Power Management ICs for Internet of Things, Energy Harvesting and Biomedical Devices

This dissertation focuses on the power management unit (PMU) and integrated circuits (ICs) for the internet of things (IoT), energy harvesting and biomedical devices. Three monolithic power harvesting methods are studied for different challenges of smart nodes of IoT networks. Firstly, we propose that an impedance tuning approach is implemented with a capacitor value modulation to eliminate the quiescent power consumption. Secondly, we develop a hill-climbing MPPT mechanism that reuses and processes the information of the hysteresis controller in the time-domain and is free of power hungry analog circuits. Furthermore, the typical power-performance tradeoff of the hysteresis controller is solved by a self-triggered one-shot mechanism. Thus, the output regulation achieves high-performance and yet low-power operations as low as 12 µW. Thirdly, we introduce a reconfigurable charge pump to provide the hybrid conversion ratios (CRs) as 1⅓× up to 8× for minimizing the charge redistribution loss. The reconfigurable feature also dynamically tunes to maximum power point tracking (MPPT) with the frequency modulation, resulting in a two-dimensional MPPT. Therefore, the voltage conversion efficiency (VCE) and the power conversion efficiency (PCE) are enhanced and flattened across a wide harvesting range as 0.45 to 3 V. In a conclusion, we successfully develop an energy harvesting method for the IoT smart nodes with lower cost, smaller size, higher conversion efficiency, and better applicability. For the biomedical devices, this dissertation presents a novel cost-effective automatic resonance tracking method with maximum power transfer (MPT) for piezoelectric transducers (PT). The proposed tracking method is based on a band-pass filter (BPF) oscillator, exploiting the PT’s intrinsic resonance point through a sensing bridge. It guarantees automatic resonance tracking and maximum electrical power converted into mechanical motion regardless of process variations and environmental interferences. Thus, the proposed BPF oscillator-based scheme was designed for an ultrasonic vessel sealing and dissecting (UVSD) system. The sealing and dissecting functions were verified experimentally in chicken tissue and glycerin. Furthermore, a combined sensing scheme circuit allows multiple surgical tissue debulking, vessel sealer and dissector (VSD) technologies to operate from the same sensing scheme board. Its advantage is that a single driver controller could be used for both systems simplifying the complexity and design cost. In a conclusion, we successfully develop an ultrasonic scalpel to replace the other electrosurgical counterparts and the conventional scalpels with lower cost and better functionality

Energy management techniques for ultra-small bio-medical implants

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 167-174).Trends in the medical industry have created a growing demand for implantable medical devices. In particular, the need to provide medical professionals a means to continuously monitor bio-markers over long time scales with increased precision is paramount to efficient healthcare. To make medical implants more attractive, there is a need to reduce their size and power consumption. Small medical implants would allow for less invasive procedures and greater comfort for patients. The two primary limitations to the size of small medical implants are the batteries that provide energy to circuit and sensor components, and the antennas that enable wireless communication to terminals outside of the body. In this work we present energy management and low-power techniques to help solve the engineering challenges posed by using ultracapacitors for energy storage. A major problem with using any capacitor as an energy source is the fact that its voltage drops rapidly with decreasing charge. This leaves the circuit to cope with a large supply variation and can lead to energy being left on the capacitor when its voltage gets too low to supply a sufficient supply voltage for operation. Rather than use a single ultracapacitor, we demonstrate higher energy utilization by splitting a single capacitor into an array of capacitors that are progressively reconfigured as energy is drawn out. An energy management IC fabricated in 180-nm CMOS implements a stacking procedure that allows for more than 98% of the initial energy stored in the ultracapacitors to be removed before the output voltage drops unsuitably low for circuit operation. The second part of this work develops techniques for wide-input-range energy management. The first chip implementing stacking suffered an efficiency penalty by using a switchedcapacitor voltage regulator with only a single conversion ratio. In a second implementation, we introduce a better solution that preserves efficiency performance by using a multiple conversion ratio switched-capacitor voltage regulator. At any given input voltage from an ultracapcitor array, the switched-capacitor voltage regulator is configured to maximize efficiency. Fabricated in a 180-nm CMOS process, the chip achieves a peak efficiency of 90% and the efficiency does not fall below 70% for input voltages between 1.25 and 3 V.by William R. Sanchez.Ph.D

