Publicaciones del IMSE

Publicaciones recientes

Band-Pass Sigma-Delta Modulation: The Path towards RF-to-Digital Conversion in Software-Defined Radio
J.M. de la Rosa
Journal Paper · Chips, vol. 2 no. 1, articles 44-69, 2023
MDPI    ISSN: 2674-0729
resumen      doi      

This paper reviews the state of the art on bandpass sigma-delta modulators (BP-sigma-deltaMs) intended to digitize radio frequency (RF) signals. A priori, this is the most direct way to implement software-defined radio (SDR) systems since the analog/digital interface is placed closer to the antenna, thus reducing the analog circuitry and doing most of the signal processing in the digital domain. In spite of their higher programmability and scalability, RF BP-sigma-deltaM analog-to-digital converters (ADCs) require more energy to operate in the GHz range as compared with their low-pass (LP) counterparts. This makes conventional direct conversion receivers (DCRs) the commonplace approach due to their overall smaller energy consumption. This paper surveys some circuits and systems techniques which can make RF ADCs and SDR-based transceivers more efficient and feasible to be embedded in mobile terminals.

Ultra-High-Resistance Pseudo-Resistors with Small Variations in a Wide Symmetrical Input Voltage Swing
F. Karami-Horestani and J.M. de la Rosa
Journal Paper · IEEE Transactions on Circuits and Systems II: Express Briefs
IEEE    ISSN: 1549-7747
resumen      doi      

This paper presents a new strategy and circuit configuration composed of serially-connected PMOS devices operating in the subthreshold region for implementing ultra-highvalue resistors required in very low-frequency active-RC filters and bio-amplifiers. Depending on the application, signal bandwidth for instance in bio-amplifiers may vary from a few mHz up to a maximum of 10 kHz. Three different resistor structures are proposed to achieve ultra-high resistance. While ranging in the order of several TY, the proposed ultra-high-resistance pseudoresistors occupy a small on-chip silicon area, which is one of the main issues in the design of analog front-end circuits in ultra-low power implantable biomedical microsystems. In addition, these ultra-high-value resistors lead to the use of a small capacitance to create a very small cut-off frequency. Therefore, the large area to implement capacitances is also considerably reduced. The proposed resistor structures have very small variations about 7% and 12% in a wide input voltage range (-0.5 V +0.5 V), thus significantly improving the total harmonic distortion of bioamplifiers and the analog front-end of the system. Simulation results of different circuits designed in a 180nm CMOS technology, are shown to demonstrate the advantages of the proposed ultra-high-resistance pseudo-resistors.

A self-powered asynchronous image sensor with independent in-pixel harvesting and sensing operations
R. Gomez-Merchan, J.A. Leñero-Bardallo and A. Rodríguez-Vázquez
Conference · IS&T International Symposium on Electronic Imaging 2023

A self-powered asynchronous sensor with a novel pixel architecture is presented. Pixels are autonomous and can harvest or sense energy independently. During the image acquisition, pixels toggle to a harvesting operation mode once they have sensed their local illumination level. With the proposed pixel architecture, most illuminated pixels provide an early contribution to power the sensor, while low-illuminated ones spend more time sensing their local illumination. Thus, the equivalent frame rate is higher than the one offered by conventional self-powered sensors that harvest and sense illumination in independent phases. The proposed sensor uses a Time-to-First-Spike readout that allows trading between image quality and data and bandwidth consumption. The device has HDR operation with a dynamic range of 80 dB. Pixel power consumption is only 70 pW. The article describes the sensors and pixel’s architectures in detail. Experimental results are provided and discussed. Sensor specifications are benchmarked against the art.

CMOS Front End for Interfacing Spin-Hall Nano-Oscillators for Neuromorphic Computing in the GHz Range
R. Fiorelli, E. Peralias, R. Mendez-Romero, M. Rajabali, A. Kumar, M. Zahedinejad, J. Akerman, F. Moradi, T. Serrano-Gotarredona and B. Linares-Barranco
Journal Paper · Electronics, vol. 12, no. 1, article 230, 2023
MDPI    ISSN: 2079-9292
resumen      doi      

Spin-Hall-effect nano-oscillators are promising beyond the CMOS devices currently available, and can potentially be used to emulate the functioning of neurons in computational neuromorphic systems. As they oscillate in the 4-20 GHz range, they could potentially be used for building highly accelerated neural hardware platforms. However, due to their extremely low signal level and high impedance at their output, as well as their microwave-range operating frequency, discerning whether the SHNO is oscillating or not carries a great challenge when its state read-out circuit is implemented using CMOS technologies. This paper presents the first CMOS front-end read-out circuitry, implemented in 180 nm, working at a SHNO oscillation frequency up to 4.7 GHz, managing to discern SHNO amplitudes of 100 mu V even for an impedance as large as 300 ohm and a noise figure of 5.3 dB(300 ohm). A design flow of this front end is presented, as well as the architecture of each of its blocks. The study of the low-noise amplifier is deepened for its intrinsic difficulties in the design, satisfying the characteristics of SHNOs.

