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Joint Deployment and Resource Allocation for Multi-AeBS Networks: A Two-Timescale Optimization Framework Using MADRL

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IEEE Transactions on Communications 2024年

作者： Zhao, Yikun Zhou, Fanqin Feng, Lei Sun, Yao Li, Wenjing Lim, Wei Yang Bryan Xiong, Zehui Mao, Shiwen Han, Zhu State Key Laboratory of Networking and Switching Technology Beijing100876 China University of Glasgow James Watt School of Engineering GlasgowG12 8QQ United Kingdom Nanyang Technological University Alibaba Group and Alibaba-NTU Joint Research Institute Singapore Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore487372 Singapore Auburn University Department of Electrical and Computer Engineering AuburnAL36849 United States University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

As an important component of the space-air-ground integrated network, aerial base station (AeBS) systems have gained significant attention for their flexibility in mobility and cost-effective construction. Nevertheless, the scarce spectrum resources and difficulty in accessing global information bring necessity and challenges to the deployment and resource allocation of AeBSs. In this paper, we propose a practical two-timescale framework to solve the resource allocation and deployment optimization problem in multi-AeBS networks. Specifically, the subcarrier allocation problem is first transformed into a many-to-one matching game coupled with power allocation and solved in a small timescale. Then, in a large timescale, the AeBS deployment subproblem is transformed into a distributed partially observable Markov decision process (Dec-POMDP), and then a novel multi-agent hypergraph convolutional deep reinforcement learning (MAHGCDRL) is proposed to solve this problem. The proposed MAHGCDRL extracts features of neighboring AeBSs through hypergraph convolutional networks, enabling AeBS agents to achieve better coordination in a distributed manner. Simulation results show that our proposed approach can attain a higher sum rate, and the proposed MAHGCDRL algorithm achieves better learning performance compared to the existing benchmarks in the literature. © 1972-2012 IEEE.

关键词： Deep reinforcement learning

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Multiple Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV

Multiple Redundant Weighted Clustered Scheme with Dynamic We...

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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Grace Khayat Constandinos X Mavromoustakis Jordi Mongay Batalla Andreas Pitsillides Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Warsaw University of Technology Warsaw Poland Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor)

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the routing algorithms that S-UAVs utilize the most frequently is clustering, where UAVs are divided into clusters. Each cluster consists of a cluster head (CH) and cluster members (CM). The selection of the CH is a topic of continuous research because of its crucial significance in inter-cluster communication. We propose a clustered weighted method with dynamic weight modification and redundancy to ensure end-to-end communication despite non-functional CH. Interspace, speed, and performance indicators are combined into a weighted metric that is used to select the CH, redundant CHs, and CMs. The suggested technique optimizes UAV role selection by dynamically and autonomously adjusting the weights. Based on the results of the executed simulation, this is a promising strategy that minimizes data loss in an emergency situation and minimizes delay.

关键词： Measurement Conferences Computational modeling Redundancy Clustering algorithms Autonomous aerial vehicles Routing Routing protocols Delays Vehicle dynamics

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DDPS: Dynamic Differential Pricing-Based Edge Offloading System With Energy Harvesting Devices

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IEEE Transactions on Network Science and engineering 2025年

作者： Xue, Hai Xia, Yun Xiong, Neal N. Zhang, Di Pei, Songwen University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Sul Ross State University Department of Computer Science and Mathematics AlpineTX79830 United States Zhengzhou University School of Electrical and Information Engineering Zhengzhou450001 China Zhengzhou University Henan International Joint Laboratory of Intelligent Health Information System Zhengzhou450001 China Zhengzhou University National Engineering Laboratory for Internet Medical Systems and Applications Zhengzhou450001 China

Mobile edge computing (MEC) mitigates the energy and computation burdens on mobile users (MUs) by offloading tasks to the network edge. To optimize MEC server utilization through effective resource allocation, a well-designed pricing strategy is indispensable. In this paper, we propose a dynamic differential pricing scheme (DDPS) for an edge offloading scenario with energy harvesting devices, which determines prices based on computing resource usage to enhance edge server (ES) utilization. First, an offloading decision algorithm is proposed to balance harvested and consumed energy, determining whether and how much data to offload. Second, a Stackelberg game-based differential pricing algorithm is proposed to optimize computing resource allocation for MUs and reallocate surplus resources to delay-sensitive devices. Extensive simulations are conducted to demonstrate the effectiveness of the proposed DDPS scheme. Specifically, in comparison to the existing best-performing pricing scheme, for different task arrival rates, DDPS can achieve a 5.3% decrease in average execution delay, a 1.7% increase in ES utility (Userver, which represents the payment from MUs minus penalties for discarded tasks), and a 2.1% increase in the average ratio of service for MUs. In addition, DDPS also improves 2.8% Userver on average with different ES computation capacities. © 2025 IEEE. All rights reserved.

关键词： Mobile edge computing

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Robust Control of Feeding Speed for Coal Mine Tunnel Drilling Machines

Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Xiao Liu Luefeng Chen Min Wu Weihua Cao Chengda Lu Witold Pedrycz School of Automation China University of Geosciences Wuhan China School of Automation the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and the Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Department of Computer Engineering Istinye University Sariyer/Istanbul Turkey

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed.