Development of a Flexible FPGA-Based Platform for Flight Control System Research

This work is part of ongoing research conducted at Virginia Commonwealth University relating to unmanned aerial vehicles. The primary objective of this thesis was to develop a flexible, high-performance autopilot platform in order to facilitate research on advanced flight control algorithms. A dual FPGA-based system architecture utilizing a stacked, multi-board design was created to meet this goal. Processing tasks were split between the two FPGA devices, allowing for improved system timing and increased throughput. A combination of analog and digital filtering techniques were employed in the new system, resulting in enhanced sensor accuracy and precision compared to the previous generation autopilot system. Several important improvements to the safety and reliability of the overall system were also achieved

Energy-efficient analog-to-digital conversion for ultra-wideband radio

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 207-222).In energy constrained signal processing and communication systems, a focus on the analog or digital circuits in isolation cannot achieve the minimum power consumption. Furthermore, in advanced technologies with significant variation, yield is traditionally achieved only through conservative design and a sacrifice of energy efficiency. In this thesis, these limitations are addressed with both a comprehensive mixed-signal design methodology and new circuits and architectures, as presented in the context of an analog-to-digital converter (ADC) for ultra-wideband (UWB) radio. UWB is an emerging technology capable of high-data-rate wireless communication and precise locationing, and it requires high-speed (>500MS/s), low-resolution ADCs. The successive approximation register (SAR) topology exhibits significantly reduced complexity compared to the traditional flash architecture. Three time-interleaved SAR ADCs have been implemented. At the mixed-signal optimum energy point, parallelism and reduced voltage supplies provide more than 3x energy savings. Custom control logic, a new capacitive DAC, and a hierarchical sampling network enable the high-speed operation. Finally, only a small amount of redundancy, with negligible power penalty, dramatically improves the yield of the highly parallel ADC in deep sub-micron CMOS.by Brian P. Ginsburg.Ph.D

Medical semiconductor sensors: a market perspective on state-of-the-art solutions and trends

The aim of this Master Thesis is to analyse the worldwide state-of-the art market solutions and trends in semiconductor sensors within medical applications; specially magnetic and pressure sensors, with the intention of developing a potential entry plan of Infineon Technologies AG into this market. For that purpose, a fit between a top-down and bottom-up qualitative and quantitative estimation of the medical semiconductor sensor’s market size has been made; with application units, sensor volumes and sensor revenues, with a horizontal scope of five years. Once understood the existing market, some insight into the competitive landscape is provided, where the key suppliers are analysed in terms of product portfolio and revenue share estimates, on an application basis. And also, a spotlight on innovation and trends at three levels – healthcare, medical devices and medical semiconductor sensors – is presented, to forecast a possible evolution of the fore-mentioned market. The research that has been conducted is based on three main sources of information; internal contacts (i.e. within Infineon), external contacts (most of them through internal references) and internet research. Access to market research company’s reports and interviews has been particularly helpful, to complement extensive internet research. Outcomes of this study indicate that the global medical semiconductor magnetic sensor market reveals low revenue potential; as most of the applications are yet innovation fields. Reed switch replacement in battery-powered medical devices can be an opportunity for magnetic switches. However, this project suggests that there is a key investment opportunity: magnetic beads for viral detection with spintronics sensors. The global medical semiconductor pressure sensor market seems a fairly mature market; the gross part of the revenue comes from blood pressure measurement. Blood pressure measurement might be an opportunity for existing automotive semiconductor pressure sensor products. Furthermore, this report suggests that the future of blood pressure measurement might tend towards implantable pressure sensors, with a non-significantly different technological basis. To conclude, this report unveils certain business opportunities for Infineon’s semiconductor magnetic and pressure sensor products; and puts special focus on the development of derivative products to pioneer the commercialization of innovative medical applications, with a forecasted huge revenue potential