PACOSYT: A Passive Component Synthesis Tool based on Machine Learning and Tailored Modeling Strategies Towards Optimal RF and mm-Wave Circuit Designs
F. Passos, N. Lourenço, E. Roca, R. Martins, R. Castro-López, N. Horta and F.V. Fernández
Journal Paper · IEEE Journal of Microwaves, first online, 2023
IEEE    ISSN: 2692-8388
resumen      doi      

In this paper, the application of regression-based supervised machine learning (ML) methods to the modeling of integrated inductors and transformers is examined. Different ML techniques are used and compared to improve accuracy. However, it is demonstrated that none of the ML techniques considered provided good results unless a smart modeling strategy, tailored to the specific design problem, is used. Taking advantage of these modeling strategies, high accuracy can be obtained when compared to full-wave electromagnetic (EM) simulations (less than 2% error) and experimental measurements (less than 5% error). The most accurate model, obtained by the appropriate combination of an ML technique and modeling strategy, has been integrated into a tool called PACOSYT. The tool uses optimization algorithms to allow the designer to obtain an inductor/transformer with optimal performances in just seconds while keeping the accuracy of EM simulations. Furthermore, the tool provides the passive component S parameter description file for seamless use in circuit simulations. The tool can be used standalone or integrated with design frameworks, like Cadence Virtuoso or AIDASoft, a framework for circuit optimization. To illustrate the different usages of the tool, several passive devices are synthesized, and hundreds of millimeter-wave power amplifiers are synthesized using AIDASoft together with PACOSYT. The tool has been developed using open-source Python frameworks and does not use any closed-source licenses. PACOSYT, which also allows other designers to create their models for different technologies, is made publicly available.

Effect of Device Mismatches in Differential Oscillatory Neural Networks
J. Shamsi, M.J. Avedillo, B. Linares-Barranco and T. Serrano-Gotarredona
Journal Paper · IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 70, no. 2, pp 872-883, 2023
IEEE    ISSN: 1549-8328
resumen      doi      

Analog implementation of Oscillatory Neural Networks (ONNs) has the potential to implement fast and ultra-low-power computing capabilities. One of the drawbacks of analog implementation is component mismatches which cause desynchronization and instability in ONNs. Emerging devices like memristors and VO2are particularly prone to variations. In this paper, we study the effect of component mismatches on the performance of differential ONNs (DONNs). Mismatches were considered in two main blocks: differential oscillatory neurons and synaptic circuits. To measure DONN tolerance to mismatches in each block, performance was evaluated with mismatches being present separately in each block. Memristor-bridge circuits with four memristors were used as the synaptic circuits. The differential oscillatory neurons were based on VO2-devices. The simulation results showed that DONN performance was more vulnerable to mismatches in the components of the differential oscillatory neurons than to mismatches in the synaptic circuits. DONNs were found to tolerate up to 20% mismatches in the memristance of the synaptic circuits. However, mismatches in the differential oscillatory neurons resulted in non-uniformity of the natural frequencies, causing desynchronization and instability. Simulations showed that 0.5% relative standard deviation (RSD) in natural frequencies can reduce DONN performance dramatically. In addition, sensitivity analyses showed that the high threshold voltage of VO2-devices is the most sensitive parameter for frequency non-uniformity and desynchronization.

The diverse meteorology of Jezero crater over the first 250 sols of Perseverance on Mars
J.A. Rodriguez-Manfredi, M. de la Torre Juarez, A. Sanchez-Lavega, R. Hueso, G. Martinez, M.T. Lemmon, C.E. Newman, A. Munguira, M. Hieta, L.K. Tamppari, J. Polkko, D. Toledo, E. Sebastian, M.D. Smith, I. Jaakonaho, M. Genzer, A. de Vicente-Retortillo, D. Viudez-Moreiras, M. Ramos, A. Saiz-Lopez, A. Lepinette, M. Wolff, R.J. Sullivan, J. Gomez-Elvira, V. Apestigue, P.G. Conrad, T. Del Rio-Gaztelurrutia, N. Murdoch, I. Arruego, D. Banfield, J. Boland, A.J. Brown, J. Ceballos, M. Dominguez-Pumar, S. Espejo, A.G. Fairén, R. Ferrandiz, E. Fischer, M. Garcia-Villadangos, S. Gimenez, F. Gomez-Gomez, S.D. Guzewich, A.-M. Harri, J.J. Jimenez, V. Jimenez, T. Makinen, M. Marin, C. Martin, J. Martin-Soler, A. Molina, L. Mora-Sotomayor, S. Navarro, V. Peinado, I. Perez-Grande, J. Pla-Garcia, M. Postigo, O. Prieto-Ballesteros, S.C.R. Rafkin, M.I. Richardson, J. Romeral, C. Romero, H. Savijärvi, J. T. Schofield, J. Torres, R. Urqui, S. Zurita & the MEDA team
Journal Paper · Nature Geoscience, 2023
NATURE    ISSN: 1752-0894
resumen      doi      