关键词： Drilling Robust control Uncertainty Robust stability Simulation Coal Resonance

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BihoT: A Large-Scale Dataset and Benchmark for Hyperspectral Camouflaged Object Tracking

arXiv

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arXiv 2024年

作者： Wang, Hanzheng Li, Wei Xia, Xiang-Gen Du, Qian The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Beijing Key Laboratory of Fractional Signals and Systems Beijing100081 China The Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States The Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States

Hyperspectral object tracking (HOT) has exhibited potential in various applications, particularly in scenes where objects are camouflaged. Existing trackers can effectively retrieve objects via band regrouping because of the bias in existing HOT datasets, where most objects tend to have distinguishing visual appearances rather than spectral characteristics. This bias allows the tracker to directly use the visual features obtained from the false-color images generated by hyperspectral images without the need to extract spectral features. To tackle this bias, we find that the tracker should focus on the spectral information when object appearance is unreliable. Thus, we provide a new task called hyperspectral camouflaged object tracking (HCOT) and meticulously construct a large-scale HCOT dataset, termed BihoT, which consists of 41,912 hyperspectral images covering 49 video sequences. The dataset covers various artificial camouflage scenes where objects have similar appearances, diverse spectrums, and frequent occlusion, making it a very challenging dataset for HCOT. Besides, a simple but effective baseline model, named spectral prompt-based distractor-aware network (SPDAN), is proposed, comprising a spectral embedding network (SEN), a spectral prompt-based backbone network (SPBN), and a distractor-aware module (DAM). Specifically, the SEN extracts spectral-spatial features via 3-D and 2-D convolutions to form a refined prompt representation. Then, the SPBN fine-tunes powerful RGB trackers with spectral prompts and alleviates the insufficiency of training samples. Moreover, the DAM utilizes a novel statistic to capture the distractor caused by occlusion from objects and background and corrects the deterioration of the tracking performance via a novel motion predictor. Extensive experiments demonstrate that our proposed SPDAN achieves state-of-the-art performance on the proposed BihoT and other HOT datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Network embeddings

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case

Optimal Linear Deception Attacks on Remote State Estimation ...

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IEEE Conference on Decision and Control

作者： Jun Shang Hanwen Zhang Jing Zhou Tongwen Chen Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack’s stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback–Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples.

关键词： Wireless communication Measurement Technological innovation System performance Kalman filters State estimation Intelligent sensors

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SSF-Net: Spatial-Spectral Fusion Network with Spectral Angle Awareness for Hyperspectral Object Tracking

arXiv

引用

arXiv 2024年

作者： Wang, Hanzheng Li, Wei Xia, Xiang-Gen Du, Qian Tian, Jing School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Fractional Signals and Systems Beijing100081 China Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States

Hyperspectral video (HSV) offers valuable spatial, spectral, and temporal information simultaneously, making it highly suitable for handling challenges such as background clutter and visual similarity in object tracking. However, existing methods primarily focus on band regrouping and rely on RGB trackers for feature extraction, resulting in limited exploration of spectral information and difficulties in achieving complementary representations of object features. In this paper, a spatialspectral fusion network with spectral angle awareness (SST-Net) is proposed for hyperspectral (HS) object tracking. Firstly, to address the issue of insufficient spectral feature extraction in existing networks, a spatial-spectral feature backbone (S2FB) is designed. With the spatial and spectral extraction branch, a joint representation of texture and spectrum is obtained. Secondly, a spectral attention fusion module (SAFM) is presented to capture the intra- and inter-modality correlation to obtain the fused features from the HS and RGB modalities. It can incorporate the visual information into the HS spectral context to form a robust representation. Thirdly, to ensure a more accurate response of the tracker to the object position, a spectral angle awareness module (SAAM) investigates the region-level spectral similarity between the template and search images during the prediction stage. Furthermore, we develop a novel spectral angle awareness loss (SAAL) to offer guidance for the SAAM based on similar regions. Finally, to obtain the robust tracking results, a weighted prediction method is considered to combine the HS and RGB predicted motions of objects to leverage the strengths of each modality. Extensive experiments on the HOTC dataset demonstrate the effectiveness of the proposed SSF-Net, compared with state-of-the-art trackers. Copyright © 2024, The Authors. All rights reserved.

关键词： Extraction

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Energy-Efficient Federated Learning-enabled Digital Twin in UAV-aided Vehicular Networks

Energy-Efficient Federated Learning-enabled Digital Twin in ...

