Low-power, crystal-free wireless systems use free-running oscillators for both RF communications and sleep mode timers. However, these oscillators suffer from poor frequency stability, leading to reciprocal mixing and carrier mismatches for RF local oscillators, and additional guard time for sleep mode timers. Meeting the frequency stability requirements of standards like IEEE 802.15.4 and BLE is a significant challenge in crystal-free IoT mote design as the non-linear nature of oscillators demands special care in early simulations. Designers can use quick AC simulations, such as PNoise and HBNoise, or transient simulations, which are broadly applicable but take several weeks to gather sufficient data. Simulating the phase noise of free-running oscillators is especially tricky, and minor errors can lead to large miscalculations, which can be problematic for designers aiming to meet specifications on the first silicon iteration. This paper aims to cover the key methods used for oscillator phase noise simulations along with some conversion methods for interpreting the results in time domain for better understanding. As a design example, a ring oscillator circuit in Intel’s 16nm FinFET process is simulated and the resulting Allan Deviation is also calculated. Discrepancies between the simulated results are reported and recommendations are made for the most suitable method for free-running ring oscillators.

Accurately determining the time constant of a circuit enables IoT nodes to easily read out resistive or capacitive sensors. However, power and cost constraints lead to hardware limitations that complicate such measurements, including ADC noise, sampling clock jitter, poor voltage control over temperature and process, and a low-power microprocessor without a fast multiplier or floating point support. This work discusses estimating the time constant of a decaying exponential’s ADC samples using a simple weighted linear regression and describes the on-chip implementation of the regression on a low-cost, low-power microprocessor. Experimental results with an imperfect ADC show that time constants over more than two orders of magnitude can be accurately estimated within 5% of the nominal value with a mean standard error of about 1% of the nominal value.

SRAM Physically Unclonable Functions (PUFs) derive secret keys from start-up values for inherent security benefits but suffer from reliability issues due to bit flipping. We introduce the Threshold-based Majority Voting Scheme (TMVS), a lightweight method that eliminates noise and mitigates bias in SRAM PUFs while retaining the simplicity of majority voting decoders used by repetition codes, without the significant entropy loss that repetition codes incur under biased responses. TMVS runs entirely in software, requires no cell-level bit-error rate qualification or SRAM redesign, and avoids the complex decoders of heavy error correcting codes. We derive closed-form expressions for decoding-error probability and expected memory, validate them on experimental data, and present a security analysis that provides exact formulas for min-entropy and secrecy leakage due to helper data and bias, identifying conditions under which TMVS achieves zero secrecy leakage. On a large public dataset, TMVS shows near-zero cross-chip secrecy leakage and preserves average conditional min-entropy above 1 bit despite biased, spatially correlated SRAM statistics. Compared with prior work, TMVS offers the smallest decoding complexity at the cost of a larger PUF size. In a representative configuration, TMVS generates a 128-bit key with failure probability 9.15 · 10−6and zero secrecy leakage at a bit-flip probability of 10%, requiring only ∼ 248k clock cycles on a 32-bit ARM Cortex-M0. These results show that TMVS is practical and implementation-friendly for resource-constrained, low-power devices.

In this work we propose and demonstrate a protocol for a time synchronized channel hopping mesh network for wireless transceivers that use exclusively imprecise and inaccurate on-chip oscillators. This protocol is built on an IEEE 802.15.4 physical layer radio that enables interoperability with protocols such as 6TiSCH or Thread. A calibration-bootstrapped multi-hop mesh network is demonstrated with a single crystal-enabled node acting as the root. The protocol is designed to create a multi-hop mesh while compensating noisy and drifting oscillators and timers. With a 4 s synchronization period, an experimental implementation of the network maintains, in the worst case, 1.8 ms 3σ absolute time synchronization and 820 µs 3σ hop-to-hop synchronization across four hops, under ambient environmental conditions. The resistance to environmental variation is tested by varying one node's supply voltage. With time and frequency feedback from received packets, the node maintains this synchronization with a supply variation of 2.5 mV/s, which is equivalent to a temperature variation of 10°C/min with a packet rate of 0.5 Hz.

The single-chip micro-mote (SC$\mu \text{M}$) is a$2\times 3$mm2single-chip crystal-free mote-on-chip. SC$\mu \text{M}$implements the IEEE802.15.4 and BLE standards and can communicate with off-the-shelf radios compliant to those standards. SC$\mu \text{M}$exclusively uses on-chip oscillators, including a 2.4-GHz LC oscillator to synthesize the communication frequency, and a 2-MHz RC oscillator to clock the chip rate. The challenge is that the LC oscillator drifts at 2100 ppm over a temperature range of 45 °C, far from the 40-ppm maximum drift mandated by the IEEE802.15.4 standard. While one-shot calibration is possible, any temperature change causes IEEE802.15.4 communication to fail. This article describes a continuous calibration approach for SC$\mu \text{M}$to adapt the tuning of its oscillators as the temperature changes. Experimental results show that it allows SC$\mu \text{M}$to keep communicating with an IEEE802.15.4 radio even under the extreme condition of using a hair dryer to heat up the chip at 3 °C/min. Under these conditions, the drift of the LC oscillator stays within the ±40-ppm limit over 94% of the time. Similarly, the drift of the 2-MHz RC oscillator stays within ±1000 ppm limit 99.98% of the time.