NASA’s Perseverance rover’s Mars Environmental Dynamics Analyzer is collecting data at Jezero crater, characterizing the physical processes in the lowest layer of the Martian atmosphere. Here we present measurements from the instrument’s first 250 sols of operation, revealing a spatially and temporally variable meteorology at Jezero. We find that temperature measurements at four heights capture the response of the atmospheric surface layer to multiple phenomena. We observe the transition from a stable night-time thermal inversion to a daytime, highly turbulent convective regime, with large vertical thermal gradients. Measurement of multiple daily optical depths suggests aerosol concentrations are higher in the morning than in the afternoon. Measured wind patterns are driven mainly by local topography, with a small contribution from regional winds. Daily and seasonal variability of relative humidity shows a complex hydrologic cycle. These observations suggest that changes in some local surface properties, such as surface albedo and thermal inertia, play an influential role. On a larger scale, surface pressure measurements show typical signatures of gravity waves and baroclinic eddies in a part of the seasonal cycle previously characterized as low wave activity. These observations, both combined and simultaneous, unveil the diversity of processes driving change on today’s Martian surface at Jezero crater.

True Random Number Generator based on RO-PUF
L.F. Rojas-Muñoz, S. Sánchez-Solano, M.C. Martínez-Rodríguez and P. Brox
Conference · Conference on Design of Circuits and Integrated Circuits DCIS 2022

The implementation of true random number generators is of vital importance to preserve the reliability of cryptographic systems. The lack of entropy can compromise their integrity, affecting the security of the entire chain of applications. Ensuring the effectiveness of a random number generator can be understood as reducing the risk of information loss due to possible attacks by third parties. This paper presents a novel approach for a true random number generator based on a Ring Oscillator- Physical Unclonable Function. Since the principle of operation of physical unclonable functions is based on the physical properties of each device, they can be used for security applications such as device identification, counterfeit prevention and increase the robustness of cryptographic functions. In addition, increasing the versatility of the design to use them as a source of entropy, they can also fulfill tasks such as generation of initialization vectors or nonces and keys for symmetric cryptography. The system incorporates multiple operating configurations, which allows a complete analysis of its performance to adapt it to different application scenarios. The randomness and correct operation of the proposed design have been evaluated online, by incorporating it into a hybrid HW/SW embedded system able to run the official test suite published by the National Institute of Standards and Technology without any need for post-processing. The architecture has been designed for Xilinx Zynq-700 family devices and implemented on the Pynq-Z2 development board.

Accurate Face Recognition on Highly Compressed Samples
A. Khan, J. Fernández-Berni and R. Carmona-Galán
Conference · International Conference on Signal Image Technology and Internet Based Systems SITIS 2022

Compressive sensing is an emerging field for lowdimensional data acquisition. Samples are acquired in the compressed domain and utilized for signal reconstruction or as input features for a classifier. In this work, hardware-aware face recognition using compressed samples was investigated. A linear support vector machine (SVM) classifier was exploited with compressed samples as input features; Faces can be reliably recognized with high average accuracy (up to 99%). To assess the robustness of the proposed scheme, three image datasets covering different facial and illumination conditions were analyzed. Random (binary) and structured (Haar-transform-based) measurement matrices were employed for generating compressed samples. For one of the datasets, Extended Yale B, and using a random binary measurement matrix, the proposed scheme achieved 82% accuracy from as few as 15 compressed samples, which means a 1/20480 sensing ratio. Accuracy and compression are also remarkably high with respect to the state-of-the-art for the other two datasets.

A Facial Authentication System using Post-Quantum-Secure Data Generated on Mobile Devices
P. López-González, R. Arjona, R. Román and I. Baturone
Conference · International Conference on Mobile Computing and Networking MOBICOM 2022

This paper describes a demonstrator of a post-quantum-secure facial authentication system distributed between a mobile device acting as a client and a remote computer acting as an authentication server. Homomorphic encryption based on Classic McEliece, one of the fourth-round candidates of the NIST post-quantum standardization process, is carried out by the client for protecting the biometric data extracted from the users’ faces at enrollment and verification. The remote computer only stores and compares the received protected data, thus preserving user privacy. An Android App and a Graphical User Interface (GUI) were implemented at the client and the server, respectively, to show the system performance in terms of computation and security.
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