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Dynamic Resource Allocation for Multi-Access Edge Computing in Urban Rail Transit

IEEE TRANSACTIONS ON VEHICULAR technology 2025年第2期74卷 3296-3310页

作者： Zhang, Qingmiao Zhang, Chenxi Zhao, Junhui Wang, Dongming Xu, Wei East Chinag Univ Sch Informat Engn Nanchang 330013 Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China

The development of information technology and intelligence in urban rail transit has attracted great attention. The requirement for compute-intensive and delay-sensitive services is increasing rapidly. As a new network paradigm, Multi-access Edge Computing (MEC) can offer an environment for information technology service and extend cloud computing capability to the edge of mobile communication network. So communication data can be timely processed near the source to effectively solve the limitation of on-board resources. In this paper, we consider the heterogeneous characteristics of services and different requirements of tasks in urban rail transit system, and a MEC system architecture based on task classification is designed. To effectively utilize communication and computing resources, a resource allocation strategy based on Task Classification Twin Delayed Deep Deterministic policy gradient (TC-TD3) algorithm is proposed, which includes communication and computing resources allocation. In addition, to address the offloading selection issue of multi-MEC servers, a task offloading algorithm based on balancing tasks priority of MEC is designed. In the system model, considering the random arrival time of tasks and the dynamic resource allocation at each time slot, we propose a dynamic task execution model which is more suitable for the urban rail transit system. The findings of the simulation demonstrate that the proposed scheme can significantly improve the task completion rate and reduce the task processing delay of different tasks.

关键词： Urban rail transit multi-access edge computing (MEC) resource allocation TC-TD3 dynamic task execution Urban rail transit multi-access edge computing (MEC) resource allocation TC-TD3 dynamic task execution

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Integrated Object Detection and communication for Synthetic Aperture Radar Images

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2025年 18卷 294-307页

作者： Xu, Zhiping Xu, Deyin Lin, Lixiong Song, Linqi Song, Dan Sun, Yanglong Chen, Qiwang Jimei Univ Sch Ocean Informat Engn Xiamen 361021 Peoples R China Xiamen Univ Key Lab Underwater Acoust Commun & Marine Informat Minist Educ Xiamen 361005 Peoples R China City Univ Hong Kong Hong Kong Peoples R China City Univ Hong Kong Shenzhen Res Inst Shenzhen Peoples R China Jimei Univ Nav Coll Xiamen 361021 Peoples R China Huaqiao Univ Coll Informat Sci & Engn Xiamen Key Lab Mobile Multimedia Commun Xiamen 361021 Peoples R China

In this article, an integrated object detection and communication (IODC) system based on single-stage detection framework is first proposed for synthetic aperture radar (SAR) images in underwater environment. Specifically, the combination of the multiscale feature extraction module and semantic information enhance fusion module for SAR images in underwater environment is designed as the semantic encoder and the results prediction module with anchor-free detection method is designed as the semantic decoder. Considering the multiscale feature, the channel encoder composed by a multiscale fusion module and a redundancy module is designed, and the channel decoder is the inverse of the channel encoder. To adapt to the time-varying and complex wireless environment, an adaptive transmission (AT) mechanism based on attention mechanism and knowledge base is proposed for the IODC system. Moreover, considering the actual application requirements, a lightweight design for the IODC system with the AT mechanism is also conducted. The experiment results on the Sonar Common Target Detection dataset show that the proposed IODC system with AT mechanism can achieve nearly 91% average precision at 25 dB, which means the proposed system can achieve the effective integration of the objection detection and communication for SAR images in underwater environment. In the lightweight design, the model parameters of the proposed system can be reduced by up to 20%, with only a 2.22% sacrifice in performance.

