Design techniques for low-power SAR ADCs in nano-scale CMOS technologies

This thesis presents low power design techniques for successive approximation register (SAR) analog-to-digital converters (ADCs) in nano-scale CMOS technologies. Low power SAR ADCs face two major challenges especially at high resolutions: (1) increased comparator power to suppress the noise, and (2) increased DAC switching energy due to the large DAC size. To improve the comparator’s power efficiency, a statistical estimation based comparator noise reduction technique is presented. It allows a low power and noisy comparator to achieve high signal-to-noise ratio (SNR) by estimating the conversion residue. A first prototype ADC in 65nm CMOS has been developed to validate the proposed noise reduction technique. It achieves 4.5 fJ/conv-step Walden figure of merit and 64.5 dB signal-to-noise and distortion ratio (SNDR). In addition, a bidirectional single-side switching technique is developed to reduce the DAC switching power. It can reduce the DAC switching power and the total number of unit capacitors by 86% and 75%, respectively. A second prototype ADC with the proposed switching technique is designed and fabricated in 180nm CMOS technology. It achieves an SNDR of 63.4 dB and consumes only 24 Wat 1MS/s, leading to aWalden figure of merit of 19.9 fJ/conv-step. This thesis also presents an improved loop-unrolled SAR ADC, which works at high frequency with reduced SAR logic power and delay. It employs the bidirectional single-side switching technique to reduce the comparator common-mode voltage variation. In addition, it uses a Vcm-adaptive offset calibration technique which can accurately calibrate comparator’s offset at its operating Vcm. A prototype ADC designed in 40nm CMOS achieves 35 dB at 700 MS/s sampling rate and consumes only 0.95 mW, leading to a Walden figure of merit of 30 fJ/conv-step.Electrical and Computer Engineerin

Quadrature Phase-Domain ADPLL with Integrated On-line Amplitude Locked Loop Calibration for 5G Multi-band Applications

5th generation wireless systems (5G) have expanded frequency band coverage with the low-band 5G and mid-band 5G frequencies spanning 600 MHz to 4 GHz spectrum. This dissertation focuses on a microelectronic implementation of CMOS 65 nm design of an All-Digital Phase Lock Loop (ADPLL), which is a critical component for advanced 5G wireless transceivers. The ADPLL is designed to operate in the frequency bands of 600MHz-930MHz, 2.4GHz-2.8GHz and 3.4GHz-4.2GHz. Unique ADPLL sub-components include: 1) Digital Phase Frequency Detector, 2) Digital Loop Filter, 3) Channel Bank Select Circuit, and 4) Digital Control Oscillator. Integrated with the ADPLL is a 90-degree active RC-CR phase shifter with on-line amplitude locked loop (ALL) calibration to facilitate enhanced image rejection while mitigating the effects of fabrication process variations and component mismatch. A unique high-sensitivity high-speed dynamic voltage comparator is included as a key component of the active phase shifter/ALL calibration subsystem. 65nm CMOS technology circuit designs are included for the ADPLL and active phase shifter with simulation performance assessments. Phase noise results for 1 MHz offset with carrier frequencies of 600MHz, 2.4GHz, and 3.8GHz are -130, -122, and -116 dBc/Hz, respectively. Monte Carlo simulations to account for process variations/component mismatch show that the active phase shifter with ALL calibration maintains accurate quadrature phase outputs when operating within the frequency bands 600MHz-930MHz, 2.4GHz-2.8GHz and 3.4GHz-4.2GHz

Investigating the impact of image content on the energy efficiency of hardware-accelerated digital spatial filters

Battery-operated low-power portable computing devices are becoming an inseparable part of human daily life. One of the major goals is to achieve the longest battery life in such a device. Additionally, the need for performance in processing multimedia content is ever increasing. Processing image and video content consume more power than other applications. A widely used approach to improving energy efficiency is to implement the computationally intensive functions as digital hardware accelerators. Spatial filtering is one of the most commonly used methods of digital image processing. As per the Fourier theory, an image can be considered as a two-dimensional signal that is composed of spatially extended two-dimensional sinusoidal patterns called gratings. Spatial frequency theory states that sinusoidal gratings can be characterised by its spatial frequency, phase, amplitude, and orientation. This article presents results from our investigation into assessing the impact of these characteristics of a digital image on the energy efficiency of hardware-accelerated spatial filters employed to process the same image. Two greyscale images each of size 128 × 128 pixels comprising two-dimensional sinusoidal gratings at maximum spatial frequency of 64 cycles per image orientated at 0° and 90°, respectively, were processed in a hardware implemented Gaussian smoothing filter. The energy efficiency of the filter was compared with the baseline energy efficiency of processing a featureless plain black image. The results show that energy efficiency of the filter drops to 12.5% when the gratings are orientated at 0° whilst rises to 72.38% at 90°

