370 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Engineering Photon Sources for Practical Quantum Information Processing:If you liked it then you should have put a ring on it

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    Integrated quantum photonics offers a promising route to the realisation of universal fault-tolerant quantum computers. Much progress has been made on the theoretical aspects of a future quantum information processor, reducing both error thresholds and circuit complexity. Currently, engineering efforts are focused on integrating the most valuable technologies for a photonic quantum computer; pure single-photon sources, low-loss phase shifters and passivecircuit components, as well as efficient single-photon detectors and corresponding electronics.Here, we present efforts to target the former under the constraints imposed by the latter. We engineer the spectral correlations of photons produced by a heralded single-photon source, such that they produce photons in pure quantum states (99.1±0.1 % purity), and enable additional optimisation using temporal shaping of the pump field. Our source also has a high intrinsicheralding efficiency (94.0 ± 2.9 %) and produces photon pairs at a rate (4.4 ± 0.1 MHz mW−2) which is an order of magnitude better than previously predicted by the literature for a resonant source of this purity. Additionally, we present tomographic methodologies that fully describe the photonic quantum states that we produce, without the use of analytical models, and as a means of verifying the quantum states we create, entitled – "Quantum-referenced SpontaneousEmission Tomography" (Q-SpET). We also design reconfigurable photonic circuits that can be operated at cryogenic temperatures, with zero static power consumption, entitled – "Cladding Layer Manipulation" (CLM). These devices function as on-chip phase shifters, enabling the local reconfiguration of circuit elements using established technologies but removing the need for active power consumption to maintain the reconfigured circuit. These devices are capable ofan Lπ = 12.3 ± 0.3 µm, a ∼7x reduction in length when compared to the thermo-optic phaseshifters used throughout this thesis. Finally, we investigate how pure photon sources operate as part of larger circuits within the typical design rules of photonic quantum circuits. Using this information to accurately model all of the spurious contributions to the final photonic quantumstate, which we call a form of nonlinear noise. This noise can decrease source purity to below 40 %, significantly affecting the fidelity of Hong-Ou-Mandel interference, and subsequently, our ability to reliably create fundamental resources for photonic quantum computers. All of this contributes to our design of a fundamental building block for integrated quantum photonic processors, the functionality of which can be predicted at scale, under the conditions imposed by the rest of the processor

    Resourse Allocation in the Wireless Internet-of-Things

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    The Internet-of-Things (IoT) is widely regarded as a promising paradigm, marking a revolutionary shift in the way that technology interacts with the world. Despite the rising popularity and extensive integration of IoT across diverse domains, the development and deployment of these interconnected systems are met with considerable challenges. One notable challenge is the scarcity of spectrum resources, which poses a significant obstacle in accommodating the massive data transmission. In addition, small-sized mobile terminals are constrained by limited computation and energy resources. These limitations make the traditional standalone operation of devices increasingly unfeasible. In this thesis, we delve into comprehensive task offloading and resource allocation strategies to utilize of limited resources in wireless IoT. In the first part, we propose a full-dimensional task offloading scheme in the multi-layer computing network. On this basis, we formulate an mixed-integer nonlinear programming (MINLP) problem and develop an inverse reinforcement learning (IRL) based algorithm to solve this problem. Without sacrificing the global optimality, the algorithm can significantly accelerate the optimal branch-and-bound (B&B) algorithm. In the second part, we delve into strategies to optimize energy efficiency within the downlink cell-free massive MIMO systems. We develop a green energy scheme and formulate it as a non-convex MINLP problem. To solve this problem, we propose a novel optimization-embedded deep reinforcement learning (DRL) algorithm, which enjoys the benefits of directly inferring solutions for the formulated problem. In the last part, we develop a NOMA-based task offloading scheme in a multi-layer computing network. On this basis, we formulate the task offloading scheme as a non-convex mixed-integer optimization problem and propose a reincarnating DRL algorithm, where accumulated apriori information is incorporated for fast retraining

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

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    This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

    Data Collection in Two-Tier IoT Networks with Radio Frequency (RF) Energy Harvesting Devices and Tags