关键词： Radar polarimetry Object detection Transformers Synthetic aperture radar Feature extraction Decoding wireless sensor networks Remote sensing Deep learning Classification algorithms semantic communication synthetic aperture radar underwater environment

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A V -Band 2-Gb/s 6.5-dBm Low-Power Transmitter in CMOS With On-Chip Antenna and Consumption Adaptivity Down to 700 nW

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 2025年第2期60卷 410-420页

作者： An, Xin Morath, Helmuth P. E. Protze, Florian Wagner, Jens Ellinger, Frank Tech Univ Dresden Chair Circuit Design & Network Theory CCN Ctr Tactile Internet Human In the Loop CeTI D-01069 Dresden Germany

This article presents and investigates a V -band transmitter (TX) for low-power wireless communication supporting on-off keying (OOK) and four-/eight-level pulse amplitude modulation (PAM4/8). To prove the concept, the circuit is implemented in a 22-nm fully depleted silicon-on-insulator (FD-SOI) complementary metal oxide semiconductor (CMOS) technology. The TX consumes 11.7 mW at full speed. Furthermore, the TX supports low-power mode with as low as 700 nW of dc power. The maximum data rate is 2 Gb/s. By applying dynamic data rate to dc-power adaptivity (DDDA), the dc power can be significantly reduced as the data rates decreases. This maintains the energy-per-bit below 10 pJ/b for data rates greater than 100 kb/s with a best value of 3.9 pJ/b and allows the dc power to be greatly reduced down to 700 nW at data rates below 20 kb/s. The measured maximum transmission power is 6.5 dBm. Moreover, the TX achieves 10-dBm effective isotropic radiated power (EIRP) with an on-chip 3-D antenna. The core area of the TX is only 0.19 mm 2 . To the best knowledge of the authors, the proposed TX is the first reported TX with DDDA and achieves the lowest dc power in comparison to similar designs that have been reported to date.

关键词： wireless sensor networks wireless communication System-on-chip Power amplifiers Logic gates Power harmonic filters Voltage-controlled oscillators Bondwire antenna consumption adaptivity duty cycling millimeter-wave (mmW) on-off keying (OOK) pulse amplitude modulation (PAM) wireless sensor network (WSN) wireless sensor network (WSN)

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Radar-aided reconfigurable intelligent surface for vehicular wireless communication

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OPTICS EXPRESS 2025年第5期33卷 11996-12011页

作者： Wang, Kun Tian, Yuze Yan, Tai Wang, Bo Shi, Xintong Xiong, Jie Yu, Wen Jin, Jing Lin, Hai Tang, Wenxuan Cent China Normal Univ Coll Phys Sci & Technol Wuhan 430079 Peoples R China South China Univ Technol Sch Future Technol Guangzhou 510641 Peoples R China Southeast Univ State Key Lab Millimeter Waves Nanjing 210096 Peoples R China Southeast Univ Inst Electromagnet Space Nanjing 210096 Peoples R China

In the intricate traffic environment of modern cities, challenges like insufficient wireless signal coverage and obstructed propagation links between base stations (BS) and vehicles are prevalent. Meanwhile, reconfigurable intelligent surface (RIS) offers what we believe to be a novel solution relying on its robust real-time control over electromagnetic (EM) waves, providing a new approach to achieving intelligent transportation and vehicle connectivity. In this paper, we propose a radar-aided intelligent wireless communication system for dynamic beam tracking. The system leverages frequency-modulated continuous wave (FMCW) radar to detect the location information of the surrounding vehicles, a pre-trained artificial neural network (ANN) combined with control boards to generate the voltage coding sequence of the desired deflection direction, and the dual-polarized RIS to realize intelligent beam tracking and wireless communication. We design a 3-bit dual-polarized RIS, consisting of 256 (16 x 16) independently controllable units, running at 3.5 GHz, and develop a high-speed control board to ensure real-time refresh of the voltage coding sequence. Comparative experiments are conducted in three different environments. The experiments consistently demonstrate that, with the assistance of the radar, the RIS can achieve dynamic beam tracking without manual intervention. The system can effectively improve wireless signal strength and communication stability, providing a new viable approach for the development of intelligent vehicular networking. (c) 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Deep learning Field programmable gate arrays Machine vision Neural networks Phase shift Visible light communications