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Asia-Pacific Conference on Communications

作者： Giang H. Pham Hoang D. Le Thanh V. Pham Chuyen T. Nguyen Anh T. Pham Computer Communications Laboratory The University of Aizu Japan Department of Mathematical and Systems Engineering Shizuoka University Japan School of Electrical and Electronic Engineering Hanoi University of Science and Technology Vietnam

Federated learning (FL)-enabled digital twin (DT) has recently attracted research attention to bring intelligent applications. However, enabling the FL-enabled DT in vehicular networks becomes challenging due to vehicle mobility’s impact on communication channels. In this regard, we propose to deploy an unmanned aerial vehicle (UAV) as a relay node to support the vehicular network. The objective is to minimize energy consumption under the trade-off with the latency and accuracy constraints of the DT model via a joint optimization of local accuracy, the local computation frequency, relay decision, and transmission power. To do so, we derive instantaneous formulas to update the accuracy and latency constraints, then solve the proposed problem using an iterative algorithm with convex optimization techniques. Numerical results show that the proposed dynamic optimization for UAV-aided vehicular networks can reduce up to 39.9% of consumption energy compared to conventional methods.

关键词：

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Orthogonal matrix of polarization combinations:concept and application to multichannel holographic recording

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Opto-Electronic Advances 2024年第10期7卷 4-13页

作者： Shujun Zheng Jiaren Tan Hongjie Liu Xiao Lin Yusuke Saita Takanori Nomura Xiaodi Tan Information Photonics Research Center College of Photonic and Electronic EngineeringFujian Normal UniversityFuzhou 350117China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA College of Photonic and Electronic Engineering Key Laboratory of Opto-Electronic Science and for Medicine of Ministry of EducationFujian Provincial Key Laboratory of Photonics TechnologyFujian Provincial Engineering Technology Research Center of Photoelectric Sensing ApplicationFujian Normal UniversityFuzhou 350117China Faculty of Systems Engineering Wakayama University930 SakaedaniWakayama640-8510Japan.

Orthogonal matrices have become a vital means for coding and signal processing owing to their unique distributional *** orthogonal matrices based on amplitude or phase combinations have been extensively explored,the orthogonal matrix of polarization combinations(OMPC)is a novel,relatively unexplored ***,we propose a method for constructing OMPCs of any dimension encompassing 4n(where n is 1,2,4,8,…)mutually orthogonal 2ncomponent polarization *** the field of holography,the integration of polarization multiplexing techniques with polarization-sensitive materials is expected to emerge as a groundbreaking approach for multichannel hologram multiplexing,offering considerable enhancements in data storage capacity and security.A multidimensional OMPC enables the realization of multichannel multiplexing and dynamical modulation of information in polarization holographic *** consolidating all information into a single position within the material,we effectively avoided extraneous crosstalk during the reconstruction *** results show that achieving four distinct holographic images individually and simultaneously depends on the polarization combination represented by the incident *** discovery opens up a new avenue for achieving highly holographic information storage and dynamically displayed information,harnessing the potential of OMPC to expand the heretofore limited dimensionality of orthogonal polarization.

关键词： orthogonal matrix of polarization combinations polarization-modulated multiplexing multichannel recording polarization holography dynamical information modulation

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Maximum Power Point Tracking Based on Crayfish Optimization Algorithm for Photovoltaic systems Operating Under Partial Shading Conditions

Maximum Power Point Tracking Based on Crayfish Optimization ...

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electrical engineering and Automatic Control (ICEEAC), International Conference on

作者： Abdelghani Draoui Ahmed Saidi Oubelaid Adel Mohammed Amine Meziane Boumediene Allaoua Abdrabbi Bourezg Department of Computer Science Laboratory of Environmental and Energy Systems (LSEE) University Center of Ali Kafi Tindouf Algeria Department of Electrical Engineering Laboratory of Sustainable Development and Computer Science University of Ahmed Draria Adrar Algeria Laboratoire de Technologie Industrielle de l'information Faculté de Technologie Bejaia University Bejaia Algeria Department of Electrical Engineering University center of Naama Naama Algeria Department of Electrical Engineering University of Tahri Mohamed Bechar Bechar Algeria Department of Electrical Engineering Dubai Men's College Higher Colleges of Technology Dubai Algeria

ISBN: (数字)9798350349740

ISBN: (纸本)9798350349757

The clean and renewable nature of energy harvested using the Photovoltaic (PV) technology makes it one the fastest growing technologies used in producing electricity. Due to the relatively low efficiency of the various solar cells available in the market, solar trackers and Maximum Power Point Tracking (MPPT) algorithms are used extensively to operate the system at its full potentials. Knowing that such systems are installed in outdoor spaces, they are inevitably subjected to partial shading conditions, where different parts of the system are subjected to different levels of solar irradiance. In case of occurrence of partial shading conditions on a PV system equipped with bypass diodes, the Power-Voltage (P-V) curve will have multiple peaks. This multi-peak curve requires using a sophisticated algorithm to track the Global Maximum Power Point (GMPP) instead of being deceived and trapped in a Local Maximum Power Point (LMPP). In this paper, the Crayfish Optimization Algorithm (COA) is suggested to track the GMPP of a PV system under partial shading conditions. The COA algorithm fetch for the GMPP by reading the PV panel output power and setting accordingly the duty cycle of the buck converter. Simulation is carried out using the MATLAB/Simulink platform and results demonstrate good tracking performance and prove the robustness of the system against rapid variations in solar irradiance levels.

关键词： Maximum power point trackers Solar irradiance Photovoltaic systems Renewable energy sources Microcontrollers Photovoltaic cells Robustness

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