Noise shaping Asynchronous SAR ADC based time to digital converter

Time-to-digital converters (TDCs) are key elements for the digitization of timing information in modern mixed-signal circuits such as digital PLLs, DLLs, ADCs, and on-chip jitter-monitoring circuits. Especially, high-resolution TDCs are increasingly employed in on-chip timing tests, such as jitter and clock skew measurements, as advanced fabrication technologies allow fine on-chip time resolutions. Its main purpose is to quantize the time interval of a pulse signal or the time interval between the rising edges of two clock signals. Similarly to ADCs, the performance of TDCs are also primarily characterized by Resolution, Sampling Rate, FOM, SNDR, Dynamic Range and DNL/INL. This work proposes and demonstrates 2nd order noise shaping Asynchronous SAR ADC based TDC architecture with highest resolution of 0.25 ps among current state of art designs with respect to post-layout simulation results. This circuit is a combination of low power/High Resolution 2nd Order Noise Shaped Asynchronous SAR ADC backend with simple Time to Amplitude converter (TAC) front-end and is implemented in 40nm CMOS technology. Additionally, special emphasis is given on the discussion on various current state of art TDC architectures.Electrical and Computer Engineerin

Noise-Shaping SAR ADCs: From Discrete Time to Continuous Time

Noise-shaping (NS) SAR ADCs become popular recently, thanks to their low-power and high-resolution features. This article first summarizes and benchmarks different discrete-time (DT) NS-SAR implementations in literature. An open-loop duty-cycled residue amplifier is selected as a power-efficient solution to realize high residue gain. Then, a digital-predicted mismatch error shaping technique is introduced to improve the DAC linearity. The proposed DT NS-SAR ADC achieves 80 dB SNDR and 98 dB SFDR in a 31.25 kHz bandwidth while consuming 7.3 μW. Next, the NS-SAR architecture is extended from DT operation to continuous-time (CT) operation. The ADC sampling switch is removed, and the loop filter is duty cycled to realize the CT NS-SAR operation. Compared to DT designs, the CT NS-SAR ADC is easy to drive and has an inherent anti-aliasing function. As a proof of concept, the proposed CT NS-SAR ADC achieves 77 dB SNDR and 86 dB SFDR in a 62.5 kHz bandwidth with a power consumption of 13.5 μW

A 7.3-μ W 13-ENOB 98-dB SFDR Noise-Shaping SAR ADC With Duty-Cycled Amplifier and Mismatch Error Shaping

This article presents a second-order noise-shaping successive-approximation-register (SAR) analog-to-digital converter (ADC) that employs a duty-cycled amplifier and digital-predicted mismatch error shaping (MES). The loop filter is composed of an active amplifier and two cascaded passive integrators to provide a theoretical 30-dB in-band noise attenuation. The amplifier achieves 18\times gain in a power-efficient way thanks to its inverter-based topology and duty-cycled operation. The capacitor mismatch in the digital-to-analog converter (DAC) array is mitigated by first-order MES. A two-level digital prediction scheme is adopted with MES to avoid input range loss. Fabricated in 65-nm CMOS technology, the prototype achieves 80-dB peak signal-to-noise-and-distortion-ratio (SNDR) and 98-dB peak spurious-free-dynamic-range (SFDR) in a 31.25-kHz bandwidth with 16\times oversampling ratio (OSR), leading to a Schreier figure-of-merit (FoM) of 176.3 dB and a Walden FoM of 14.3 fJ/conversion-step.</p

Fully-passive switched-capacitor techniques for high performance SAR ADC design

In recent years, SAR ADC becomes more and more popular in various low-power applications such as wireless sensors and low energy radios due to its circuit simplicity, high power efficiency, and scaling compatibility. However, its speed is limited by its successive approximation procedures and its power efficiency greatly reduces with the ADC resolution going beyond 10 bit. To address these issues, this thesis proposes to embed two techniques: 1) compressive sensing (CS) and 2) noise shaping (NS) to a conventional SAR ADC. The realization of both techniques are based on fully-passive switched-capacitor techniques. CS is a recently emerging sampling paradigm, stating that the sparsity of a signal can be exploited to reduce the ADC sampling rate below the Nyquist rate. Different from conventional CS frameworks which require dedicated analog CS encoders, this thesis proposes a fully-passive CS-SAR ADC architecture which only requires minor modification to a conventional SAR ADC. Two chips are fabricated in a 0.13 µm process to prove the concept. One chip is a single-channel CS-SAR ADC which can reduce the ADC conversion rate by 4 times, thus reducing the ADC power by 4 times. In many wireless sensing applications, multiple ADCs are commonly required to sense multi-channel signals such as multi-lead ECG sensing and parallel neural recording. Therefore, the other chip is a multi-channel CS-SAR ADC which can simultaneously convert 4-channel signals with a sampling rate of one channel’s Nyquist rate. At 0.8 V and 1 MS/s, both chips achieve an effective Walden FoM of around 5 fJ/conversion-step. This thesis also proposes a novel NS SAR ADC architecture that is simple, robust and low power for high-resolution applications. Compared to conventional ∆Σ ADCs, it replaces the power-hungry active integrator with a passive integrator which only requires one switch and two capacitors. Compared to previous 1st-order NS SAR ADC works, it achieves the best NS performance and can be easily extended to 2nd-order. A 1st-order 10-bit NS SAR ADC is fabricated in a 0.13 µm process. Through NS, SNDR increases by 6 dB with OSR doubled, achieving a 12- bit ENOB at OSR = 8. An improved version of a 2nd-order 9-bit NS SAR ADC is designed and simulated in a 40 nm process. The SNDR increases by 10 dB with OSR doubled, achieving a 14-bit ENOB at OSR = 16. At a bandwidth of 312.5 kHz, the Schreier FoM is 181 dB and the Walden FoM is 12.5 fJ/conversion-step, proving that the proposed NS SAR ADC architecture can achieve high resolution and high power efficiency simultaneously.Electrical and Computer Engineerin