Miniaturized, low-voltage power converters with fast dynamic response

Thesis (Ph. D.)--Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 216-224).This thesis introduces a two-stage architecture that combines the strengths of switched capacitor (SC) techniques (small size, light-load performance) with the high efficiency and regulation capability of switch-mode power converters. The resulting designs have a superior efficient-power density trade-off over traditional designs. These power converters can provide numerous lowvoltage outputs over a wide input voltage range with a very fast dynamic response, which are ideal for powering logic devices in the mobile and high-performance computing markets. Both design and fabrication considerations for power converters using this architecture are addressed. The results are demonstrated in a 2.4 W dc-dc converter implemented in a 180 nm CMOS IC process and co-packaged with its passive components for high-performance. The converter operates from an input voltage of 2.7 V to 5.5 V with an output voltage of /= 80% efficiency.by David Giuliano.Ph.D

Architectures and circuits for low-voltage energy conversion and applications in renewable energy and power management

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 337-343).In this thesis we seek to develop smaller, less expensive, and more efficient power electronics. We also investigate emerging applications where the proper implementation of these new types of power converters can have a significant impact on the overall system performance. We have developed a new two-stage dc-dc converter architecture suitable for low-voltage CMOS power delivery. The architecture, which combines the benefits of switched-capacitor and inductor-based converters, achieves both large voltage step-down and high switching frequency, while maintaining good efficiency. We explore the benefits of a new soft-charging technique that drastically reduces the major loss mechanism in switched-capacitor converters, and we show experimental results from a 5-to-1 V, 0.8 W integrated dc-dc converter developed in 180 nm CMOS technology. The use of power electronics to increase system performance in a portable thermophotovoltaic power generator is also investigated in this thesis. We show that mechanical non-idealities in a MEMS fabricated energy conversion device can be mitigated with the help of low-voltage distributed maximum power point tracking (MPPT) dc-dc converters. As part of this work, we explore low power control and sensing architectures, and present experimental results of a 300 mW integrated MPPT developed in 0.35 um CMOS with all power, sensing and control circuitry on chip. The final piece of this thesis investigates the implementation of distributed power electronics in solar photovoltaic applications. We explore the benefits of small, intelligent power converters integrated directly into the solar panel junction box to enhance overall energy capture in real-world scenarios. To this end, we developed a low-cost, high efficiency (>98%) power converter that enables intelligent control and energy conversion at the sub-panel level. Experimental field measurements show that the solution can provide up to a 35% increase in panel output power during partial shading conditions compared to current state-of-the-art solutions.by Robert C. N. Pilawa-Podgurski.Ph.D

Acquisition systems and decoding algorithms of peripheral neural signals for prosthetic applications

