188 research outputs found
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Two-Timescale Joint Precoding Design and RIS Optimization for User Tracking in Near-Field MIMO Systems
In this paper, we propose a novel framework that aims to jointly design the
reflection coefficients of multiple RISs and the precoding strategy of a single
BS to optimize the self-tracking of the position and the velocity of a single
multi-antenna UE that moves either in the far- or near-field region.
Differently from the literature, and to keep the overall complexity affordable,
we assume that RIS optimization is performed less frequently than localization
and precoding adaptation. The proposed procedure leads to minimize the inverse
of the received power in the UE position uncertainty area between two
subsequent optimization steps.
The optimal RIS and precoder strategy are compared with the classical
beam-focusing strategy and with a scheme that maximizes the communication rate.
It is shown that if the RISs are optimized for communications, their
configuration is suboptimal when used for tracking purposes.
Numerical results show that in typical indoor environments with only one BS
and a few RISs operating on millimeter waves, high location accuracy in the
range of less than half a meter can be achieved
Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023
Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida
Integrated Circuits and Systems for Smart Sensory Applications
Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware
A Robot to Measure Water Parameters in Water Distribution Systems
Water distribution systems (WDS) are critical infrastructures that transfer drinking water to consumers. In the U.S., around 42 billion gallons of water are being delivered per day via one million miles of pipes to be used in different sectors. Incidents to pipelines cause leak or let contaminants enter purified water in pipe that is harmful to public health. Hence, periodic condition assessments of pipelines and water inside it are required. However, due to the long and complicated configurations of these networks, access to all parts of the pipelines is a cumbersome task. To this aim, in-pipe robots are promising solution that facilitate access to different locations inside pipelines and perform different in-pipe missions.
In this project, we design and fabricate an in-pipe robotic system is that is used for water quality monitoring. The robot is equipped with a wireless sensor module and the sensor module is synchronized with the motion unit of the robot. The wireless sensor module facilitates bi-directional data transmission between the robot and base station aboveground. The integrated robotic system navigates in different configurations of the pipeline with smart motion.
To this aim, the mechanical design of the self-powered robot based on three adjustable arm modules and three actuator modules is designed. The components of the robot are characterized based on real operation conditions in pipes. A multi-phase motion control algorithm is developed for the robot to move in straight path and non-straight configurations like bends and T-junctions. A bi-directional wireless sensor module is designed to send data packets through underground environment. Finally, the multi-phase motion controller is synchronized with the wireless sensor module and we propose an operation procedure for the robot. In the operation procedure, some radio transceivers are located at non-straight configurations of pipelines and receive the sensor measurements from the robot and guide the robot in the desired direction. The proposed operation procedure provides smart navigation and data transmission during operation for the robot
Localization error bounds for 5G mm-wave systems under hardware impairments
Localization and location aware systems are expected to be counted as one of the main services
of 5G millimeter wave (mmWave) communication systems. mmWave communication
systems are offering a large bandwidth from 30-300 GHz frequency band along with low
latency communications. Although, they use massive number of antennas at their transmitters
and receivers, their transceivers occupy a very small area, in order of centimeters.
These features make 5G mmWave communication systems an exceptional candidate for
the localization services. However, mmWave suffers from some limitations such as high
vulnerability to the environment and hardware deficiency.
The hardware used in mmWave system’s transceivers including power amplifiers and
analog/digital converters, cannot be manufactured perfectly as of high costs. Therefore, it
is highly probabilistic to see a non-linear behavior coming out of the mmWave transceivers,
known as hardware impairments (HWIs). HWIs is generally caused as a result of nonlinearity
of transmitter power amplifier and receiver low noise amplifier (LNA) as well as
analog to digital (ADC) and digital to analog converters (DAC). Moreover, HWIs is the
general form of phase noise and In/Quadrature phase (I/Q) imbalance. Because of the
mmWave’s nature, even a slight shortcoming can cause severe effects on its performance.
This thesis investigates the possible effects of HWIs on the user localization error bounds.
Towards that and focusing on line-of-sight (LOS) path, we derive the Cramer-Rao Lower
Bound (CRLB) for the user equipment (UE)’s location and orientation by starting with
a conventional two dimension (2D) scenario and then, we extend it to the realistic three
dimensional (3D) scenario. [...
High-Performance Reconfigurable Piezoelectric Resonators and Filters for RF Frontend Applications
A conventional RF frontend module consists of many filters where each filter is allocated for a specific frequency band. These filters are connected through multiplexing switch networks to support multi-band wireless standards. Using an individual filter for each frequency band increases the module size, power consumption and cost. Therefore, implementation of reconfigurable filters that can operate at different frequency bands while maintaining key RF performance requirements such as low insertion loss, good linearity and power handling is necessary for manufacturing of future RF frontends.
Acoustic wave resonators based on piezoelectric devices such as Surface Acoustic Wave (SAW) and Bulk Acoustic Wave (BAW) are the most commonly used technologies to manufacture filters for RF applications. The objective of the research described in this thesis is to investigate the feasibility of tunable filter solutions using piezoelectric SAW resonators. A tunable SAW technology which can maintain required performance parameters and can be commercially manufactured will constitute a technological breakthrough in wireless communications.
