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arXiv 2024年

作者： Kratochvila, Lukas de Jong, Gijs Arkesteijn, Monique Bilík, Šimon Zemčík, Tomáš Horak, Karel Rellermeyer, Jan S. Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science TU Delft Delft Netherlands Department of Management in the Built Environment Faculty of Architecture and the Built Environment TU Delft Delft Netherlands Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland Dependable and Scalable Software Systems Institute of Systems Engineering Faculty of Electrical Engineering and Computer Science Leibniz University Hannover Hannover Germany

digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orientation in exceptional situations, and faster rescue intervention. Nevertheless, creating the twins still remains a largely manual effort, due to a lack of 3D-representations, which are available only in limited amounts for some new buildings. Thus, in this paper we aim to synthesize 3D information from commonly available 2D architectural floor plans. We propose two novel pixel-wise segmentation methods based on the MDA-Unet and MACU-Net architectures with improved skip connections, an attention mechanism, and a training objective together with a reconstruction part of the pipeline, which vectorizes the segmented plans to create a 3D model. The proposed methods are compared with two other state-of-the-art techniques and several benchmark datasets. On the commonly used CubiCasa benchmark dataset, our methods have achieved the mean F1 score of 0.86 over five examined classes, outperforming the other pixel-wise approaches tested. We have also made our code publicly available to support research in the field. © 2024, CC BY.

关键词： Semantic Segmentation

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MIMO Virtual Array Design for mmWave 4D-Imaging Radar Sensors

MIMO Virtual Array Design for mmWave 4D-Imaging Radar Sensor...

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European Signal Processing Conference (EUSIPCO)

作者： Nazila Karimian Sichani Mohammad Alaee-Kerahroodi Ehsan Raei Bhavani Shankar M. R. Esfandiar Mehrshahi Seyyed Ali Ghorashi Department of Telecommunications Faculty of Electrical Engineering Shahid Beheshti University Tehran Iran Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg Department of Computer Science and Digital Technologies School of Architecture Computing and Engineering University of East London London UK

The recently developed 4D-Imaging mmWave MIMO radars have significant advantages over conventional radar sensors because they offer a large virtual array in both azimuth and elevation. However, the physical placement of transmit and receive antennas to achieve the desired virtual array, while considering cost and efficiency is not intuitive. In this paper, we propose an optimization framework for optimally placing the transmit and receive array physical elements. The proposed framework obtains a sequence of optimal placements based on the coordinate descent by defining a desired virtual array and number of transmit and receive antenna elements as the objective. The objective function is then monotonically minimized in each iteration of the proposed algorithm, converging to a solution that guarantees the desired number of transmit and receive antenna elements, while the obtained virtual array is as close to the desired virtual array as possible. The simulation results are validated by simulating the virtual array of multiple commercially available 4D-Imaging radar products.

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PCA-based Channel Estimation for MIMO Communications

arXiv

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arXiv 2022年

作者： Soares, Jonathan Aguiar Mayer, Kayol Soares Valadares, Pedro Benevenuto Arantes, Dalton Soares The Digital Communications Laboratory – ComLab Department of Communications School of Electrical and Computer Engineering University of Campinas – Unicamp SP Campinas13083-852 Brazil

In multiple-input multiple-output communications, channel estimation is paramount to keep base stations and users on track. This paper proposes a novel PCA-based – principal component analysis – channel estimation approach for MIMO orthogonal frequency division multiplexing systems. The channel frequency response is firstly estimated with the least squares method, and then PCA is used to filter only the higher singular components of the channel impulse response, which is then converted back to frequency domain. The proposed approach is compared with the MMSE, the minimum mean square error estimation, in terms of bit error rate versus Eb/N0. © 2022, CC BY.

关键词： Principal component analysis

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Waveform Selection for FMCW and PMCW 4D-Imaging Automotive Radar Sensors

Waveform Selection for FMCW and PMCW 4D-Imaging Automotive R...

