Channel characterization for chip-scale wireless communications within computing packages

Wireless Network-on-Chip (WNoC) appears as a promising alternative to conventional interconnect fabrics for chip-scale communications. WNoC takes advantage of an overlaid network composed by a set of millimeter-wave antennas to reduce latency and increase throughput in the communication between cores. Similarly, wireless inter-chip communication has been also proposed to improve the information transfer between processors, memory, and accelerators in multi-chip settings. However, the wireless channel remains largely unknown in both scenarios, especially in the presence of realistic chip packages. This work addresses the issue by accurately modeling flip-chip packages and investigating the propagation both its interior and its surroundings. Through parametric studies, package configurations that minimize path loss are obtained and the trade-offs observed when applying such optimizations are discussed. Single-chip and multi-chip architectures are compared in terms of the path loss exponent, confirming that the amount of bulk silicon found in the pathway between transmitter and receiver is the main determinant of losses.Peer ReviewedPostprint (author's final draft

Energy and relevance-aware adaptive monitoring method for wireless sensor nodes with hard energy constraints

© 2024 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Traditional dynamic energy management methods optimize the energy usage in wireless sensor nodes adjusting their behavior to the operating conditions. However, this comes at the cost of losing the predictability in the operation of the sensor nodes. This loss of predictability is particularly problematic for the battery life, as it determines when the nodes need to be serviced. In this paper, we propose an energy and relevance-aware monitoring method, which leverages the principles of self-awareness to address this challenge. On one hand, the relevance-aware behavior optimizes how the monitoring efforts are allocated to maximize the monitoring accuracy; while on the other hand, the power-aware behavior adjusts the overall energy consumption of the node to achieve the target battery life. The proposed method is able to balance both behaviors so as to achieve the target battery life, at the same time is able to exploit variations in the collected data to maximize the monitoring accuracy. Furthermore, the proposed method coordinates two different adaptive schemes, a dynamic sampling period scheme, and a dual prediction scheme, to adjust the behavior of the sensor node. The evaluation results show that the proposed method consistently meets its battery lifetime goal, even when the operating conditions are artificially changed, and is able to improve the mean square error of the collected signal by up to 20% with respect to the same method with the relevance-aware behavior disabled, and of up to 16% with respect the same algorithm with just the adaptive sampling period or the dual prediction scheme enabled. Consequently showing the ability of the proposed method of making appropriate decisions to balance the competing interest of its two behaviors and coordinate the two adaptive schemes to improve their performance.This study was supported by the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR 2019 DI 075 to David Arnaiz). The founder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer ReviewedPostprint (published version

On anomaly-aware structural health monitoring at the extreme edge

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Self-awareness has been successfully utilized to create adaptive behaviors in wireless sensor nodes. However, its adoption can be daunting in scenarios, such as structural health monitoring, where the monitored environment is too complex for it to be accurately modeled by a sensor node. This article addresses this challenge by proposing a novel and lightweight anomaly-aware monitoring method for structural health monitoring that can be directly executed by a sensor node. Instead of modeling the complete structure, the proposed anomaly-aware monitoring method uses the vibration measurements of the sensor node to identify local deviations in the dynamic response of the monitored structure. The self-awareness module can then use this information to guide the dynamic behavior of the sensor node, replacing more resource-intensive structural models. We use data from multiple public benchmark structures to evaluate different features and propose an unsupervised feature selection method. Additionally, we evaluate different anomaly detection algorithms comparing their ability to detect local structural damages, also taking into account their memory and energy cost. The proposed method has been implemented in a commercial sensor node, and deployed in a scaled structure where various damage scenarios were simulated to validate the proposed method, where it was able to successfully detect the presence of damages in over 88% of the cases. Finally, we showcase how the proposed method can enhance self-awareness through the use of a simulation, where the proposed monitoring method was able to extend the battery life of the sensor node by over 59%, without impacting the node’s ability to swiftly detect damages in the structure.This work was supported in part by the Industrial Doctorate Plan of the Department of Research and Universities of the Generalitat de Catalunya. The work of David Arnaiz was supported by Agència de Gestió d’Ajuts Universitaris de Recerca under Grant AGAUR 2019 DI 075.Peer ReviewedPostprint (published version