During the years, neuroprosthetic applications have obtained a great deal of attention by the international research, especially in the bioengineering field, thanks to the huge investments on several proposed projects funded by the political institutions which consider the treatment of this particular disease of fundamental importance for the global community. The aim of these projects is to find a possible solution to restore the functionalities lost by a patient subjected to an upper limb amputation trying to develop, according to physiological considerations, a communication link between the brain in which the significant signals are generated and a motor prosthesis device able to perform the desired action. Moreover, the designed system must be able to give back to the brain a sensory feedback about the surrounding world in terms of pressure or temperature acquired by tactile biosensors placed at the surface of the cybernetic hand. It in fact allows to execute involuntarymovements when for example the armcomes in contact with hot objects. The development of such a closed-loop architecture involves the need to address some critical issues which depend on the chosen approach. Several solutions have been proposed by the researches of the field, each one differing with respect to where the neural signals are acquired, either at the central nervous systemor at the peripheral one,most of themfollowing the former even that the latter is always considered by the amputees amore natural way to handle the artificial limb. This research work is based on the use of intrafascicular electrodes directly implanted in the residual peripheral nerves of the stump which represents a good compromise choice in terms of invasiveness and selectivity extracting electroneurographic (ENG) signals from which it is possible to identify the significant activity of a quite limited number of neuronal cells. In the perspective of the hardware implementation of the resulting solution which can work autonomously without any intervention by the amputee in an adaptive way according to the current characteristics of the processed signal and by using batteries as power source allowing portability, it is necessary to fulfill the tight constraints imposed by the application under consideration involved in each of the various phases which compose the considered closed-loop system. Regarding to the recording phase, the implementation must be able to remove the unwanted interferences mainly due to the electro-stimulations of themuscles placed near the electrodes featured by an order of magnitude much greater in comparison to that of the signals of interest amplifying the frequency components belonging to the significant bandwidth, and to convert them with a high resolution in order to obtain good performance at the next processing phases. To this aim, a recording module for peripheral neural signals will be presented, based on the use of a sigma-delta architecture which is composed by two main parts: an analog front-end stage for neural signal acquisition, pre-filtering and sigma-delta modulation and a digital unit for sigma-delta decimation and system configuration. Hardware/software cosimulations exploiting the Xilinx System Generator tool in Matlab Simulink environment and then transistor-level simulations confirmed that the system is capable of recording neural signals in the order of magnitude of tens of μV rejecting the huge low-frequency noise due to electromyographic interferences. The same architecture has been then exploited to implement a prototype of an 8-channel implantable electronic bi-directional interface between the peripheral nervous system and the neuro-controlled hand prosthesis. The solution includes a custom designed Integrated Circuit (0.35μm CMOS technology), responsible of the signal pre-filtering and sigma-delta modulation for each channel and the neural stimuli generation (in the opposite path) based on the directives sent by a digital control systemmapped on a low-cost Xilinx FPGA Spartan-3E 1600 development board which also involves the multi-channel sigma-delta decimation with a high-order band-pass filter as first stage in order to totally remove the unwanted interferences. In this way, the analog chip can be implanted near the electrodes thanks to its limited size avoiding to add a huge noise to theweak neural signals due to longwires connections and to cause heat-related infections, shifting the complexity to the digital part which can be hosted on a separated device in the stump of the amputeewithout using complex laboratory instrumentations. The system has been successfully tested from the electrical point of view and with in-vivo experiments exposing good results in terms of output resolution and noise rejection even in case of critical conditions. The various output channels at the Nyquist sampling frequency coming from the acquisition system must be processed in order to decode the intentions of movements of the amputee, applying the correspondent electro-mechanical stimulation in input to the cybernetic hand in order to perform the desired motor action. Different decoding approaches have been presented in the past, the majority of them were conceived starting from the relative implementation and