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IEEE National Conference on Radar

作者： Nazila Karimian Sichani Moein Ahmadi Ehsan Raei Mohammad Alaee-Kerahroodi Bhavani Shankar M. R. Esfandiar Mehrshahi Seyyed Ali Ghorashi Department of Telecommunications Faculty of Electrical Engineering Shahid Beheshti University Tehran Iran Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg Department of Computer Science and Digital Technologies School of Architecture Computing and Engineering University of East London London UK

The emerging 4D-imaging automotive MIMO radar sensors necessitate the selection of appropriate transmit wave-forms, which should be separable on the receive side in addition to having low auto-correlation sidelobes. TDM, FDM, DDM, and inter-chirp CDM approaches have traditionally been proposed for FMCW radar sensors to ensure the orthogonality of the transmit signals. However, as the number of transmit antennas increases, each of the aforementioned approaches suffers from some drawbacks, which are described in this paper. PMCW radars, on the other hand, can be considered to be more costly to implement, have been proposed to provide better performance and allow for the use of waveform optimization techniques. In this context, we use a block gradient descent approach to design a waveform set for MIMO-PMCW that is optimized based on weighted integrated sidelobe level in this paper, and we show that the proposed waveform outperforms conventional MIMO-FMCW approaches by performing comparative simulations.

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Constrained Optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic Control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： Optimization algorithms

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AgileWatts: An Energy-Efficient CPU Core Idle-State architecture for Latency-Sensitive Server Applications 22

AgileWatts: An Energy-Efficient CPU Core Idle-State Architec...

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Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture

作者： Jawad Haj Yahya Haris Volos Davide B. Bartolini Georgia Antoniou Jeremie S. Kim Zhe Wang Kleovoulos Kalaitzidis Tom Rollet Zhirui Chen Ye Geng Onur Mutlu Yiannakis Sazeides Rivos Inc Mountain View California United States Computer Architecture Laboratory Department of Computer Science University of Cyprus Computing Systems Lab Huawei Zurich Research Center Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

ISBN: (纸本)9781665462723

User-facing applications running in modern datacenters exhibit irregular request patterns and are implemented using a multitude of services with tight latency requirements (30--250μs). These characteristics render existing energy-conserving techniques ineffective when processors are idle due to the long transition time (order of 100μs) from a deep CPU core idle power state (C-state). While prior works propose management techniques to mitigate this inefficiency, we tackle it at its root with AgileWatts (AW): a new deep CPU core C-state architecture optimized for datacenter server processors targeting latency-sensitive *** drastically reduces the transition latency from deep CPU core idle power states while retaining most of their power savings based on three key ideas. First, AW eliminates the latency (several microseconds) of saving/restoring the core context when powering-off/-on the core in a deep idle state by i) implementing medium-grained power-gates, carefully distributed across the CPU core, and ii) retaining context in the power-ungated domain. Second, AW eliminates the flush latency (several tens of microseconds) of the L1/L2 caches when entering a deep idle state by keeping L1/L2 content power-ungated. A small control logic also remains ungated to serve cache coherence traffic. AW implements cache sleep-mode and leakage reduction for the power-ungated domain by lowering a core's voltage to the minimum operational level. Third, using a state-of-the-art power efficient all-digital phase-locked loop (ADPLL) clock generator, AW keeps the PLL active and locked during the idle state, cutting microseconds of wake-up latency at negligible power *** evaluation with an accurate industrial-grade simulator calibrated against an Intel Skylake server shows that AW reduces the energy consumption of Memcached by up to 71% (35% on average) with <1% end-to-end performance degradation. We observe similar trends for other evaluated services (MySQL and Kafka).

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Continual Reinforcement Learning for digital Twin Synchronization Optimization

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IEEE Transactions on Mobile Computing 2025年

作者： Tong, Haonan Chen, Mingzhe Zhao, Jun Hu, Ye Yang, Zhaohui Liu, Yuchen Yin, Changchuan Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing Advanced Information Network Laboratory Beijing China College of Computing and Data Science Singapore University of Miami Department of Electrical and Computer Engineering Frost Institute for Data Science and Computing Coral Gables33146 United States University of Miami Department of Industrial and Systems Engineering Coral Gables33146 United States Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China North Carolina State University Department of Computer Science RaleighNC27695 United States Beijing Key Laboratory of Network System Architecture and Convergence China Beijing University of Posts and Telecommunications Beijing Advanced Information Network Laboratory Beijing100876 China