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Promoting Inshore Ship Detection in SAR Images: A Fourier-Based Scene Transformation and Semantic Enhancement Framework

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2025年 18卷 10055-10074页

作者： Liu, Shuang Li, Dong Wan, Jun Zhan, Muyang Su, Jia Zhu, Hanying Chongqing Univ Sch Microelect & Commun Engn Chongqing 400044 Peoples R China Chongqing Univ Chongqing Key Lab Space Informat Network & Intelli Chongqing 400044 Peoples R China Shanghai Aerosp Elect Technol Inst Shanghai 201109 Peoples R China Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Peoples R China

Deep learning-based synthetic aperture radar (SAR) ship detection approaches have made significant progress, but still face challenges in inshore scenarios. Inshore regions are cluttered with docks, port facilities, and buildings, which exhibit high visual similarity to actual ship targets in SAR images and are major factors that reduce detection accuracy. Mainstream methods typically focus on directly extracting ship target features from inshore scene images. However, such cluttered backgrounds hamper the effectiveness of feature extraction and ultimately decrease detection accuracy. To alleviate this dilemma, we revisit farshore and inshore images in the frequency domain space from a new perspective, and propose a novel Fourier-based scene transformation and semantic enhancement (FSTSE) framework that utilizes farshore target as an explicit prior information to improve inshore SAR ship detection. Specifically, inspired by Fourier properties, a farshore-inshore scene transformation module (Far-In-STM) is proposed. The Far-In-STM enriches the diversity of SAR image background environments by performing scene transformations between farshore and inshore scene images. The resulting transformed image is called the pseudoinshore image. Then, a dual consistency supervision mechanism (Dual-CSM) is designed, which imposes consistency constraints on gradients and prediction distributions between the farshore image and its corresponding pseudoinshore image. The Dual-CSM allows the discriminative semantics of ship targets to be fully captured and explored in complex backgrounds by exploiting the semantic correlation between images. Extensive experiments on several public SAR ship detection datasets indicate that the proposed FSTSE significantly outperforms other methods in inshore ship detection.

关键词： Marine vehicles Feature extraction Radar polarimetry Transformers Semantics Synthetic aperture radar Accuracy Frequency-domain analysis Attention mechanisms Clutter Fourier-based scene transformation inshore SAR ship detection semantic enhancement

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Propagation-aware Q-coverage and Q-connectivity network design in relay-aided IoT sensor systems using heuristic and genetic algorithms

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Neural Computing and Applications 2025年 1-28页

作者： Thang, Nguyen Xuan Hanh, Nguyen Thi Son, Nguyen Van Tan, Nguyen Phuc Hung, To Quang Chien, Trinh Van Binh, Huynh Thi Thanh Faculty of Computer Science Hanoi University Nguyen Trai Hanoi Viet Nam Faculty of Interdisciplinary Digital Technology Phenikaa University Yen Nghia Ha Dong Hanoi12116 Viet Nam Faculty of Computer Science Phenikaa University Yen Nghia Ha Dong Hanoi12116 Viet Nam School of Information and Communication Technology Hanoi University of Science and Technology Dai Co Viet Hanoi Viet Nam

wireless sensor networks play a crucial role in Internet of Things systems, whose development and prevalence have given rise to numerous challenges. One of the most notable problems regarding wireless sensor networks is the sensor deployment problem, where the objective is to minimize the number of nodes used and to satisfy the constraints of coverage and connectivity. In reality, sensors may be prone to errors and failures;therefore, simple coverage and simple connectivity cannot guarantee fault tolerance for a system. This leads to the concepts of Q-coverage and Q-connectivity, which indicates that each target needs q covering sensors and q node-disjoint paths to the base station. To minimize the number of nodes while still ensuring Q-coverage and Q-connectivity, we propose a heuristic algorithm and an algorithm based on the genetic algorithm. Besides, we construct various experiment scenarios and a realistic dataset to evaluate the efficiency of our proposed methods. The experiment results show that our proposed algorithms significantly outperform existing methods in both solution quality and running time. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Connectivity Heuristic algorithm IoT networks Target coverage wireless sensor network

