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QoE-Guaranteed Optimization in MEC-Enabled Metaverse: An Active Inference Deep Reinforcement Learning Approach

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Du, Jianbo Gong, Jie Chu, Xiaoli Xiong, Zehui Chen, Xianfu Dong, Mianxiong Yu, F. Richard Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security School of Communications and Information Engineering Xi'an710121 China The University of Sheffield Mappin Street Department of Electronic and Electrical Engineering SheffieldS1 3JD United Kingdom Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore Singapore Shenzhen CyberAray Network Technology Company Ltd Shenzhen518000 China Muroran Institute of Technology Department of Sciences and Informatics Muroran050-8585 Japan Carleton University Systems and Computer Engineering OttawaON Canada

In this paper, we consider a MEC-enabled metaverse scenario which consists of a remote metaverse server and an edge server that cooperates to provide services to mobile users. The edge server is deployed at the base station (BS), serves a dual role: augmenting computational capabilities for user equipment (UE) and pre-caching a portion of the metaverse service contents before each time slot. Moreover, the foreground information and the requested contents generated by the UEs can also be cached to the BS. We formulate a problem to maximize the cache hit number by jointly optimizing contents pre-caching and resource allocation at the BS while considering UEs preference and reducing the UEs total energy consumption, essential for the efficient delivery of services in dynamic MEC environments. To solve this problem, we reformulate it as a partially observable markov decision process and propose an active inference enabled deep reinforcement learning algorithm, which combines active inference with deep reinforcement learning to select the optimal strategy by minimizing the expected free energy. Simulations show that the proposed algorithm can effectively improve the total quality of experience and the cache hit number of UEs, while minimizing the UEs total energy consumption compared with other baseline algorithms © 2015 IEEE.

关键词： Active learning

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Hyperedge overlap drives synchronizability of systems with higher-order interactions

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Physical Review E 2025年第3期111卷 034302-034302页

作者： Santiago Lamata-Otín Federico Malizia Vito Latora Mattia Frasca Jesús Gómez-Gardeñes Department of Condensed Matter Physics University of Zaragoza 50009 Zaragoza Spain GOTHAM Laboratory Institute of Biocomputation and Physics of Complex Systems (BIFI) University of Zaragoza 50018 Zaragoza Spain Department of Physics and Astronomy University of Catania 95125 Catania Italy School of Mathematical Sciences Queen Mary University of London London E1 4NS United Kingdom Complexity Science Hub Vienna A-1080 Vienna Austria Department of Electrical Electronics and Computer Science Engineering University of Catania 95125 Catania Italy

The microscopic organization of dynamical systems coupled via higher-order interactions plays a pivotal role in understanding their collective behavior. In this paper, we introduce a framework for systematically investigating the impact of the interaction structure on dynamical processes. Specifically, we develop an hyperedge overlap matrix whose elements characterize the two main aspects of the microscopic organization of higher-order interactions: the inter-order hyperedge overlap (nondiagonal matrix elements) and the intra-order hyperedge overlap (encapsulated in the diagonal elements). In this way, the first set of terms quantifies the extent of superposition of nodes among hyperedges of different orders, while the second focuses on the number of nodes in common between hyperedges of the same order. Our findings indicate that large values of both types of hyperedge overlap hinder synchronization stability, and that the larger is the order of interactions involved, the more important is their role. Our findings also indicate that the two types of overlap have qualitatively distinct effects on the dynamics of coupled chaotic oscillators. In particular, large values of intra-order hyperedge overlap hamper synchronization by favoring the presence of disconnected sets of hyperedges, while large values of inter-order hyperedge overlap hinder synchronization by increasing the number of shared nodes between groups converging on different trajectories, without necessarily causing disconnected sets of hyperedges.