Millimeter-wave propagation within a computer chip package

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Wireless Network-on-Chip (WNoC) appears as a promising alternative to conventional interconnect fabrics for chip-scale communications. The WNoC paradigm has been extensively analyzed from the physical, network and architecture perspectives assuming mmWave band operation. However, there has not been a comprehensive study at this band for realistic chip packages and, thus, the characteristics of such wireless channel remain not fully understood. This work addresses this issue by accurately modeling a flip-chip package and investigating the wave propagation inside it. Through parametric studies, a locally optimal configuration for 60 GHz WNoC is obtained, showing that chip-wide attenuation below 32.6 dB could be achieved with standard processes. Finally, the applicability of the methodology is discussed for higher bands and other integrated environments such as a Software-Defined Metamaterial (SDM).Peer ReviewedPostprint (author's final draft

Engineer the channel and adapt to it: enabling wireless intra-chip communication

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The authors gratefully acknowledge support from the Spanish MINECO under grant PCIN-2015-012, from the EU’s H2020 FET-OPEN program under grants No. 736876 and No. 863337, and by the Catalan Institution for Research and Advanced Studies (ICREA).Peer ReviewedPostprint (author's final draft

Exploration of intercell wireless millimeter-wave communication in the landscape of intelligent metasurfaces

Software-defined metasurfaces are electromagnetically ultra-thin, artificial components thatcan provide engineered and externally controllable functionalities. The control over these functionalities isenabled by the metasurface tunability, which is implemented by embedded electronic circuits that modifylocally the surface resistance and reactance. Integrating controllers within the metasurface able them tointercommunicate and adaptively reconfigure, thus imparting a desired electromagnetic operation, opens thepath towards the creation of an artificially intelligent (AI) fabric where each unit cell can have its own sensing,programmable computing, and actuation facilities. In this work we take a crucial step towards bringing theAI metasurface technology to emerging applications, in particular exploring the wireless mm-wave intercellcommunication capabilities in a software-defined HyperSurface designed for operation in the microwaveregime. We examine three different wireless communication channels within the landscape of the reflectivemetasurface: Firstly, in the layer where the control electronics of the HyperSurface lie, secondly inside adedicated layer enclosed between two metallic plates, and, thirdly, inside the metasurface itself. For each casewe examine the physical implementation of the mm-wave transceiver nodes, we quantify communicationchannel metrics, and we identify complexity vs. performance trade-offs.Peer ReviewedPostprint (published version

Radiation pattern prediction for metasurfaces: A neural network-based approach

As the current standardization for the 5G networks nears completion, work towards understanding the potential technologies for the 6G wireless networks is already underway. One of these potential technologies for the 6G networks is reconfigurable intelligent surfaces. They offer unprecedented degrees of freedom towards engineering the wireless channel, i.e., the ability to modify the characteristics of the channel whenever and however required. Nevertheless, such properties demand that the response of the associated metasurface is well understood under all possible operational conditions. While an understanding of the radiation pattern characteristics can be obtained through either analytical models or full-wave simulations, they suffer from inaccuracy and extremely high computational complexity, respectively. Hence, in this paper, we propose a neural network-based approach that enables a fast and accurate characterization of the metasurface response. We analyze multiple scenarios and demonstrate the capabilities and utility of the proposed methodology. Concretely, we show that this method can learn and predict the parameters governing the reflected wave radiation pattern with an accuracy of a full-wave simulation (98.8–99.8%) and the time and computational complexity of an analytical model. The aforementioned result and methodology will be of specific importance for the design, fault tolerance, and maintenance of the thousands of reconfigurable intelligent surfaces that will be deployed in the 6G network environment.This research was funded by the European Commission grant number H2020-FETOPEN736876 (VISORSURF) and by ICREA under the ICREA Academia program.Peer ReviewedPostprint (published version

Intralymphatic chemotherapy injection in gynecological cancer. A pilot study

Se ha administrado bleomicina oleosa o adriamicina durante el curso de una linfografía a 16 enfermas de cáncer de vulva, cérvix o endometrio. Se presenta la técnica de administración y se exponen los efectos secundarios observados, los resultados del estudio anatomopatológico y la evolución de las enfermas hasta la actualidad

Millimeter-wave propagation within a computer chip package

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Wireless Network-on-Chip (WNoC) appears as a promising alternative to conventional interconnect fabrics for chip-scale communications. The WNoC paradigm has been extensively analyzed from the physical, network and architecture perspectives assuming mmWave band operation. However, there has not been a comprehensive study at this band for realistic chip packages and, thus, the characteristics of such wireless channel remain not fully understood. This work addresses this issue by accurately modeling a flip-chip package and investigating the wave propagation inside it. Through parametric studies, a locally optimal configuration for 60 GHz WNoC is obtained, showing that chip-wide attenuation below 32.6 dB could be achieved with standard processes. Finally, the applicability of the methodology is discussed for higher bands and other integrated environments such as a Software-Defined Metamaterial (SDM).Peer Reviewe