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Exploiting Structured Sparsity in Near Field: From the Perspective of Decomposition

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IEEE communicationS MAGAZINE 2025年第1期63卷 37-43页

作者： Guo, Xufeng Chen, Yuanbin Wang, Ying Yuen, Chau Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Nanyang Singapore

The structured sparsity can be leveraged in traditional far-field channels, greatly facilitating efficient sparse channel recovery by compressing the complexity of overheads to the level of the scatterer number. However, when experiencing a fundamental shift from planar-wave-based far-field modeling to spherical-wave-based near-field modeling, whether these benefits persist in the near-field regime remains an open issue. To answer this question, this article delves into structured sparsity in the near-field realm, examining its peculiarities and challenges. In particular, we present the key features of near-field structured sparsity in contrast to the far-field counterpart, drawing from both physical and mathematical perspectives. Upon unmasking the theoretical bottlenecks, we resort to bypassing them by decoupling the geometric parameters of the scatterers, termed the triple parametric decomposition (TPD) framework. It is demonstrated that our novel TPD framework can achieve robust recovery of near-field sparse channels by applying the potential structured sparsity and avoiding the curse of complexity and overhead.

关键词： Three-dimensional displays Complexity theory Near field communication Telecommunication network management Channel estimation wireless sensor networks Linear antenna arrays 6G mobile communication Switching circuits Spectral efficiency Space division multiplexing MIMO

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Stochastic Event-Triggered Feedback Physical Watermarks Against Replay Attacks

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IEEE TRANSACTIONS ON network SCIENCE AND ENGINEERING 2025年第2期12卷 814-822页

作者： Zhao, Xudong Xing, Wei Wang, Xinyu Zhao, Ning Dalian Univ Technol Key Lab Intelligent Control & Optimizat Ind Equipm Minist Educ Dalian 116024 Peoples R China Hainan Univ Sch Informat & Commun Engn Haikou 570228 Peoples R China Bohai Univ Coll Control Sci & Engn Jinzhou 121010 Peoples R China

This paper considers the security of cyber-physical systems (CPSs) subject to replay attacks with measurements of the sensor transmitted to the remote estimator over a wireless communication network. We present a novel stochastic event-triggered feedback physical watermarking technique to effectively mitigate the impact of replay attacks, while simultaneously addressing the performance degradation caused by the inclusion of physical watermarks. This innovative approach dynamically adjusts the probability of adding physical watermarks based on the system's current operational state, striking a balance between optimal performance and effective countermeasures against replay attacks. And, as a result, the probability of adding physical watermarks increases when the system is subjected to malicious replay attacks. Furthermore, the performances of both the system and the detector are thoroughly characterized in two distinct scenarios: (i) the system operating under normal conditions, and (ii) the system being subjected to replay attacks. These scenarios allow for a comprehensive evaluation of the system's capabilities and the detector's efficacy in detecting and mitigating potential security threats. Finally, simulation examples are provided to corroborate and illustrate the theoretical results.

关键词： Watermarking Event detection Time measurement Detectors System performance Kalman filters Estimation Costs Optimization Denial-of-service attack Cyber-physical systems event-triggered feedback physical watermark replay attacks

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Intelligent Waveform Design for Integrated Sensing and communication

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IEEE wireless communicationS 2025年第1期32卷 166-173页

作者： Zhang, Jifa Guo, Shaoyong Gong, Shiqi Xing, Chengwen Zhao, Nan Ng, Derrick Wing Kwan Niyato, Dusit Dalian Univ Technol Sch Informat & Commun Engn Dalian Peoples R China Dalian Univ Technol Dalian Peoples R China Beijing Univ Posts & Telecommun State Key Lab Net Working & Switching Technol Beijing Peoples R China Beijing Inst Technol Sch Cyberspace Sci & Technol Beijing Peoples R China Beijing Inst Technol Sch Informat & Elect Beijing Peoples R China Univ New South Wales Sydney Australia Nanyang Technol Univ Coll Comp & Data Sci Singapore Singapore