关键词： Synchronization

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Conceptualizing UAM: Technologies and Methods for Safe and Efficient Urban Air Transportation

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Green Energy and Intelligent Transportation 2025年

作者： Lidia Zewde Ioannis A. Raptis North Carolina A&T State University Department of Electrical and Computer Engineering Autonomous Robotics Systems Laboratory Greensboro USA

The effective integration of Urban Air Mobility (UAM) hinges upon the adoption of a comprehensive approach that harmoniously melds various network components, placing paramount importance on the pillars of safety, sustainability, and efficiency. Existing technologies are currently undergoing a transformative evolution to cater to the distinctive requirements of UAM, with an unwavering commitment to enhancing safety, sustainability, and efficiency. This paper meticulously elucidates the extant technologies and methodologies that pertain to the safe and efficient realm of air transportation while delving into the perspective of key UAM network components: (1) Aircraft classification, dimensions, and operational technology; (2) Airspace typology and structural intricacies; and (3) Air Traffic Management (ATM) services. In conclusion, this paper culminates by offering insights into prospective research directions in this burgeoning field.

关键词： Urban Aerial Mobility Electric Vertical Takeoff and Landing Urban Airspace Aircraft Traffic Management Aircraft Communication Navigation and Surveillance Ground Infrastructure Concept of Operations

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MemMIMO: A Simulation Framework for Memristor-Based Massive MIMO Acceleration

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IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年

作者： Xu, Jiawei Zheng, Yi Stathis, Dimitrios Wang, Ruijia Shen, Ruisi Zheng, Li-Rong Zou, Zhuo Hemani, Ahmed University of Macau State-Key Laboratory of Analog and Mixed-Signal VLSI Institute of Microelectronics Faculty of Science and Technology ECE Department China Fudan University State Key Laboratory of Integrated Chips and Systems School of Information Science and Technology Shanghai China KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden

Memristor-based crossbar architectures have proven highly effective for matrix vector multiplication (MVM) operations, making them a promising solution for accelerating the MVMs widely used in precoding algorithms for multiple input multiple output (MIMO) wireless communication systems. However, real-world implementation of memristor-based computing systems face challenges due to commonly observed non-idealities in both the devices themselves and the circuits they’re built into. To facilitate a rapid design flow and investigate the impact of non-idealities, an integrated open-source simulation framework MemMIMO is developed. The simulation framework estimates the accuracy and hardware performance of the computing system, offering a variety of flexible design options. MemMIMO integrates a behavioral model of the mix-signal architecture with a digital front-end. There are three major building blocks in MemMIMO: the device fitting block, the mapping block, and the performance estimation block. These blocks work together to map the complex MVMs in precoding algorithms for MIMO systems to crossbar-based architectures that incorporate memristor models characterized by physical device behavior. Using two typical use cases targeting six-generation (6G) massive MIMO communication as case studies, MemMIMO is used to model different memristor devices, explore the impact of non-idealities on system accuracy, and benchmark circuit-level performance metrics including area, speed, and power. © 1982-2012 IEEE.

关键词： System-on-chip

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Effective Two-Stage Double Auction for Dynamic Resource Trading in Edge Networks via Overbooking

arXiv

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arXiv 2025年

作者： Wu, Sicheng Liwang, Minghui Wang, Deqing Wang, Xianbin Wu, Chao Tang, Junyi Li, Li Jiao, Zhenzhen The School of Informatics Xiamen University Fujian China The Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China The Department of Electrical and Computer Engineering Western University ON Canada The School of Public Affairs Zhejiang University Hangzhou310027 China School of Information Science and Engineering Lanzhou University Lanzhou China The iF-Labs Beijing Teleinfo Technology Co. Ltd. CAICT China