performance evaluation of their off-line version. At the end of the research, it is necessary to develop these solutions on embedded systems performing an online processing of the peripheral neural signals. However, it is often possible only by using complex hardware platforms clocked at very high operating frequencies which are not be compliant with the low-power requirements needed to allow portability for the prosthetic device. At present, in fact, the important aspect of the real-time implementation of sophisticated signal processing algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited resources of the former may have on the efficiency/effectiveness of any given algorithm. In this research work it has been addressed the optimization of a state-of-the-art algorithmfor PNS signals decoding that is a step forward for its real-time, full implementation onto a floating-point Digital Signal Processor (DSP). Beyond low-level optimizations, different solutions have been proposed at an high level in order to find the best trade-off in terms of effectiveness/efficiency. A latency model, obtained through cycle accurate profiling of the different code sections, has been drawn in order to perform a fair performance assessment. The proposed optimized real-time algorithmachieves up to 96% of correct classification on real PNS signals acquired through tf-LIFE electrodes on animals, and performs as the best off-line algorithmfor spike clustering on a synthetic cortical dataset characterized by a reasonable dissimilarity between the spikemorphologies of different neurons. When the real-time requirements are joined to the fulfilment of area and power minimization for implantable/portable applications, such as for the target neuroprosthetic devices, only custom VLSI implementations can be adopted. In this case, every part of the algorithmshould be carefully tuned. To this aim, the first preprocessing stage of the decoding algorithmbased on the use of aWavelet Denoising solution able to remove also the in-band noise sources has been deeply analysed in order to obtain an optimal hardware implementation. In particular, the usually overlooked part related to threshold estimation has been evaluated in terms of required hardware resources and functionality, exploiting the commercial Xilinx System Generator tool for the design of the architecture and the co-simulation. The analysis has revealed how the widely used Median Absolute Deviation (MAD) could lead o hardware implementations highly inefficient compared to other dispersion estimators demonstrating better scalability, relatively to the specific application. Finally, two different hardware implementations of the reference decoding algorithm have been presented highlighting pros and cons of each one of them. Firstly, a novel approach based on high-level dataflow description and automatic hardware generation is presented and evaluated on the on-line template-matching spike sorting algorithmwhich represents the most complex processing stage. It starts from the identification of the single kernels with the greater computational complexity and using their dataflow description to generate the HDL implementation of a coarse-grained reconfigurable global kernel characterized by theminimumresources in order to reduce the area and the energy dissipation for the fulfilment of the low-power requirements imposed by the application. Results in the best case have revealed a 71%of area saving compared tomore traditional solutions,without any accuracy penalty. With respect to single kernels execution, better latency performance are achievable stillminimizing the number of adopted resources. The performance in terms of latency can also be improved by tuning the implemented parallelismin the light of a defined number of channels and real-time constraints, by using more than one reconfigurable global kernel in order that they can be exploited to perform the same or different kernels at the same time in a parallel way, due to the fact that each one can execute the relative processing only in a sequential way. For this reason, a second FPGA-based prototype has been proposed based on the use of aMulti-Processor System-on-Chip (MPSoC) embedded architecture. This prototype is capable of respecting the real-time constraints posed by the application when clocked at less than 50 MHz, in comparison to 300 MHz of the previous DSP implementation. Considering that the application workload is extremely data dependent and unpredictable due to the sparsity of the neural signals, the architecture has to be dimensioned taking into account critical worst-case operating conditions in order to always ensure the correct functionality. To compensate the resulting overprovisioning of the system architecture, a software-controllable power management based on the use of clock gating techniques has been integrated in order tominimize the dynamic power consumption of the resulting solution. Summarizing, this research work can be considered a sort of proof-of-concept for the proposed techniques considering all the design issues which characterize each stage of the closed-loop system in the perspective of a portable low-power real-time hardware implementation of the neuro-controlled prosthetic device

