Efficient generation of data sets for one-shot statistical calibration of RF/mm-wave circuits

International audienc

Solutions pour l'auto-adaptation des systèmes sans fil

The current demand on ubiquitous connectivity imposes stringent requirements on the fabrication of Radio-Frequency (RF) circuits. Designs are consequently transferred to the most advanced CMOS technologies that were initially introduced to improve digital performance. In addition, as technology scales down, RF circuits are more and more susceptible to a lot of variations during their lifetime, as manufacturing process variability, temperature, environmental conditions, aging… As a result, the usual worst-case circuit design is leading to sub-optimal conditions, in terms of power and/or performance most of the time for the circuit. In order to counteract these variations, increasing the performances and also reduce power consumption, adaptation strategies must be put in place.More importantly, the fabrication process introduces more and more performance variability, which can have a dramatic impact on the fabrication yield. That is why RF designs are not easily fabricated in the most advanced CMOS technologies, as 32nm or 22nm nodes for instance. In this context, the performances of RF circuits need to be calibrated after fabrication so as to take these variations into account and recover yield loss.This thesis work is presenting on a post-fabrication calibration technique for RF circuits. This technique is performed during production testing with minimum extra cost, which is critical since the cost of test can be comparable to the cost of fabrication concerning RF circuits and cannot be further raised. Calibration is enabled by equipping the circuit with tuning knobs and sensors. Optimal tuning knob identification is achieved in one-shot based on a single test step that involves measuring the sensor outputs once. For this purpose, we rely on variation-aware sensors which provide measurements that remain invariant under tuning knob changes. As an auxiliary benefit, the variation-aware sensors are non-intrusive and totally transparent to the circuit.Our proposed methodology has first been demonstrated with simulation data with an RF power amplifier as a case study. Afterwards, a silicon demonstrator has then been fabricated in a 65nm technology in order to fully demonstrate the methodology. The fabricated dataset of circuits is extracted from typical and corner wafers. This feature is very important since corner circuits are the worst design cases and therefore the most difficult to calibrate. In our case, corner circuits represent more than the two third of the overall dataset and the calibration can still be proven. In details, fabrication yield based on 3 sigma performance specifications is increased from 21% to 93%. This is a major performance of the technique, knowing that worst case circuits are very rare in industrial fabrication.La demande courante de connectivité instantanée impose un cahier des charges très strict sur la fabrication des circuits Radio-Fréquences (RF). Les circuits doivent donc être transférées vers les technologies les plus avancées, initialement introduites pour augmenter les performances des circuits purement numériques. De plus, les circuits RF sont soumis à de plus en plus de variations et cette sensibilité s’accroît avec l’avancées des technologies. Ces variations sont par exemple les variations du procédé de fabrication, la température, l’environnement, le vieillissement… Par conséquent, la méthode classique de conception de circuits “pire-cas” conduit à une utilisation non-optimale du circuit dans la vaste majorité des conditions, en termes de performances et/ou de consommation. Ces variations doivent donc être compensées, en utilisant des techniques d’adaptation.De manière plus importante encore, le procédé de fabrication des circuits introduit de plus en plus de variabilité dans les performances des circuits, ce qui a un impact important sur le rendement de fabrication des circuits. Pour cette raison, les circuits RF sont difficilement fabriqués dans les technologies CMOS les plus avancées comme les nœuds 32nm ou 22nm. Dans ce contexte, les performances des circuits RF doivent êtres calibrées après fabrication pour prendre en compte ces variations et retrouver un haut rendement de fabrication.Ce travail de these présente une méthode de calibration post-fabrication pour les circuits RF. Cette méthodologie est appliquée pendant le test de production en ajoutant un minimum de coût, ce qui est un point essentiel car le coût du test est aujourd’hui déjà comparable au coût de fabrication d’un circuit RF et ne peut être augmenté d’avantage. Par ailleurs, la puissance consommée est aussi prise en compte pour que l’impact de la calibration sur la consommation soit minimisé. La calibration est rendue possible en équipant le circuit avec des nœuds de réglages et des capteurs. L’identification de la valeur de réglage optimale du circuit est obtenue en un seul coup, en testant les performances RF une seule et unique fois. Cela est possible grâce à l’utilisation de capteurs de variations du procédé de fabrication qui sont invariants par rapport aux changements des nœuds de réglage. Un autre benefice de l’utilisation de ces capteurs de variation sont non-intrusifs et donc totalement transparents pour le circuit sous test. La technique de calibration a été démontrée sur un amplificateur de puissance RF utilisé comme cas d’étude. Une première preuve de concept est développée en utilisant des résultats de simulation.Un démonstrateur en silicium a ensuite été fabriqué en technologie 65nm pour entièrement démontrer le concept de calibration. L’ensemble des puces fabriquées a été extrait de trois types de wafer différents, avec des transistors aux performances lentes, typiques et rapides. Cette caractéristique est très importante car elle nous permet de considérer des cas de procédé de fabrication extrêmes qui sont les plus difficiles à calibrer. Dans notre cas, ces circuits représentent plus des deux tiers des puces à disposition et nous pouvons quand même prouver notre concept de calibration. Dans le détails, le rendement de fabrication passe de 21% avant calibration à plus de 93% après avoir appliqué notre méthodologie. Cela constitue une performance majeure de notre méthodologie car les circuits extrêmes sont très rares dans une fabrication industrielle