The single-chip micro mote (SC$\mu \text{M}$) is a crystal-free single-chip mote that brings us one step closer to the Smart Dust vision, in particular, as it can communicate with off-the-shelf IEEE802.15.4 and Bluetooth low energy devices. However, before it can be part of such networks, the crystal-free SC$\mu \text{M}$chip needs to be able to accurately tune its communication frequency to synchronize to the network. This is a challenge since its onboard RC and LC-based resonating circuits have a drift rate that can be three orders of magnitude worse than crystal-based oscillators typically used in today’s radios. This article introduces QuickCal, a solution that allows an SC$\mu \text{M}$chip to self-calibrate against off-the-shelf devices dedicated to assisting with its calibration. We show that an SC$\mu \text{M}$chip can self-calibrate against this QuickCal Box in fewer than 3 min. We further validate that once it has self-calibrated, an SC$\mu \text{M}$chip can reliably communicate with off-the-shelf IEEE802.15.4 devices. Finally, we demonstrate a heterogeneous network—composed of an SC$\mu \text{M}$chip and an OpenMote device—implementing a full 6TiSCH Industrial IoT protocol stack, which uses time synchronization and channel hopping. This is the first time that a crystal-free radio is participating in a channel-hopping-enabled TSCH network.

The Internet-of-Things (IoT) promises one trillion wireless sensors in the next 10 to 15 years. To enable this scale, we present the experimental results on the time-keeping ability of crystal-free radios to lower the cost of the wireless sensors. We propose a network referenced frequency lock loop and demonstrate a one sigma mean frequency accuracy of 47 p/min, post calibration. We also extend this concept to calibrate the on-chip RF local oscillator by exploiting the network time synchronization for frequency calibration. This timing accuracy is sufficient to create a scalable wireless mesh network up to 10 hops deep with a 1 ms guard time interval. The impact of time synchronization on the average power consumption of the wireless sensor node is negligible and especially true for environments with mobility and high data traffic. We envision these emerging microsystems to be embedded into everyday objects and discuss the tradeoff of mobility with the average power consumption.

In the spring of 2017, the UC Berkeley department of EECS introduced an innovative new course: "28nm SoC for IoT." This course went far beyond schematic-level design typical of circuits education and resulted in a chip going out for manufacturing. Ten students with no prior IC experience, nine undergraduate and one graduate, designed and laid out an SoC in ST 28nm FD-SOI CMOS including a 2.4GHz transceiver, baseband filtering, ADC, Bluetooth MAC, a RISC-V CPU, and internal power regulation. The transceiver, baseband, ADC, and power regulation were successfully fabricated. This paper discusses the instructors' experiences and results with this course.

Ring oscillators have area and power advantages over LC tanks, but conventional wisdom is that rings must be locked to a high-Q external reference to be useful in RF communications. In this paper we explore performance of a 2.4GHz receiver incorporating only a free-running ring as a local oscillator. Using a simple technique to compensate for frequency error, we find that a minimum-size ring fabricated in 65nm CMOS and consuming only 105μW is able to demodulate 75% of received 802.15.4 packets and, if the FSK tone deviation is doubled from 802.15.4 spec, packet receive rate exceeds 99.8%.

Despite recent growth in the field of wearable devices, persistent collection of data with clear biomedical relevance remains elusive. The majority of products focus on short-term personal fitness metrics instead of long-term biomedical monitoring. The ideal wearable platform for researchers would include flexibility to test different biometric sensors. We present an open-source, modifiable, and user-reconfigurable wearable sensor system capable of enabling biomedical investigations not feasible with currently-available devices. Our armband device has been configured to measure skin temperature, light, and activity across days to detect internal circadian rhythms. Instability of circadian rhythms is linked to risk of many diseases, including mental illness such as depression, and has predictive power for personal affective state, yet its clinical use is slow in adoption in part because of the difficulty in acquiring relevant data. We provide evidence that such measurements are attainable at high resolution, low cost, and with minimal subject burden. Our device was tested with a variety of other sensors, and results indicate that daily circadian stability and hourly ultradian rhythms in core body temperature and hormone concentrations can be predicted from armband data. Future devices will be self-powered and perform automatic data collection to improve data continuity.