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    The Internet of things (IoT) is expected to connect physical objects and end-users using technologies such as wireless sensor networks and radio frequency identification (RFID). In addition, it will employ a wireless multi-hop backhaul to transfer data collected by a myriad of devices to users or applications such as digital twins operating in a Metaverse. A critical issue is that the number of packets collected and transferred to the Internet is bounded by limited network resources such as bandwidth and energy. In this respect, IoT networks have adopted technologies such as time division multiple access (TDMA), signal interference cancellation (SIC) and multiple-input multiple-output (MIMO) in order to increase network capacity. Another fundamental issue is energy. To this end, researchers have exploited radio frequency (RF) energy-harvesting technologies to prolong the lifetime of energy constrained sensors and smart devices. Specifically, devices with RF energy harvesting capabilities can rely on ambient RF sources such as access points, television towers, and base stations. Further, an operator may deploy dedicated power beacons that serve as RF-energy sources. Apart from that, in order to reduce energy consumption, devices can adopt ambient backscattering communication technologies. Advantageously, backscattering allows devices to communicate using negligible amount of energy by modulating ambient RF signals. To address the aforementioned issues, this thesis first considers data collection in a two-tier MIMO ambient RF energy-harvesting network. The first tier consists of routers with MIMO capability and a set of source-destination pairs/flows. The second tier consists of energy harvesting devices that rely on RF transmissions from routers for energy supply. The problem is to determine a minimum-length TDMA link schedule that satisfies the traffic demand of source-destination pairs and energy demand of energy harvesting devices. It formulates the problem as a linear program (LP), and outlines a heuristic to construct transmission sets that are then used by the said LP. In addition, it outlines a new routing metric that considers the energy demand of energy harvesting devices to cope with routing requirements of IoT networks. The simulation results show that the proposed algorithm on average achieves 31.25% shorter schedules as compared to competing schemes. In addition, the said routing metric results in link schedules that are at most 24.75% longer than those computed by the LP

    D4.2 Intelligent D-Band wireless systems and networks initial designs

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    This deliverable gives the results of the ARIADNE project's Task 4.2: Machine Learning based network intelligence. It presents the work conducted on various aspects of network management to deliver system level, qualitative solutions that leverage diverse machine learning techniques. The different chapters present system level, simulation and algorithmic models based on multi-agent reinforcement learning, deep reinforcement learning, learning automata for complex event forecasting, system level model for proactive handovers and resource allocation, model-driven deep learning-based channel estimation and feedbacks as well as strategies for deployment of machine learning based solutions. In short, the D4.2 provides results on promising AI and ML based methods along with their limitations and potentials that have been investigated in the ARIADNE project

    Direct communication radio Iinterface for new radio multicasting and cooperative positioning

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    Cotutela: Universidad de defensa UNIVERSITA’ MEDITERRANEA DI REGGIO CALABRIARecently, the popularity of Millimeter Wave (mmWave) wireless networks has increased due to their capability to cope with the escalation of mobile data demands caused by the unprecedented proliferation of smart devices in the fifth-generation (5G). Extremely high frequency or mmWave band is a fundamental pillar in the provision of the expected gigabit data rates. Hence, according to both academic and industrial communities, mmWave technology, e.g., 5G New Radio (NR) and WiGig (60 GHz), is considered as one of the main components of 5G and beyond networks. Particularly, the 3rd Generation Partnership Project (3GPP) provides for the use of licensed mmWave sub-bands for the 5G mmWave cellular networks, whereas IEEE actively explores the unlicensed band at 60 GHz for the next-generation wireless local area networks. In this regard, mmWave has been envisaged as a new technology layout for real-time heavy-traffic and wearable applications. This very work is devoted to solving the problem of mmWave band communication system while enhancing its advantages through utilizing the direct communication radio interface for NR multicasting, cooperative positioning, and mission-critical applications. The main contributions presented in this work include: (i) a set of mathematical frameworks and simulation tools to characterize multicast traffic delivery in mmWave directional systems; (ii) sidelink relaying concept exploitation to deal with the channel condition deterioration of dynamic multicast systems and to ensure mission-critical and ultra-reliable low-latency communications; (iii) cooperative positioning techniques analysis for enhancing cellular positioning accuracy for 5G+ emerging applications that require not only improved communication characteristics but also precise localization. Our study indicates the need for additional mechanisms/research that can be utilized: (i) to further improve multicasting performance in 5G/6G systems; (ii) to investigate sideline aspects, including, but not limited to, standardization perspective and the next relay selection strategies; and (iii) to design cooperative positioning systems based on Device-to-Device (D2D) technology

    Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

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    Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida
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