Acquisition systems and decoding algorithms of peripheral neural signals for prosthetic applications

During the years, neuroprosthetic applications have obtained a great deal of attention by the international research, especially in the bioengineering field, thanks to the huge investments on several proposed projects funded by the political institutions which consider the treatment of this particular disease of fundamental importance for the global community. The aim of these projects is to find a possible solution to restore the functionalities lost by a patient subjected to an upper limb amputation trying to develop, according to physiological considerations, a communication link between the brain in which the significant signals are generated and a motor prosthesis device able to perform the desired action. Moreover, the designed system must be able to give back to the brain a sensory feedback about the surrounding world in terms of pressure or temperature acquired by tactile biosensors placed at the surface of the cybernetic hand. It in fact allows to execute involuntarymovements when for example the armcomes in contact with hot objects. The development of such a closed-loop architecture involves the need to address some critical issues which depend on the chosen approach. Several solutions have been proposed by the researches of the field, each one differing with respect to where the neural signals are acquired, either at the central nervous systemor at the peripheral one,most of themfollowing the former even that the latter is always considered by the amputees amore natural way to handle the artificial limb. This research work is based on the use of intrafascicular electrodes directly implanted in the residual peripheral nerves of the stump which represents a good compromise choice in terms of invasiveness and selectivity extracting electroneurographic (ENG) signals from which it is possible to identify the significant activity of a quite limited number of neuronal cells. In the perspective of the hardware implementation of the resulting solution which can work autonomously without any intervention by the amputee in an adaptive way according to the current characteristics of the processed signal and by using batteries as power source allowing portability, it is necessary to fulfill the tight constraints imposed by the application under consideration involved in each of the various phases which compose the considered closed-loop system. Regarding to the recording phase, the implementation must be able to remove the unwanted interferences mainly due to the electro-stimulations of themuscles placed near the electrodes featured by an order of magnitude much greater in comparison to that of the signals of interest amplifying the frequency components belonging to the significant bandwidth, and to convert them with a high resolution in order to obtain good performance at the next processing phases. To this aim, a recording module for peripheral neural signals will be presented, based on the use of a sigma-delta architecture which is composed by two main parts: an analog front-end stage for neural signal acquisition, pre-filtering and sigma-delta modulation and a digital unit for sigma-delta decimation and system configuration. Hardware/software cosimulations exploiting the Xilinx System Generator tool in Matlab Simulink environment and then transistor-level simulations confirmed that the system is capable of recording neural signals in the order of magnitude of tens of μV rejecting the huge low-frequency noise due to electromyographic interferences. The same architecture has been then exploited to implement a prototype of an 8-channel implantable electronic bi-directional interface between the peripheral nervous system and the neuro-controlled hand prosthesis. The solution includes a custom designed Integrated Circuit (0.35μm CMOS technology), responsible of the signal pre-filtering and sigma-delta modulation for each channel and the neural stimuli generation (in the opposite path) based on the directives sent by a digital control systemmapped on a low-cost Xilinx FPGA Spartan-3E 1600 development board which also involves the multi-channel sigma-delta decimation with a high-order band-pass filter as first stage in order to totally remove the unwanted interferences. In this way, the analog chip can be implanted near the electrodes thanks to its limited size avoiding to add a huge noise to theweak neural signals due to longwires connections and to cause heat-related infections, shifting the complexity to the digital part which can be hosted on a separated device in the stump of the amputeewithout using complex laboratory instrumentations. The system has been successfully tested from the electrical point of view and with in-vivo experiments exposing good results in terms of output resolution and noise rejection even in case of critical conditions. The various output channels at the Nyquist sampling frequency coming from the acquisition system must be processed in order to decode the intentions of movements of the amputee, applying the correspondent electro-mechanical stimulation in input to the cybernetic hand in order to perform the desired motor action. Different decoding approaches have been presented in the past, the majority of them were