Integrated sensing and communication (ISAC) represents a unified paradigm to enhance spectral efficiency and reduce hardware costs by enabling the coexistence of communication and radar functionalities using the same spectral and hardware resources. Dual-functional (DF) waveform design, as an essential component of ISAC, often entails high-complexity, non-convex optimization algorithms, hindering its practical online deployment. Leveraging the robust predictive capabilities of deep learning (DL) and deep reinforcement learning (DRL), these technologies have emerged as viable and streamlined approaches for the online design of DF waveforms more suitable for the dynamic environment. Thus, in this article, we first provide a comprehensive overview of ISAC, with a particular focused examination of its waveform design. Then, we introduce DL/DRL and highlight its important roles in ISAC, especially in intelligent waveform design. Moreover, we develop DL- and DRL-based algorithms tailored for conventional DF waveform design, and simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS)-aided DF waveform design, respectively. Simulation results verify the effectiveness of the developed algorithms, with emerging research directions presented.

关键词： Radar Hardware Integrated sensing and communication Costs Channel estimation wireless sensor networks wireless communication Heuristic algorithms Autonomous aerial vehicles Training

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An Accountable GAKA Protocol With Changeable Thresholds and Verifiable Shares in UAVs-Assisted IoVs for Emergency Rescue

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年第4期26卷 5522-5537页

作者： Wang, Di Cao, Yue Lam, Kwok-Yan Chi, Chi-Hung Choo, Kim-Kwang Raymond Wuhan Univ Sch Cyber Sci & Engn Key Lab Aerosp Informat Secur & Trusted Comp Minist Educ Wuhan 430072 Peoples R China Nanyang Technol Univ Coll Comp & Data Sci Singapore 639798 Singapore Nanyang Technol Univ Natl Digital Trust Ctr Singapore 639798 Singapore Univ Texas San Antonio Dept Informat Syst & Cyber Secur San Antonio TX 78249 USA

Unmanned aerial vehicles (UAVs) equipped with high line-of-sight communications have been explored as a complement to emergency communication vehicles (ECVs), particularly when ground Internet of Vehicles (IoVs) is dysfunctional resulting from natural disasters. To protect the communication security and integrity of this air-ground integrated networks created in an untrusted and open wireless environment, authentication and key agreement (AKA) is an essential mechanism to establish a secure communication channel by negotiating a session key. Nonetheless, general AKA protocols are typically not ideal for time-sensitive and computing-intensive UAVs-assisted IoVs emergency rescue, in that they are unable to simultaneously satisfy efficiency and key security requirements including accountability, resilience, thresholds changeability, shares verifiability, group adaptability, and key update. To address this challenge, this paper proposes an accountable group authentication and key agreement (GAKA) protocol with changeable thresholds and verifiable shares supporting adaptive group memberships and updatable keys (i.e. SecER). To safeguard accurate rescue decisions for ground ECVs enabled by reliable collaboration among multiple UAVs, we propose a pseudonym mechanism that aims to provide accountability for UAVs. To achieve resilience and thresholds changeability, our SecER utilizes secret sharing coupled with random parameters to seamlessly transform our GAKA protocol into one running with a new threshold in one round (i.e. round-optimal), rather than two rounds. Finally, verifiable parameters and updatable keys are respectively applied to counter deception attacks caused by maliciously distributed shares and to support adaptive network topology (i.e. UAVs joining and leaving). Extensive simulations show that compared to the state-of-the-art approaches, our SecER is superior in balancing security and efficiency.

关键词： Protocols Autonomous aerial vehicles Cryptography Disasters Authentication Resilience Biometrics Air to ground communication Smart cards Privacy Internet of Vehicles secure communication unmanned aerial vehicles group authentication key agreement

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