Thin-Film Piezoelectric on Substrate (TPoS) resonators, based on Aluminum Nitride (AlN) piezoelectric material which are fabricated using commercially available Silicon on Insulator (SOI) PiezoMUMPs process, have been demonstrated. By combining the superior acoustic properties of AlN and single crystalline silicon substrate, this class of resonators achieves ultra-high quality factor (Q) values in excess of 3600. A 3-pole bandpass filter using direct electrical coupling between the resonators has been presented and we have studied the performance of the fabricated filter over a temperature range from -196ºC up to +120ºC and under high power.
For the first time, we have demonstrated the integration of switching elements, based on Vanadium Dioxide (VO2) phase change material, with Incredible-High-Performance SAW (IHP-SAW) technology which allows us to design and implement switchable and reconfigurable SAW resonators and filters for wireless applications.
Switchable multi-band filters using VO2 switches strategically imbedded within the resonators of the filter have been demonstrated. A switchable dual-band filter with four switching states and two channels was presented using hybrid integration approach where discrete VO2 switches were fabricated separately and then integrated with the SAW resonators and filters using wire bonds. The fabricated 5-pole dual-band filter demonstrated good insertion loss in both transmission states but had inadequate performance in terms of isolation between the channels due to the limitations of the hybrid integration approach. Moreover, hybrid integration does not allow us to use more than a few switching elements and cannot be used for the implementation of higher order filters. To address these issues, we have demonstrated the monolithic integration of VO2 switches using an in-house fabrication process that allows us to fabricate VO2 switches and SAW resonators and filters on a single chip. A dual-band switchable higher order 7-pole filter with six monolithically integrated VO2 switches, three for each channel, was demonstrated. The monolithic integration allows the single-chip implementation of the proposed switchable dual-band filter with improved performance along with significant size reduction and ease of manufacturing, paving the path for commercialization of this technology.
Novel reconfigurable SAW resonators and filters with tunable center frequency were also presented for the first time. Tuning of the center frequency between two different states was achieved by changing the configuration of interdigitated electrodes within the SAW resonator and by using a set of tuning electrodes and VO2 switches. In the first implementation, the VO2 switches were integrated over the electrodes and inside the active area of the SAW resonator. Each resonator consists of hundreds of tuning electrodes and for a reliable switching each resonator requires a number of heater elements which results in increased DC power consumption and total size. A second reconfigurable resonator with a modified structure and using a modified in-house fabrication process to include a second electrode layer was proposed to reduce the number of required VO2 switching elements for an even more compact implementation and ten times reduction in the required DC power consumption. Design, implementation, and measurement results for a 3-pole tunable SAW filter based on the proposed reconfigurable resonators have been presented. The filter’s center frequency is tuned from 733 MHz to 713 MHz while the insertion loss was maintained below 2.5 dB. The fabricated SAW resonators and filters also showed acceptable linear and high-power performance characteristics. This is the first time a single-chip implementation of a reconfigurable SAW filter with center frequency tuning and acceptable RF performance using monolithically integrated VO2 switches is ever reported. The single-chip implementation of the proposed SAW resonators and filters enables the development of future low-cost RF multi-band transceivers with improved performance and functionality
ADVANCED RADIO ACCESS NETWORK FEATURING FLEXIBLE PER-UE SERVICE PROVISIONING AND COLLABORATIVE MOBILE EDGE COMPUTING
Enriched by numerous technological advances, radio access networks (RANs) in the fifth mobile networks generation (5G)-and-beyond strive to meet the goals of both mobile network operators (MNOs) and end-users. While MNOs seek efficiency, resiliency, reliability and flexibility of their networks, end-users are more concerned with the variety and quality of the provided, state-of-the-art, reasonably priced services. This has resulted in a complex, multi-tier, and heterogeneous RAN architecture that is severely challenged to achieve and maintain a strict reliability requirement of seven-nines (i.e., 99.99999% network up-time) and to meet ultra-reliable, low latency communications (URLLC) requirements with a latency upper bound of 1 ms end-to-end roundtrip time. Based on the flexible function split concept and data-plane programmability, this dissertation makes several key contributions to the body of knowledge on advanced, service-oriented RANs in two key core components. The first core component pertains to improving fronthaul efficiency, resiliency, flexibility, and latency performance with a cross-layer integration of Analog-Option-9 function split in the flexible fronthaul paradigm. Within the folds of that, the novel cross-layer digital-analog integration is experimentally investigated to pave the way for promising analog technologies to find their niche in 5G-and-beyond. The second core component is related to the design of lightweight, fronthaul-positioned multi-access edge computing (MEC) units to host Cooperative-URLLC applications at the edge of the fronthaul. Hence, from the vertical perspective, the dissertation provides solutions to support general URLLC applications and the Cooperative-URLLC variation by shrinking and eliminating latency sources at the Top-of-RAN and Low-RAN segments of advanced RANs.Ph.D
Advanced Computational Methods for Oncological Image Analysis
[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians’ unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations—such as segmentation, co-registration, classification, and dimensionality reduction—and multi-omics data integration.
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