This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects factory physical object state data from wireless devices to build a real-time virtual DT system for factory event analysis. Due to continuous data transmission, maintaining DT synchronization must use extensive wireless resources. To address this issue, a subset of devices is selected to transmit their sensing data, and resource block (RB) allocation is optimized. This problem is formulated as a constrained Markov process (CMDP) problem that minimizes the long-term mismatch between the physical and virtual systems. To solve this CMDP, we first transform the problem into a dual problem that refines RB constraint impacts on device scheduling strategies. We then propose a continual reinforcement learning (CRL) algorithm to solve the dual problem. The CRL algorithm learns a stable policy across historical experiences for quick adaptation to dynamics in physical states and network capacity. Simulation results show that the CRL can adapt quickly to network capacity changes and reduce normalized root mean square error (NRMSE) between physical and virtual states by up to 55.2%, using the same RB number as traditional methods. © 2025 IEEE. All rights reserved.

关键词： Markov processes

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Reinforcement Learning with Unbiased Policy Evaluation and Linear Function Approximation

Reinforcement Learning with Unbiased Policy Evaluation and L...

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IEEE Conference on Decision and Control

作者： Anna Winnicki R. Srikant Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois at Urbana-Champaign C3.ai Digital Transformation Institute

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We provide performance guarantees for a variant of simulation-based policy iteration for controlling Markov decision processes that involves the use of stochastic approximation algorithms along with state-of-the-art techniques that are useful for very large MDPs, including lookahead, function approximation, and gradient descent. Specifically, we analyze two algorithms; the first algorithm involves a least squares approach where a new set of weights associated with feature vectors is obtained via least squares minimization at each iteration and the second algorithm is a two-time-scale algorithm taking several steps of gradient descent towards the least squares solution before obtaining the next iterate using a stochastic approximation algorithm.

关键词： Upper bound Process control Reinforcement learning Markov processes Aerospace electronics Approximation algorithms Minimization

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Formal Analysis of an IoT-Based Healthcare Application

Formal Analysis of an IoT-Based Healthcare Application

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IEEE Symposium on computers and Communications (ISCC)

作者： Maissa Elleuch Sofiène Tahar Digital Research Center of Sfax Technopark of Sfax Sfax Tunisia CES Laboratory National School of Engineers of Sfax Sfax University Tunisia Dept. of Electrical & Computer Engineering Concordia University Montreal Quebec Canada

In the healthcare context, remote monitoring based on the Internet of Things (IoT) technology is a widespread application. Underlying entities are interacting to bring up various services, so that their communication has to be ensured without defects such as deadlocks. The correct validation of these IoT applications is a major concern because of their distributed and concurrent features, as well as, the safety-critical nature of the health context. In this paper, we show how we use a model checking approach to accurately validate the behavior of an IoT-based healthcare application. We then focus on verifying three important classes of properties namely safety, liveness, and absence of deadlock. The verification is guaranteed by means of the UPPAAL model checker.

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Mode Selection and Power Allocation for UAV-Assisted Cellular Networks 13

Mode Selection and Power Allocation for UAV-Assisted Cellula...

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13th International Conference on Wireless Communications and Signal Processing, WCSP 2021

作者： Feng, Daquan Jiang, Wei Qian, Gongbin Long, Litai Xiao, Sa Xia, Xiang-Gen Shenzhen Key Laboratory of Digital Creative Technology Shenzhen University Shenzhen China Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan China University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States

ISBN: (纸本)9781665407854

In this paper, we study the mode selection and power allocation in a UAV-assisted cellular network, where a UAV user pair coexists with a regular cellular user (RCU). The UAV user pair can operate either in full-duplex (FD) mode or half-duplex (HD) mode for two-way information exchange. We aim to maximize the overall throughput of the system while guaranteeing the QoS requirements for both of the UAV user pair and RCU. We first adopt Phase 1 method for access control in each mode. Then concave-convex procedure (CCCP) method is applied with log-barrier interior point method to maximize the overall throughput of the network. Numerical results demonstrate that the proposed joint access control, mode selection and power allocation method can significantly improve the system performance. © 2021 IEEE.

关键词： Access control

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