Power Efficient Architectures for Low Noise Switched-Capacitor Filters and High Accuracy Analog-to-Digital Converters

Filters and data converters are key analog-and-mixed-signal (AMS) building blocks in communication systems, such as software-defined radios and internet-of-things. In this dissertation, novel switched-capacitor filter and analog-to-digital converter (ADC) circuit configurations have been explored which are power efficient and are digital scaling friendly. First, a novel switched-capacitor low-pass filter architecture is presented. In the proposed scheme, a feedback path is added to a charge-rotating real-pole filter to implement complex poles. The selectivity is enhanced, and the in-band loss is reduced compared with the real-pole filter. The output thermal noise level and the tuning range are both close to those of the real-pole filter. A fourth-order filter prototype was implemented in a 180-nm CMOS technology. The measured in-band loss is reduced by 3.3 dB compared with that of a real-pole filter. The sampling rate of the filter is programmable from 65 to 300 MS/s with a constant DC gain. The 3-dB cut-off frequency of the filter can be tuned from 0.490 to 13.3 MHz with over 100-dB maximum stop-band rejection. The measured in-band third-order output intercept point is 28.7 dBm, and the averaged spot noise is 6.54 nV/Hz. The filter consumes 4.3 mW from a 1.8 V supply. Next, an opamp-free noise shaping successive-approximation register (SAR) ADC is presented. Third-order noise shaping is achieved by implementing a second-order passive filter and a passive error feedback topology. In the proposed scheme, the SAR error signals (including quantization noise, comparator thermal noise, and DAC settling error) are subjected to third-order noise shaping. Therefore, the thermal noise specifications of the comparator can be relaxed. Also, since no active element is used, the proposed scheme achieves a higher power efficiency than earlier SAR ADCs. Finally, a novel 0-2 Multi Stage Noise Shaping (MASH) ADC is presented. The first stage is implemented using a 4-bit SAR ADC. The second stage uses a VCO-based quantizer (VCOQ). Unlike earlier VCOQs which provide first-order noise shaping, the proposed VCOQ achieves second-order noise filtering. To implement this noise shaping, the quantization noise of the VCOQ is extracted as a pulse-width-modulated (PWM) signal, and it is fed back to the VCO input using a charge pump circuit. Any error related to the charge pump circuitry will be first-order shaped at the output. Simulation results confirm the second-order noise shaping of the output of the ADC, and an excellent (14-bit SNDR) performance with oversampling ratio (OSR) of 16

Design Techniques for High-Performance SAR A/D Converters

The design of electronics needs to account for the non-ideal characteristics of the device technologies used to realize practical circuits. This is particularly important in mixed analog-digital design since the best device technologies are very different for digital compared to analog circuits. One solution for this problem is to use a calibration correction approach to remove the errors introduced by devices, but this adds complexity and power dissipation, as well as reducing operation speed, and so must be optimised. This thesis addresses such an approach to improve the performance of certain types of analog-to-digital converter (ADC) used in advanced telecommunications, where speed, accuracy and power dissipation currently limit applications. The thesis specifically focuses on the design of compensation circuits for use in successive approximation register (SAR) ADCs. ADCs are crucial building blocks in communication systems, in general, and for mobile networks, in particular. The recently launched fifth generation of mobile networks (5G) has required new ADC circuit techniques to meet the higher speed and lower power dissipation requirements for 5G technology. The SAR has become one of the most favoured architectures for designing high-performance ADCs, but the successive nature of the circuit operation makes it difficult to reach ∼GS/s sampling rates at reasonable power consumption. Here, two calibration techniques for high-performance SAR ADCs are presented. The first uses an on-chip stochastic-based mismatch calibration technique that is able to accurately compute and compensate for the mismatch of a capacitive DAC in a SAR ADC. The stochastic nature of the proposed calibration method enables determination of the mismatch of the CAPDAC with a resolution much better than that of the DAC. This allows the unit capacitor to scale down to as low as 280aF for a 9-bit DAC. Since the CAP-DAC causes a large part of the overall dynamic power consumption and directly determines both the sizes of the driving and sampling switches and the size of the input capacitive load of the ADC and the kT/C noise power, a small CAP-DAC helps the power efficiency. To validate the proposed calibration idea, a 10-bit asynchronous SAR ADC was fabricated in 28-nm CMOS. Measurement results show that the proposed stochastic calibration improves the ADC’s SFDR and SNDR by 14.9 dB, 11.5 dB, respectively. After calibration, the fabricated SAR ADC achieves an ENOB of 9.14 bit at a sampling rate of 85 MS/s, resulting in a Walden FoM of 10.9 fJ/c-s. The second calibration technique is a timing-skew calibration for a time-interleaved (TI) SAR ADC that calibrates/computes the inter-channel timing and offset mismatch simultaneously. Simulation results show the effectiveness of this calibration method. When used together, the proposed mismatch calibration technique and the timing-skew calibration technique enables a TI SAR ADC to be designed that can achieve a sampling rate of ∼GS/s with 10-bit resolution and a power consumption as low as ∼10mW; specifications that satisfy the requirements of 5G technology

Ultra-low Power Circuits and Architectures for Neuromorphic Computing Accelerators with Emerging TFETs and ReRAMs

Neuromorphic computing using post-CMOS technologies is gaining increasing popularity due to its promising potential to resolve the power constraints in Von-Neumann machine and its similarity to the operation of the real human brain. To design the ultra-low voltage and ultra-low power analog-to-digital converters (ADCs) for the neuromorphic computing systems, we explore advantages of tunnel field effect transistor (TFET) analog-to-digital converters (ADCs) on energy efficiency and temperature stability. A fully-differential SAR ADC is designed using 20 nm TFET technology with doubled input swing and controlled comparator input common-mode voltage. To further increase the resolution of the ADC, we design an energy efficient 12-bit noise shaping (NS) successive-approximation register (SAR) ADC. The 2nd-order noise shaping architecture with multiple feed-forward paths is adopted and analyzed to optimize system design parameters. By utilizing tunnel field effect transistors (TFETs), the Delta-Sigma SAR is realized under an ultra-low supply voltage VDD with high energy efficiency. The stochastic neuron is a key for event-based probabilistic neural networks. We propose a stochastic neuron using a metal-oxide resistive random-access memory (ReRAM). The ReRAM\u27s conducting filament with built-in stochasticity is used to mimic the neuron\u27s membrane capacitor, which temporally integrates input spikes. A capacitor-less neuron circuit is designed, laid out, and simulated. The output spiking train of the neuron obeys the Poisson distribution. Based on the ReRAM based neuron, we propose a scalable and reconfigurable architecture that exploits the ReRAM-based neurons for deep Spiking Neural Networks (SNNs). In prior publications, neurons were implemented using dedicated analog or digital circuits that are not area and energy efficient. In our work, for the first time, we address the scaling and power bottlenecks of neuromorphic architecture by utilizing a single one-transistor-one-ReRAM (1T1R) cell to emulate the neuron. We show that the ReRAM-based neurons can be integrated within the synaptic crossbar to build extremely dense Process Element (PE)–spiking neural network in memory array–with high throughput. We provide microarchitecture and circuit designs to enable the deep spiking neural network computing in memory with an insignificant area overhead

Plasmonic color filter array, high performance analog to digital converter architectures and novel circuit techniques

Part I: Plasmonic color filters can be manufactured at lower cost since they can be fabricated in single lithographic process step as compared to Fabry-Perot based filters. In addition, they have narrow passband making resolving sharp features in sample spectrum possible. Due to these benefits, in this thesis, Plasmonic color filters are investigated as alternative to conventional color filters and their feasibility for spectroscopy demonstrated through reconstruction of 6 sample spectra by using a set of 20 color filters. The error in reconstructed sample spectra is less than 0.137 root mean squared error across all samples. Part II: A novel 12-bit pipelined successive approximation analog to digital converter is investigated for high speed data conversion. The design was implemented in TSMC 65nm process to demonstrate the feasibility of the architecture. Furthermore, a high dynamic range audio delta sigma modulator using pseudo-pseudo differential topology was investigated and feasibility simulated using TSMC 65nm process. In addition, various novel systems and circuit techniques including efficient calibration of feedback digital to analog converters, new boosted switch and push-pull source follower circuits were investigated to improve upon existing circuit topologies