To facilitate responsive and cost-effective computing resource scheduling and service delivery over edge-assisted mobile networks, this paper investigates a novel two-stage double auction methodology via utilizing an interesting idea of resource overbooking to overcome dynamic and uncertain nature from edge servers (sellers) and demand from mobile devices (as buyers). The proposed auction integrates multiple essential factors such as social welfare maximization and decision-making latency (e.g., the time for determining winning seller-buyer pairs) reduction, by introducing a stagewise strategy: an overbooking-driven pre-double auction (OPDAuction) for determining long-term cooperations between sellers and buyers before practical resource transactions as Stage I, and a real-time backup double auction (RBDAuction) for handling residual resource demands during actual transactions. In particular, by applying a proper overbooking rate, OPDAuction helps with facilitating trading contracts between appropriate sellers and buyers as guidance for future transactions, by allowing the booked resources to exceed supply. Then, since pre-auctions may cause risks, our RBDAuction adjusts to real-time market changes, further enhancing the overall social welfare. More importantly, we offer an interesting view to show that our proposed two-stage auction can support significant design properties such as truthfulness, individual rationality, and budget balance. Through extensive experiments, we demonstrate good performance in social welfare, time efficiency, and computational scalability, outstripping conventional methods in dynamic edge computing settings. Copyright © 2025, The Authors. All rights reserved.

关键词： Budget control

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Wireless Hallucination in Generative AI-enabled Communications: Concepts, Issues, and Solutions

arXiv

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arXiv 2025年

作者： Wang, Xudong Wang, Jiacheng Feng, Lei Niyato, Dusit Zhang, Ruichen Kang, Jiawen Xiong, Zehui Du, Hongyang Mao, Shiwen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China College of Computing and Data Science Nanyang Technological University Singapore School of Automation Guangdong University of Technology Guangzhou510006 China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Department of Electrical and Electronic Engineering University of Hong Kong Pok Fu Lam Hong Kong Department of Electrical and Computer Engineering Auburn University Auburn United States

Generative AI (GenAI) is driving the intelligence of wireless communications. Due to data limitations, random generation, and dynamic environments, GenAI may generate channel information or optimization strategies that violate physical laws or deviate from actual real-world requirements. We refer to this phenomenon as wireless hallucination, which results in invalid channel information, spectrum wastage, and low communication reliability but remains underexplored. To address this gap, this article provides a comprehensive concept of wireless hallucinations in GenAI-driven communications, focusing on hallucination mitigation. Specifically, we first introduce the fundamental, analyze its causes based on the GenAI workflow, and propose mitigation solutions at the data, model, and post-generation levels. Then, we systematically examines representative hallucination scenarios in GenAI-enabled communications and their corresponding solutions. Finally, we propose a novel integrated mitigation solution for GenAI-based channel estimation. At the data level, we establish a channel estimation hallucination dataset and employ generative adversarial networks (GANs)-based data augmentation. Additionally, we incorporate attention mechanisms and large language models (LLMs) to enhance both training and inference performance. Experimental results demonstrate that the proposed hybrid solutions reduce the normalized mean square error (NMSE) by 0.19, effectively reducing wireless hallucinations. Copyright © 2025, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Power dissipation and magnetic forces on MAGLEV rebars

引用

IEEE TRANSACTIONS ON MAGNETICS 1997年第2期33卷 1021-1036页

作者： Zahn, M IEEE Department of Electrical Engineering and Computer Science Laboratory for Electromagnetic and Electronic Systems Massachusetts Institute of Technology

Concrete guideways for proposed MAGLEV vehicles may be reinforced with electrically conducting and magnetizable steel rebars, Transient magnetic fields due to passing MAGLEV vehicles will then induce transient currents in the rebars leading to power dissipation and temperature rise as well as Lorentz and magnetization forces on the rebars, In order to evaluate if this heating and force on the rebars affects concrete life and performance, analysis is presented for an infinitely long conducting and magnetizable cylinder in imposed uniform axial or transverse magnetic fields, Exact and approximate solutions are presented for sinusoidal steady state and step transient magnetic fields inside and outside the cylinder, the induced current density, the vector potential for transverse magnetic fields, the time average dissipated power in the sinusoidal steady state, and the total energy dissipated for step transients, Forces are approximately calculated for imposed magnetic fields with a weak spatial gradient, The analysis is applied to representative rebar materials.