conceived starting from the relative implementation and performance evaluation of their off-line version. At the end of the research, it is necessary to develop these solutions on embedded systems performing an online processing of the peripheral neural signals. However, it is often possible only by using complex hardware platforms clocked at very high operating frequencies which are not be compliant with the low-power requirements needed to allow portability for the prosthetic device. At present, in fact, the important aspect of the real-time implementation of sophisticated signal processing algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited resources of the former may have on the efficiency/effectiveness of any given algorithm. In this research work it has been addressed the optimization of a state-of-the-art algorithmfor PNS signals decoding that is a step forward for its real-time, full implementation onto a floating-point Digital Signal Processor (DSP). Beyond low-level optimizations, different solutions have been proposed at an high level in order to find the best trade-off in terms of effectiveness/efficiency. A latency model, obtained through cycle accurate profiling of the different code sections, has been drawn in order to perform a fair performance assessment. The proposed optimized real-time algorithmachieves up to 96% of correct classification on real PNS signals acquired through tf-LIFE electrodes on animals, and performs as the best off-line algorithmfor spike clustering on a synthetic cortical dataset characterized by a reasonable dissimilarity between the spikemorphologies of different neurons. When the real-time requirements are joined to the fulfilment of area and power minimization for implantable/portable applications, such as for the target neuroprosthetic devices, only custom VLSI implementations can be adopted. In this case, every part of the algorithmshould be carefully tuned. To this aim, the first preprocessing stage of the decoding algorithmbased on the use of aWavelet Denoising solution able to remove also the in-band noise sources has been deeply analysed in order to obtain an optimal hardware implementation. In particular, the usually overlooked part related to threshold estimation has been evaluated in terms of required hardware resources and functionality, exploiting the commercial Xilinx System Generator tool for the design of the architecture and the co-simulation. The analysis has revealed how the widely used Median Absolute Deviation (MAD) could lead o hardware implementations highly inefficient compared to other dispersion estimators demonstrating better scalability, relatively to the specific application. Finally, two different hardware implementations of the reference decoding algorithm have been presented highlighting pros and cons of each one of them. Firstly, a novel approach based on high-level dataflow description and automatic hardware generation is presented and evaluated on the on-line template-matching spike sorting algorithmwhich represents the most complex processing stage. It starts from the identification of the single kernels with the greater computational complexity and using their dataflow description to generate the HDL implementation of a coarse-grained reconfigurable global kernel characterized by theminimumresources in order to reduce the area and the energy dissipation for the fulfilment of the low-power requirements imposed by the application. Results in the best case have revealed a 71%of area saving compared tomore traditional solutions,without any accuracy penalty. With respect to single kernels execution, better latency performance are achievable stillminimizing the number of adopted resources. The performance in terms of latency can also be improved by tuning the implemented parallelismin the light of a defined number of channels and real-time constraints, by using more than one reconfigurable global kernel in order that they can be exploited to perform the same or different kernels at the same time in a parallel way, due to the fact that each one can execute the relative processing only in a sequential way. For this reason, a second FPGA-based prototype has been proposed based on the use of aMulti-Processor System-on-Chip (MPSoC) embedded architecture. This prototype is capable of respecting the real-time constraints posed by the application when clocked at less than 50 MHz, in comparison to 300 MHz of the previous DSP implementation. Considering that the application workload is extremely data dependent and unpredictable due to the sparsity of the neural signals, the architecture has to be dimensioned taking into account critical worst-case operating conditions in order to always ensure the correct functionality. To compensate the resulting overprovisioning of the system architecture, a software-controllable power management based on the use of clock gating techniques has been integrated in order tominimize the dynamic power consumption of the resulting solution. Summarizing, this research work can be considered a sort of proof-of-concept for the proposed techniques considering all the design issues which characterize each stage of the closed-loop system in the perspective of a portable low-power real-time hardware implementation of the neuro-controlled prosthetic device

