A 14-bit 250 MS/s IF Sampling Pipelined ADC in 180 nm CMOS Process

This paper presents a 14-bit 250 MS/s ADC fabricated in a 180 nm CMOS process, which aims at optimizing its linearity, operating speed, and power efficiency. The implemented ADC employs an improved SHA with parasitic optimized bootstrapped switches to achieve high sampling linearity over a wide input frequency range. It also explores a dedicated foreground calibration to correct the capacitor mismatches and the gain error of residue amplifier, where a novel configuration scheme with little cost for analog front-end is developed. Moreover, a partial non-overlapping clock scheme associated with a high-speed reference buffer and fast comparators is proposed to maximize the residue settling time. The implemented ADC is measured under different input frequencies with a sampling rate of 250 MS/s and it consumes 300 mW from a 1.8 V supply. For 30 MHz input, the measured SFDR and SNDR of the ADC is 94.7 dB and 68.5 dB, which can remain over 84.3 dB and 65.4 dB for up to 400 MHz. The measured DNL and INL after calibration are optimized to 0.15 LSB and 1.00 LSB, respectively, while the Walden FOM at Nyquist frequency is 0.57 pJ/step

A Low-Power, Reconfigurable, Pipelined ADC with Automatic Adaptation for Implantable Bioimpedance Applications

Biomedical monitoring systems that observe various physiological parameters or electrochemical reactions typically cannot expect signals with fixed amplitude or frequency as signal properties can vary greatly even among similar biosignals. Furthermore, advancements in biomedical research have resulted in more elaborate biosignal monitoring schemes which allow the continuous acquisition of important patient information. Conventional ADCs with a fixed resolution and sampling rate are not able to adapt to signals with a wide range of variation. As a result, reconfigurable analog-to-digital converters (ADC) have become increasingly more attractive for implantable biosensor systems. These converters are able to change their operable resolution, sampling rate, or both in order convert changing signals with increased power efficiency. Traditionally, biomedical sensing applications were limited to low frequencies. Therefore, much of the research on ADCs for biomedical applications focused on minimizing power consumption with smaller bias currents resulting in low sampling rates. However, recently bioimpedance monitoring has become more popular because of its healthcare possibilities. Bioimpedance monitoring involves injecting an AC current into a biosample and measuring the corresponding voltage drop. The frequency of the injected current greatly affects the amplitude and phase of the voltage drop as biological tissue is comprised of resistive and capacitive elements. For this reason, a full spectrum of measurements from 100 Hz to 10-100 MHz is required to gain a full understanding of the impedance. For this type of implantable biomedical application, the typical low power, low sampling rate analog-to-digital converter is insufficient. A different optimization of power and performance must be achieved. Since SAR ADC power consumption scales heavily with sampling rate, the converters that sample fast enough to be attractive for bioimpedance monitoring do not have a figure-of-merit that is comparable to the slower converters. Therefore, an auto-adapting, reconfigurable pipelined analog-to-digital converter is proposed. The converter can operate with either 8 or 10 bits of resolution and with a sampling rate of 0.1 or 20 MS/s. Additionally, the resolution and sampling rate are automatically determined by the converter itself based on the input signal. This way, power efficiency is increased for input signals of varying frequency and amplitude

Baseband analog front-end and digital back-end for reconfigurable multi-standard terminals

Multimedia applications are driving wireless network operators to add high-speed data services such as Edge (E-GPRS), WCDMA (UMTS) and WLAN (IEEE 802.11a,b,g) to the existing GSM network. This creates the need for multi-mode cellular handsets that support a wide range of communication standards, each with a different RF frequency, signal bandwidth, modulation scheme etc. This in turn generates several design challenges for the analog and digital building blocks of the physical layer. In addition to the above-mentioned protocols, mobile devices often include Bluetooth, GPS, FM-radio and TV services that can work concurrently with data and voice communication. Multi-mode, multi-band, and multi-standard mobile terminals must satisfy all these different requirements. Sharing and/or switching transceiver building blocks in these handsets is mandatory in order to extend battery life and/or reduce cost. Only adaptive circuits that are able to reconfigure themselves within the handover time can meet the design requirements of a single receiver or transmitter covering all the different standards while ensuring seamless inter-interoperability. This paper presents analog and digital base-band circuits that are able to support GSM (with Edge), WCDMA (UMTS), WLAN and Bluetooth using reconfigurable building blocks. The blocks can trade off power consumption for performance on the fly, depending on the standard to be supported and the required QoS (Quality of Service) leve

Integrated Circuit Blocks for High Performance Baseband and RF Analog-to-Digital Converters