关键词： eddy currents MAGLEV magnetic fields magnetic forces rebars

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Fast implementation of the forward positional acceleration of robots via the distributed arithmetic technique

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CIRCUITS systems AND SIGNAL PROCESSING 1997年第2期16卷 165-195页

作者： Grigoriadis, GK Mertzios, BG Automatic Control Systems Laboratory Department of Electrical and Computer Engineering Dimocritus University of Thrace Xanthi Greece

This paper refers to the fast implementation of the positional forward acceleration of the end effector of revolute robotic arms with spherical wrists, using the distributed arithmetic technique. The acceleration of the end effector is calculated by a cascade configuration of two pipelined arrays that calculate the Jacobian matrix and its time derivative, as well as the centrifugal-Coriolis and linear accelerations. These partial accelerations are then added in the adder tree. The building blocks of the arrays are the distributed arithmetic-based circuits that implement the matrix-vector multiplications involved in the calculations. The digit-serial configuration of the proposed implementation of the positional forward acceleration of the end effector is described. The serial and the parallel configurations may result as special cases of the digit-serial configuration. The proposed distributed arithmetic (DA) implementation of the positional forward acceleration may be applied, after appropriate modifications, to the general case of robots having either revolute or prismatic joints, with any type of wrist.

关键词： End effectors

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Efficient Model Training in Edge Networks with Hierarchical Split Learning

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IEEE Transactions on Mobile Computing 2025年

作者： Zhang, Songge Wu, Wen Song, Lingyang Shen, Xuemin Peking University Shenzhen Graduate School School of Electronic and Computer Engineering Shenzhen 518055 China Pengcheng Laboratory Frontier Research Center Shenzhen 518055 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing 100871 China Xiangtan University Hunan Institute of Advanced Sensing and Information Technology Xiangtan China University of Waterloo Department of Electrical and Computer Engineering Waterloo N2L 3G1 Canada

In this paper, we propose an efficient model training scheme, named Group-based Hierarchical Split Learning (GHSL), which can accelerate the artificial intelligence (AI) training process in edge networks in a “first-sequential-then-parallel” manner. Specifically, the proposed scheme hierarchically splits an AI model into a user-side and server-side model, while dividing a number of users into multiple groups. Users in each group train user-side models with the interaction of the shared server-side model sequentially;different groups perform the above training process parallelly;the AI models of each group are aggregated into a global model. We also carry out the convergence analysis for the proposed scheme over non-independent and identically distributed data, which reveals that the convergence rate depends on user grouping. Furthermore, we propose a data-driven two-stage user grouping algorithm to minimize the overall training delay, taking user resource heterogeneity and the black-box training process into account. The proposed algorithm first utilizes the Gaussian process regression approach to determine the number of groups, and then employs the coalition game theory to determine the optimal user grouping decision. Comprehensive simulation results demonstrate that the proposed scheme can reduce training delay, user-side computational workload, and communication overhead by up to 19%, 53%, and 54%, respectively, comparing to state-of-the-art benchmarks. © 2002-2012 IEEE.

关键词： convergence analysis Hierarchical split learning user grouping

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On asymptotic convergence of the dual filters associated with two families of biorthogonal wavelets

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1997年第12期45卷 2928-2940页

作者： Wei, D Bovik, AC Laboratory for Vision Systems Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

The asymptotic behavior of the dual filters associated with biorthogonal spline wavelet (BSW) systems and general biorthogonal Coifman wavelet (GBCW) systems are studied. As the order of the wavelet systems approaches infinity, the magnitude responses of the dual filters in the BSW systems either diverge or converge to some nonideal frequency responses. However, the synthesis filters in the GBCW systems converge to an ideal halfband low pass filter without exhibiting any Gibbs like phenomenon, and a subclass of the analysis filters also converge to an ideal halfband lowpass filter but with a one-sided Gibbs-like behavior. The two approximations of the ideal lowpass filter by the filter associated with a Daubechies orthonormal wavelet and by the synthesis filter in a GBCW system of the same order are compared. Such a study of the asymptotic behaviors of wavelet systems provides insightful characterization of these systems and systematic assessment and global comparison of different wavelet systems.

关键词： Convergence Filters H infinity control Frequency response Wavelet analysis Spline Transfer functions Lagrangian functions Machine vision Gaussian processes

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