Crypto-processeur architecture, programmation et évaluation de la sécurité

Les architectures des processeurs et coprocesseurs cryptographiques se montrent fréquemment vulnérables aux différents types d attaques ; en particulier, celles qui ciblent une révélation des clés chiffrées. Il est bien connu qu une manipulation des clés confidentielles comme des données standards par un processeur peut être considérée comme une menace. Ceci a lieu par exemple lors d un changement du code logiciel (malintentionné ou involontaire) qui peut provoquer que la clé confidentielle sorte en clair de la zone sécurisée. En conséquence, la sécurité de tout le système serait irréparablement menacée. L objectif que nous nous sommes fixé dans le travail présenté, était la recherche d architectures matérielles reconfigurables qui peuvent fournir une sécurité élevée des clés confidentielles pendant leur génération, leur enregistrement et leur échanges en implantant des modes cryptographiques de clés symétriques et des protocoles. La première partie de ce travail est destinée à introduire les connaissances de base de la cryptographie appliquée ainsi que de l électronique pour assurer une bonne compréhension des chapitres suivants. Deuxièmement, nous présentons un état de l art des menaces sur la confidentialité des clés secrètes dans le cas où ces dernières sont stockées et traitées dans un système embarqué. Pour lutter contre les menaces mentionnées, nous proposons alors de nouvelles règles au niveau du design de l architecture qui peuvent augmenter la résistance des processeurs et coprocesseurs cryptographiques contre les attaques logicielles. Ces règles prévoient une séparation des registres dédiés à l enregistrement de clés et ceux dédiés à l enregistrement de données : nous proposons de diviser le système en zones : de données, du chiffreur et des clés et à isoler ces zones les unes des autres au niveau du protocole, du système, de l architecture et au niveau physique. Ensuite, nous présentons un nouveau crypto-processeur intitulé HCrypt, qui intègre ces règles de séparation et qui assure ainsi une gestion sécurisée des clés. Mises à part les instructions relatives à la gestion sécurisée de clés, quelques instructions supplémentaires sont dédiées à une réalisation simple des modes de chiffrement et des protocoles cryptographiques. Dans les chapitres suivants, nous explicitons le fait que les règles de séparation suggérées, peuvent également être étendues à l architecture d un processeur généraliste et coprocesseur. Nous proposons ainsi un crypto-coprocesseur sécurisé qui est en mesure d être utilisé en relation avec d autres processeurs généralistes. Afin de démontrer sa flexibilité, le crypto-coprocesseur est interconnecté avec les processeurs soft-cores de NIOS II, de MicroBlaze et de Cortex M1. Par la suite, la résistance du crypto-processeur par rapport aux attaques DPA est testée. Sur la base de ces analyses, l architecture du processeur HCrypt est modifiée afin de simplifier sa protection contre les attaques par canaux cachés (SCA) et les attaques par injection de fautes (FIA). Nous expliquons aussi le fait qu une réorganisation des blocs au niveau macroarchitecture du processeur HCrypt, augmente la résistance du nouveau processeur HCrypt2 par rapport aux attaques de type DPA et FIA. Nous étudions ensuite les possibilités pour pouvoir reconfigurer dynamiquement les parties sélectionnées de l architecture du processeur crypto-coprocesseur. La reconfiguration dynamique peut être très utile lorsque l algorithme de chiffrement ou ses implantations doivent être changés en raison de l apparition d une vulnérabilité Finalement, la dernière partie de ces travaux de thèse, est destinée à l exécution des tests de fonctionnalité et des optimisations stricts des deux versions du cryptoprocesseur HCryptArchitectures of cryptographic processors and coprocessors are often vulnerable to different kinds of attacks, especially those targeting the disclosure of encryption keys. It is well known that manipulating confidential keys by the processor as ordinary data can represent a threat: a change in the program code (malicious or unintentional) can cause the unencrypted confidential key to leave the security area. This way, the security of the whole system would be irrecoverably compromised. The aim of our work was to search for flexible and reconfigurable hardware architectures, which can provide high security of confidential keys during their generation, storage and exchange while implementing common symmetric key cryptographic modes and protocols. In the first part of the manuscript, we introduce the bases of applied cryptography and of reconfigurable computing that are necessary for better understanding of the work. Second, we present threats to security of confidential keys when stored and processed within an embedded system. To counteract these threats, novel design rules increasing robustness of cryptographic processors and coprocessors against software attacks are presented. The rules suggest separating registers dedicated to key storage from those dedicated to data storage: we propose to partition the system into the data, cipher and key zone and to isolate the zones from each other at protocol, system, architectural and physical levels. Next, we present a novel HCrypt crypto-processor complying with the separation rules and thus ensuring secure key management. Besides instructions dedicated to secure key management, some additional instructions are dedicated to easy realization of block cipher modes and cryptographic protocols in general. In the next part of the manuscript, we show that the proposed separation principles can be extended also to a processor-coprocessor architecture. We propose a secure crypto-coprocessor, which can be used in conjunction with any general-purpose processor. To demonstrate its flexibility, the crypto-coprocessor is interconnected with the NIOS II, MicroBlaze and Cortex M1 soft-core processors. In the following part of the work, we examine the resistance of the HCrypt cryptoprocessor to differential power analysis (DPA) attacks. Following this analysis, we modify the architecture of the HCrypt processor in order to simplify its protection against side channel attacks (SCA) and fault injection attacks (FIA). We show that by rearranging blocks of the HCrypt processor at macroarchitecture level, the new HCrypt2 processor becomes natively more robust to DPA and FIA. Next, we study possibilities of dynamically reconfiguring selected parts of the processor - crypto-coprocessor architecture. The dynamic reconfiguration feature can be very useful when the cipher algorithm or its implementation must be changed in response to appearance of some vulnerability. Finally, the last part of the manuscript is dedicated to thorough testing and optimizations of both versions of the HCrypt crypto-processor. Architectures of crypto-processors and crypto-coprocessors are often vulnerable to software attacks targeting the disclosure of encryption keys. The thesis introduces separation rules enabling crypto-processor/coprocessors to support secure key management. Separation rules are implemented on novel HCrypt crypto-processor resistant to software attacks targetting the disclosure of encryption keysST ETIENNE-Bib. électronique (422189901) / SudocSudocFranceF