Nowadays, the multi-standard wireless receivers and multi-format video processors have created a great demand for integrating multiple standards into a single chip. The multiple standards usually require several Analog to Digital Converters (ADCs) with different specifications. A promising solution is adopting a power and area efficient reconfigurable ADC with tunable bandwidth and dynamic range. The advantage of the reconfigurable ADC over customized ADCs is that its power consumption can be scaled at different specifications, enabling optimized power consumption over a wide range of sampling rates and resulting in a more power efficient design. Moreover, the reconfigurable ADC provides IP reuse, which reduces design efforts, development costs and time to market. On the other hand, software radio transceiver has been introduced to minimize RF blocks and support multiple standards in the same chip. The basic idea is to perform the analog to digital (A/D) and digital to analog (D/A) conversion as close to the antenna as possible. Then the backend digital signal processor (DSP) can be programmed to deal with the digital data. The continuous time (CT) bandpass (BP) sigma-delta ADC with good SNR and low power consumption is a good choice for the software radio transceiver. In this work, a proposed 10-bit reconfigurable ADC is presented and the non-overlapping clock generator and state machine are implemented in UMC 90nm CMOS technology. The state machine generates control signals for each MDAC stage so that the speed can be reconfigured, while the power consumption can be scaled. The measurement results show that the reconfigurable ADC achieved 0.6-200 MSPS speed with 1.9-27 mW power consumption. The ENOB is about 8 bit over the whole speed range. In the second part, a 2-bit quantizer with tunable delay circuit and 2-bit DACs are implemented in TSMC 0.13um CMOS technology for the 4th order CT BP sigma-delta ADC. The 2-bit quantizer and 2-bit DACs have 6dB SNR improvement and better stability over the single bit quantizer and DACs. The penalty is that the linearity of the feedback DACs should be considered carefully so that the nonlinearity doesn't deteriorate the ADC performance. The tunable delay circuit in the quantizer is designed to adjust the excess loop delay up to +/- 10% to achieve stability and optimal performance

A built-in self-test technique for high speed analog-to-digital converters

Fundação para a Ciência e a Tecnologia (FCT) - PhD grant (SFRH/BD/62568/2009

A re-configurable pipeline ADC architecture with built-in self-test techniques

High-performance analog and mixed-signal integrated circuits are integral parts of today\u27s and future networking and communication systems. The main challenge facing the semiconductor industry is the ability to economically produce these analog ICs. This translates, in part, into the need to efficiently evaluate the performance of such ICs during manufacturing (production testing) and to come up with dynamic architectures that enable the performance of these ICs to be maximized during manufacturing and later when they\u27re operating in the field. On the performance evaluation side, this dissertation deals with the concept of Built-In-Self-Test (BIST) to allow the efficient and economical evaluation of certain classes of high-performance analog circuits. On the dynamic architecture side, this dissertation deals with pipeline ADCs and the use of BIST to dynamically, during production testing or in the field, re-configure them to produce better performing ICs.;In the BIST system proposed, the analog test signal is generated on-chip by sigma-delta modulation techniques. The performance of the ADC is measured on-chip by a digital narrow-band filter. When this system is used on the wafer level, significant testing time and thus testing cost can be saved.;A re-configurable pipeline ADC architecture to improve the dynamic performance is proposed. Based on dynamic performance measurements, the best performance configuration is chosen from a collection of possible pipeline configurations. This basic algorithm can be applied to many pipeline analog systems. The proposed grouping algorithm cuts down the number of evaluation permutation from thousands to 18 for a 9-bit ADC thus allowing the method to be used in real applications.;To validate the developments of this dissertation, a 40MS/s 9-bit re-configurable pipeline ADC was designed and implemented in TSMC\u27s 0.25mum single-poly CMOS digital process. This includes a fully differential folded-cascode gain-boosting operational amplifier with high gain and high unity-gain bandwidth. The experimental results strongly support the effectiveness of reconfiguration algorithm, which provides an average of 0.5bit ENOB improvement among the set of configurations. For many applications, this is a very significant performance improvement.;The BIST and re-configurability techniques proposed are not limited to pipeline ADCs only. The BIST methodology is applicable to many analog systems and the re-configurability is applicable to any analog pipeline system

Reconfigurable low power robust pipeline ADC for Biomedical applications

Demand for high-performance analog-to-digital converter (ADC) integrated circuits (ICs) with optimal combined specifications of resolution, sampling rate and power consumption becomes dominant due to emerging applications in wireless communications, broad band transceivers, digital-intermediate frequency (IF) receivers and countless of digital devices. This research is dedicated to develop a pipeline ADC design methodology with minimum power dissipation, while keeping relatively high speed and high resolution

High Performance RF and Basdband Analog-to-Digital Interface for Multi-standard/Wideband Applications