Containing the Nanometer “Pandora-Box”: Cross-Layer Design Techniques for Variation Aware Low Power Systems

The demand for richer multimedia services, multifunctional portable devices and high data rates can only been visioned due to the improvement in semiconductor technology. Unfortunately, sub-90 nm process nodes uncover the nanometer Pandora-box exposing the barriers of technology scaling—parameter variations, that threaten the correct operation of circuits, and increased energy consumption, that limits the operational lifetime of today’s systems. The contradictory design requirements for low-power and system robustness, is one of the most challenging design problems of today. The design efforts are further complicated due to the heterogeneous types of designs (logic, memory, mixed-signal) that are included in today’s complex systems and are characterized by different design requirements. This paper presents an overview of techniques at various levels of design abstraction that lead to low power and variation aware logic, memory and mixed-signal circuits and can potentially assist in meeting the strict power budgets and yield/quality requirements of future systems

A Sleep-Scheduling-Based Cross-Layer Design Approach for Application-Specific Wireless Sensor Networks

The pervasiveness and operational autonomy of mesh-based wireless sensor networks (WSNs) make them an ideal candidate in offering sustained monitoring functions at reasonable cost over a wide area. To extend the functional lifetime of battery-operated sensor nodes, stringent sleep scheduling strategies with communication duty cycles running at sub-1% range are expected to be adopted. Although ultra-low communication duty cycles can cast a detrimental impact on sensing coverage and network connectivity, its effects can be mitigated with adaptive sleep scheduling, node deployment redundancy and multipath routing within the mesh WSN topology. This work proposes a cross-layer organizational approach based on sleep scheduling, called Sense-Sleep Trees (SS-Trees), that aims to harmonize the various engineering issues and provides a method to extend monitoring capabilities and operational lifetime of mesh-based WSNs engaged in wide-area surveillance applications. Various practical considerations such as sensing coverage requirements, duty cycling, transmission range assignment, data messaging, and protocol signalling are incorporated to demonstrate and evaluate the feasibility of the proposed design approach

Modern Telemetry

Telemetry is based on knowledge of various disciplines like Electronics, Measurement, Control and Communication along with their combination. This fact leads to a need of studying and understanding of these principles before the usage of Telemetry on selected problem solving. Spending time is however many times returned in form of obtained data or knowledge which telemetry system can provide. Usage of telemetry can be found in many areas from military through biomedical to real medical applications. Modern way to create a wireless sensors remotely connected to central system with artificial intelligence provide many new, sometimes unusual ways to get a knowledge about remote objects behaviour. This book is intended to present some new up to date accesses to telemetry problems solving by use of new sensors conceptions, new wireless transfer or communication techniques, data collection or processing techniques as well as several real use case scenarios describing model examples. Most of book chapters deals with many real cases of telemetry issues which can be used as a cookbooks for your own telemetry related problems

A low power, low noise, 1.8 GHz voltage-controlled oscillator

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (leaf 97).by Donald A. Hitko.M.S