Low-power high-speed ADC design techniques in scaled CMOS process

The power consumption of a single-channel successive approximation register (SAR) analog-to-digital (ADC) tends to linearly increase with its sampling rate (f[subscript s]), when f[subscript s] is small. However, when f[subscript s] passes a certain point for a given technology node, the ADC power P increases at much higher rate and the normalized power efficiency (P/f[subscript s]) starts to degrade rapidly. To enhance the conversion speed of SAR ADC, while maintaining a good power efficiency, this thesis presents speed-enhancing techniques for SAR ADC in nano-scale CMOS technologies. First chapter presents a 2b/cycle hybrid SAR architecture with only 1 differential capacitor-DAC (CDAC). Unlike prior multi-bit/cycle SAR works that make use of only the DAC differential mode (DM) voltage, the proposed architecture exploits both the DM and the common mode (CM). By using two degrees of freedom, 2b/cycle conversion technique can boost the f[subscript s] of the ADC without any additional DAC arrays. High-speed ADCs can boost the conversion speed not only by increasing the f[subscript s] of a single-channel ADC, but also by time-interleaving multiple ADC sub-channels running at a lower rate. For an N-channel time-interleaved (TI) SAR ADC operating at f[subscript s], each sub-SAR channel only needs to operate at f[subscript s]=N. Therefore, each sub-SAR can operate in the linear power versus speed region, leading to a significant power saving compared to a single-channel ADC running at the same sampling rate. Despite of its power efficiency, TI-ADC suffers from mismatches among sub-ADC channels, including gain, offset, and timing mismatches. Among them, timing skew is one of the most difficult errors to calibrate as it is nontrivial to extract and its induced error depends on both the frequency and the amplitude of the input signal. Second chapter of this thesis presents a TI-SAR with a fast variance-based timing-skew calibration technique. It uses a single-comparator based window detector (WD) to calibrate the timing skew. The WD suppresses variance estimation errors and allow precise variance estimation from a significantly small number of samples. It has low-hardware cost and orders of magnitude faster convergence speed compared to prior variance-based timing-skew calibration technique. The last chapter presents another TI-SAR with mean absolute deviation (MAD) based timing-skew calibration technique. In addition to all the advantages presented with the fast variance-based timing-skew calibration technique, the proposed technique further reduces the digital computation power by 50% by eliminating the squaring operations, which are essential in variance-based calibration techniqueElectrical and Computer Engineerin

Multilevel Power Estimation Of VLSI Circuits Using Efficient Algorithms

New and complex systems are being implemented using highly advanced Electronic Design Automation (EDA) tools. As the complexity increases day by day, the dissipation of power has emerged as one of the very important design constraints. Now low power designs are not only used in small size applications like cell phones and handheld devices but also in high-performance computing applications. Embedded memories have been used extensively in modern SOC designs. In order to estimate the power consumption of the entire design correctly, an accurate memory power model is needed. However, the memory power model commonly used in commercial EDA tools is too simple to estimate the power consumption accurately. For complex digital circuits, building their power models is a popular approach to estimate their power consumption without detailed circuit information. In the literature, most of power models are built with lookup tables. However, building the power models with lookup tables may become infeasible for large circuits because the table size would increase exponentially to meet the accuracy requirement. This thesis involves two parts. In first part it uses the Synopsys power measurement tools together with the use of synthesis and extraction tools to determine power consumed by various macros at different levels of abstraction including the Register Transfer Level (RTL), the gate and the transistor level. In general, it can be concluded that as the level of abstraction goes down the accuracy of power measurement increases depending on the tool used. In second part a novel power modeling approach for complex circuits by using neural networks to learn the relationship between power dissipation and input/output characteristic vector during simulation has been developed. Our neural power model has very low complexity such that this power model can be used for complex circuits. Using such a simple structure, the neural power models can still have high accuracy because they can automatically consider the non-linear power distributions. Unlike the power characterization process in traditional approaches, our characterization process is very simple and straightforward. More importantly, using the neural power model for power estimation does not require any transistor-level or gate-level description of the circuits. The experimental results have shown that the estimations are accurate and efficient for different test sequences with wide range of input distributions

Low Power Processor Architectures and Contemporary Techniques for Power Optimization – A Review

The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. © 2009 ACADEMY PUBLISHER