The prevalence of wireless standards and the introduction of dynamic standards/applications, such as software-defined radio, necessitate the next generation wireless devices that integrate multiple standards in a single chip-set to support a variety of services. To reduce the cost and area of such multi-standard handheld devices, reconfigurability is desirable, and the hardware should be shared/reused as much as possible. This research proposes several novel circuit topologies that can meet various specifications with minimum cost, which are suited for multi-standard applications. This doctoral study has two separate contributions: 1. The low noise amplifier (LNA) for the RF front-end; and 2. The analog-to-digital converter (ADC). The first part of this dissertation focuses on LNA noise reduction and linearization techniques where two novel LNAs are designed, taped out, and measured. The first LNA, implemented in TSMC (Taiwan Semiconductor Manufacturing Company) 0.35Cm CMOS (Complementary metal-oxide-semiconductor) process, strategically combined an inductor connected at the gate of the cascode transistor and the capacitive cross-coupling to reduce the noise and nonlinearity contributions of the cascode transistors. The proposed technique reduces LNA NF by 0.35 dB at 2.2 GHz and increases its IIP3 and voltage gain by 2.35 dBm and 2dB respectively, without a compromise on power consumption. The second LNA, implemented in UMC (United Microelectronics Corporation) 0.13Cm CMOS process, features a practical linearization technique for high-frequency wideband applications using an active nonlinear resistor, which obtains a robust linearity improvement over process and temperature variations. The proposed linearization method is experimentally demonstrated to improve the IIP3 by 3.5 to 9 dB over a 2.5–10 GHz frequency range. A comparison of measurement results with the prior published state-of-art Ultra-Wideband (UWB) LNAs shows that the proposed linearized UWB LNA achieves excellent linearity with much less power than previously published works. The second part of this dissertation developed a reconfigurable ADC for multistandard receiver and video processors. Typical ADCs are power optimized for only one operating speed, while a reconfigurable ADC can scale its power at different speeds, enabling minimal power consumption over a broad range of sampling rates. A novel ADC architecture is proposed for programming the sampling rate with constant biasing current and single clock. The ADC was designed and fabricated using UMC 90nm CMOS process and featured good power scalability and simplified system design. The programmable speed range covers all the video formats and most of the wireless communication standards, while achieving comparable Figure-of-Merit with customized ADCs at each performance node. Since bias current is kept constant, the reconfigurable ADC is more robust and reliable than the previous published works

Mismatch-Immune Successive-Approximation Techniques for Nanometer CMOS ADCs

During the past decade, SAR ADCs have enjoyed increasing prominence due to their inherently scaling-friendly architecture. Several recent SAR ADC innovations focus on decreasing power consumption, mitigating thermal noise, and improving bandwidth, however most of those that use non-hybrid architectures are limited to moderate (8-10 bit) resolu- tion. Assuming an almost rail-to-rail dynamic range, comparator noise and DAC element mismatch constraints are critical but not insurmountable at 10 bits of resolution or less in sub-100nm processes. On the other hand, analysis shows that for medium-resolution ADCs (11-15 bits, depending on the LSB voltage of the converter), the mismatch sizing constraint still dominates unit capacitor sizing over the kT/C sampling noise constraint, and can only be mitigated by drawing increasingly larger capacitors. The focus of this work is to extend the scaling benefits of the SAR architecture to medium and higher ADC resolutions through mitigating and ultimately harnessing DAC element mismatch. This goal is achieved via a novel, completely reconfigurable capacitor DAC that allows the rearranging of capacitors to different trial groupings in the SAR cycle so that mismatch can be canceled. The DAC is implemented in a 12-bit SAR ADC in 65nm CMOS, and a nearly 2-bit improvement in linearity is demonstrated with a simple reconfiguration algorithm.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138630/1/ncolins_1.pd

BPLight-CNN: A Photonics-based Backpropagation Accelerator for Deep Learning

Training deep learning networks involves continuous weight updates across the various layers of the deep network while using a backpropagation algorithm (BP). This results in expensive computation overheads during training. Consequently, most deep learning accelerators today employ pre-trained weights and focus only on improving the design of the inference phase. The recent trend is to build a complete deep learning accelerator by incorporating the training module. Such efforts require an ultra-fast chip architecture for executing the BP algorithm. In this article, we propose a novel photonics-based backpropagation accelerator for high performance deep learning training. We present the design for a convolutional neural network, BPLight-CNN, which incorporates the silicon photonics-based backpropagation accelerator. BPLight-CNN is a first-of-its-kind photonic and memristor-based CNN architecture for end-to-end training and prediction. We evaluate BPLight-CNN using a photonic CAD framework (IPKISS) on deep learning benchmark models including LeNet and VGG-Net. The proposed design achieves (i) at least 34x speedup, 34x improvement in computational efficiency, and 38.5x energy savings, during training; and (ii) 29x speedup, 31x improvement in computational efficiency, and 38.7x improvement in energy savings, during inference compared to the state-of-the-art designs. All these comparisons are done at a 16-bit resolution; and BPLight-CNN achieves these improvements at a cost of approximately 6% lower accuracy compared to the state-of-the-art