Remote Navigation and Contact-Force Control of Radiofrequency Ablation Catheters

Atrial fibrillation (AF), the most common and clinically significant heart rhythm disorder, is characterized by rapid and irregular electrical activity in the upper chambers resulting in abnormal contractions. Radiofrequency (RF) cardiac catheter ablation is a minimally invasive curative treatment that aims to electrically correct signal pathways inside the atria to restore normal sinus rhythm. Successful catheter ablation requires the complete and permanent elimination of arrhythmogenic signals by delivering transmural RF ablation lesions contiguously near and around key cardiac structures. These procedures are complex and technically challenging and, even when performed by the most skilled physician, nearly half of patients undergo repeat procedures due to incomplete elimination of the arrhythmogenic pathways. This thesis aims to incorporate innovative design to improve catheter stability and maneuverability through the development of robotic platforms that enable precise placement of reproducibly durable ablation lesions. The first part of this thesis deals with the challenges to lesion delivery imposed by cardiorespiratory motion. One of the main determinants of the delivery of durable and transmural RF lesions is the ability to define and maintain a constant contact force between the catheter tip electrode and cardiac tissue, which is hampered by the presence of cardiorespiratory motion. To address this need, I developed and evaluated a novel catheter contact-force control device. The compact electromechanical add-on tool monitors catheter-tissue contact force in real-time and simultaneously adjusts the position of a force-sensing ablation catheter within a steerable sheath to compensate for the change in contact force. In a series of in vitro and in vivo experiments, the contact-force control device demonstrated an ability to: a) maintain an average force to within 1 gram of a set level; b) reduce contact-force variation to below 5 grams (2-8-fold improvement over manual catheter intervention); c) ensure the catheter tip never lost contact with the tissue and never approached dangerous force levels; and importantly, d) deliver reproducible RF ablation lesions regardless of cardiac tissue motion, which were of the same depth and volume as lesions delivered in the absence of tissue motion. In the second part of the thesis, I describe a novel steerable sheath and catheter robotic navigation system, which incorporates the catheter contact-force controller. The robotic platform enables precise and accurate manipulation of a remote conventional steerable sheath and permits catheter-tissue contact-force control. The robotic navigation system was evaluated in vitro using a phantom that combines stationary and moving targets within an in vitro model representing a beating heart. An electrophysiologist used the robotic system to remotely navigate the sheath and catheter tip to select targets and compared the accuracy of reaching these targets performing the same tasks manually. Robotic intervention resulted in significantly higher accuracy and significantly improved the contact-force profile between the catheter tip and moving tissue-mimicking material. Our studies demonstrate that using available contact-force information within a robotic system can ensure precise and accurate placement of reliably transmural RF ablation lesions. These robotic systems can be valuable tools used to optimize RF lesion delivery techniques and ultimately improve clinical outcomes for AF ablation therapy

Novel linear and nonlinear optical signal processing for ultra-high bandwidth communications

The thesis is articulated around the theme of ultra-wide bandwidth single channel signals. It focuses on the two main topics of transmission and processing of information by techniques compatible with high baudrates. The processing schemes introduced combine new linear and nonlinear optical platforms such as Fourier-domain programmable optical processors and chalcogenide chip waveguides, as well as the concept of neural network. Transmission of data is considered in the context of medium distance links of Optical Time Division Multiplexed (OTDM) data subject to environmental fluctuations. We experimentally demonstrate simultaneous compensation of differential group delay and multiple orders of dispersion at symbol rates of 640 Gbaud and 1.28 Tbaud. Signal processing at high bandwidth is envisaged both in the case of elementary post-transmission analog error mitigation and in the broader field of optical computing for high level operations (“optical processor”). A key innovation is the introduction of a novel four-wave mixing scheme implementing a dot-product operation between wavelength multiplexed channels. In particular, it is demonstrated for low-latency hash-key based all-optical error detection in links encoded with advanced modulation formats. Finally, the work presents groundbreaking concepts for compact implementation of an optical neural network as a programmable multi-purpose processor. The experimental architecture can implement neural networks with several nodes on a single optical nonlinear transfer function implementing functions such as analog-to-digital conversion. The particularity of the thesis is the new approaches to optical signal processing that potentially enable high level operations using simple optical hardware and limited cascading of components

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications