sensor Interfaces: Combining an AFE and ADC
Figure 2. The various inputs and characteristics of a sensor interface
As a system that can be implemented with semiconductors, sensor interfaces typically combine an analog front-end (AFE) circuit and an ADC circuit. The role of the AFE is to convert the sensor’s output signals into voltage signals without loss or distortion and input them to the ADC. The ADC then accurately converts these analog voltage signals into the final digital values. And for sensor interfaces to possess its desired characteristics, it is critical for the implementation of a semiconductor circuit to balance the distribution of performance between the AFE and the ADC to achieve the optimal performance with a high figure-of-merit1.
1Figure-of-merit: a numerical quantity based on one or more characteristics of a system or device that represents a measure of efficiency or effectiveness
AFE: Converting Voltage, Current, Resistance, and Capacitance to Analog Signals
Looking at a sensor interface system and the four types of AFE circuits that are differentiated according to their inputs, they all share the common feature of being feedback circuits2 centered around an operational amplifier (Op-amp). As each of these circuits and their operations will be given a closer look, it will be important to understand that the input current, input voltage, input resistance, and input capacitor are the four types of output for a sensor device.
2Feedback circuit: a circuit that feeds back some of the output to the input of a system
Figure 3. The four types of analog front-end (AFE) circuits
Firstly, the current-input front-end—also called a transimpedance amplifier—is a circuit that uses an op-amp and a feedback resistor (Rfeed) to convert the input current into a proportional output voltage. While the op-amp is an integrated circuit that can amplify weak electric signals, a Rfeed controls the amount of output. As the gain, or the magnitude of an amplifier’s output and input, is determined by the size of the Rfeed, the resistor requires stability.
The voltage-input front-end can be implemented by adding a gain resistor (Rgain) to the current-input front-end, and it amplifies to the desired gain and produces an output voltage. Consequently, balancing the proportion of Rfeed and Rgain leads to the desired gain and allows for easy adjustments within the semiconductor while leading to minimal changes coming from the process or fluctuations in temperature. However, a voltage drop, or the amount of voltage loss that occurs through all or part of a circuit due to impedance, occurs when the input current flows entirely through the Rfeed.
Next, the resistance-input front-end has a very similar structure to the voltage-input front-end. But there are also differences such as the input voltage being replaced with the reference voltage while the gain resistor is replaced with the input resistor for the parts to be operational. In the case of these front-ends, a stable reference voltage and Rfeed are required to secure an accurate resistance-to-voltage gain. And to compensate for the inverse relationship between the output voltage and the input resistor, an inverse transformation is later performed on the digital output of the ADC to obtain an input resistor value.
Finally, a capacitance-to-voltage conversion is obtained through more intricate operations that are absent from the previously mentioned structures. The circuit uses a feedback capacitor instead of an Rfeed while a switch is added to the input capacitor. The operation here follows a specific procedure. First, the reference power source and the input capacitor are connected through the switch to create an electrical charge. Then, this connection is discontinued while another switch is connected to the op-amp front-end to transfer the electrical charges to the feedback capacitor. As a result of this process, the output voltage is converted proportionally to the size of the input capacitor.
So, what impact does the AFE have on the performance of a sensor interface system? As the AFE is the first stage of the sensor interface system, the key requirements of having a wide input range, linearity, and a low noise level largely determine the performance of the sensor interface system. It is especially the low noise that has a significant impact as the noise of the feedback loop from the op-amp becomes the input-referred noise3 of the front-end. Thus, designing a low-noise op-amp is very critical. The main noises in an op-amp consists of thermal and flicker noise. The most crucial factor in reducing thermal noise is the semiconductor transistor that makes up the first input end of a circuit. In the first input end of an op-amp, voltage is converted to current by the trans-conductance4 of a transistor. Since the output current and the input voltage are linearly related as responding and control, respectively, arising problems can be compensated by maximizing the trans-conductance parameter. In some cases, flicker noises are even more emphasized than thermal noises. And as the power density of these flicker noises increases as the frequency decreases, reducing the flicker noise in the circuit that deals with low-frequency signals below tens of kHz is critical.
3Input-referred noise: The noise voltage or current that, when applied to the input of the noiseless circuit, generates the same output noise as the actual circuit does
4Trans-conductance: The electrical characteristic relating the current through the output of a device to the voltage across the input of a device
One way to solve this problem is to increase the physical size of the transistor in the first input end to reduce the fundamental flicker noise. In addition, techniques such as auto-zeroing and chopper stabilization—which reduces energy at the chopping frequency and maintains low noise levels at lower frequencies—can be used to remove noise more effectively. These techniques have been widely applied to many sensor interface semiconductor systems.
ADC: Low-power, High-resolution Connections for Sensor Interfaces
The voltage signals converted in the AFE go through an ADC to turn into digital signals, or the final output of a sensor interface. An ADC requires high resolution to accurately capture the analog data from the sensor device, and the retrieval of the data requires high energy efficiency.
Figure 4. The measurement of the power density and frequency of a N-bit CDAC
A successive-approximation-register ADC (SAR-ADC), which is one of the oldest ADC structures, possesses such high resolution and high energy efficiency on top of having an intuitive operation based on a circuit formation and binary search algorithm that is reminiscent of a digital logic. These attributes make it compatible with the latest semiconductor processes and, consequently, high in demand.
A SAR-ADC consists of an N-bit capacitor digital-to-analog converter (CDAC), a comparator, a SAR logic, and a track and hold (TAH). At its core, however, is the CDAC which uses a capacitor to convert a digital input into an analog output. At this time, the resolution of the SAR-ADC is inversely proportional to the number of bits in the CDAC, making the resolution become the smallest size of voltage the CDAC can exhibit. The number of bits in the CDAC also determines the magnitude of the quantization noise5. Quantization noise degrades resolution and appears uniformly over the entire frequency range of the power density.
Then, is it possible to increase the number of bits in the CDAC indefinitely to reduce the quantization noise and increase resolution? Although this is theoretically possible, there are practical limitations to implementing this in a semiconductor circuit. First, there are limitations within the CDAC as there are physical gaps between the capacitors carrying the bits in the CDAC due to constraints in the semiconductor process. The problem arises when the physical gap increases to cause errors in the form of harmonic distortion6 with linear degradation. This problem becomes even more severe as the size of the capacitor decreases. But there is even another limitation of the comparator that causes additional problems. As a comparator is responsible for comparing input voltages and outputting them, the size of the voltages that the comparator can compare is limited by various factors including thermal noise, flicker noise, and offset voltage7—even if the CDAC ideally produces a very small voltage. Finally, the resistance in the sampling switch at the input end increases the number of capacitors, and this causes greater thermal and KT/C noise8. In other words, it is physically challenging to improve resolution by significantly increasing the number of bits.
To overcome these limitations, the size of the gap between the capacitors can be minimized by adding or subtracting capacitors to each of the capacitors responsible for each bit in the CDAC. For the comparator, the limitations can be mitigated by using methods such as maximizing the trans-conductance parameter and frequency that was used for the AFE when addressing thermal noise and flicker noise. As the offset voltage has the same characteristics as flicker noise, it can also be removed in the same way. Finally, KT/C noise can be reduced below the desired noise level by increasing the size of the capacitors in the CDAC while increasing the sampling frequency. Using these techniques, low-power SAR-ADCs have been developed to obtain the level of 18-bit resolution.
5Quantization noise: The difference between the actual analog input that is typically represented by a sine wave and the value of the smallest discrete step or least significant bit
6Harmonic distortion: The distortion of the signals due to harmonic frequencies of a periodic voltage or current
7Offset voltage: The result of a difference in voltage between the outputs of two op-amps
8KT/C noise: The total thermal noise power added to a signal when a sample is taken on a capacitor
The Future of Next-generation Sensor Interface Technologies
The amount of physical, chemical, and biological data is growing at a staggering rate due to the advancement and expansion of today’s highlighted AI technology. Additionally, technologies that require real-time interaction such as AR and VR are being integrated into our daily lives while the use of mobile, wearable, and IoT/IoE devices is also on the rise. In line with these developments, the demand for related sensors is expected to grow exponentially, and the types and number of sensors required in a relevant system is anticipated to increase.
Based on this outlook of the future, it can be expected that developments in sensor interface systems will concentrate on technologies for miniaturization and low power consumption. Such goals were highlighted in recent papers presented at the International Solid-State Circuits Conference (ISSCC), one of the world’s most prestigious semiconductor conferences. The first type of trend discussed was the direct conversion sensor interface technology which converts data from sensor devices directly into digital values without using an AFE, which takes up a lot of power and space. Another trend that has a more direct approach to sensor solutions is a flexible type of technology that allows a single sensor interface system to be compatible with any of the voltage, current, resistance, and capacitance sensor devices. This minimizes the need for interfaces that correspond to various types of existing sensor devices. Finally, a third trend in the form of multi-modal sensor interface technology makes it possible to achieve simultaneous sensing with a single circuit system by complementing the flexible technology that has limitations in simultaneously sensing multiple sensor devices. These technologies are still in the early, conceptual stages, but they are expected to increasingly appear in the future.
Through this article, it was established that the main signals to be identified by sensing systems are resistance, capacitance, voltage and current. High-performing front-end circuits are required to convert these physical variables to an electrical signal that will further be processed by an ADC, with a common example being an SAR-ADC. To integrate more and more sensors into increasingly miniaturized devices, the sensing circuits need to offer ultra-low noise performance to achieve fine resolutions, maintain, linearity, and minimize power consumption as much as possible. This would lead to making sensor system design a challenging but exciting field. With increasing demands in digital connectivity and data acquisition from surrounding environments, numerous innovations are expected to emerge in sensor system design in the near future.
<Other articles from this series>
[DGIST Series] How the Quest for AI Led to Next-Generation Memory & Computing Processors
[DGIST Series] How Broadband Interface Circuits Are Evolving for Optimal Data Transfer
[DGIST Series] The Role of Semiconductor Technologies in Future Robotics
[DGIST Series] The Technologies Handling the Growing Data Demands in Healthcare
[DGIST Series] Silicon Photonics: Revolutionizing Data Transfers by Unleashing the Power of Light
[DGIST Series] AI-Powered Micro/Nanorobots to Revolutionize Medical Field
