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International Conference on Communications, Signal Processing, and systems, CSPS 2018

作者： Zhao, Juan Xu, Xiaolong Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9789811362637

Both the power and the information are transmitted wirelessly, respectively, in downlink and uplink traffics for spatial-division multiple access networks. The receiver in uplink is equipped with multiple antennas to support the multiple access *** the first frequency band, the transmitter sends power wirelessly to multiple users at the same time. In the second frequency band, all the users utilize the received power, respectively, to send information wirelessly to the receiver (the same node in the downlink). The objective is to achieve the best energy efficiency over the whole networks while assuring the required quality of service in terms of the minimum throughput over all the unlink traffics. The unknown parameter is the transmit power in downlink. The difficulty is to deal with the hard derivations over the closed-form solution to the complicated problem. The proposed method successfully obtains the optimal solution in terms of the closed form. Numerical simulations verify the good performance achieved by our proposed method. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Power transmission

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Relation Classification based on Selective Entity-Aware Attention 25

Relation Classification based on Selective Entity-Aware Atte...

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Ding, Haijie Xu, Xiaolong Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Jiangsu Nanjing China

ISBN: (纸本)9781665405270

Relation classification aims to classify the entity pairs into a certain relation, which is an important task of natural language processing. The latest end-to-end models based on attention mechanism still have shortcomings, i.e., the attention will be gradually weakened when processing long sequences, and they cannot make use of the hidden type information of the entities. To solve these problems, we propose a relation classification model based on the selective entity-aware attention mechanism, which consists of context encoder and entity-aware attention network. In the context encoder, contextual word semantics are learned through self-attention. Entity selection is applied to adapt the fact that different words can determine each other's importance. Latent types of entities are taken as auxiliary information to make full use of the entities' hidden features. Experiments on the SemEval-2010 Task 8 dataset and TACRED show that our model outperforms the baselines without implementing any external resources or NLP tools, and the entity-aware attention indeed improve the model's performance. © 2022 IEEE.

关键词： Semantics

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Economical Electricity Supplement for Mobile Collectors in Large-Scale Multitask WSNs 21

Economical Electricity Supplement for Mobile Collectors in L...

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21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International Conference on Big data and Cloud Computing, 16th IEEE International Conference on Social Computing and Networking and 13th International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zhai, Xin Xu, Lijie Zhang, Jialei Wang, Kun Xu, Jia Xu, Bei Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China

ISBN: (纸本)9798350329223

For large-scale multitask wireless sensor networks (LSM-WSNs), the traditional data collection mode could suffer low energy-efficiency on data transmission, since the large-scale multitask scenarios could result in much higher packet collision probability, especially for harsh environments. Mobile data collection is an efficient data acquisition way to prolong network lifetime for LSM-WSNs. However, the mobile collectors could suffer electricity shortage problem, since the limited battery capacity of any mobile collector could not afford the energy consumption of its long-distance movement and massive data collection in large-scale multitask scenarios. Deploying wireless chargers to supplement the energy of mobile collectors is a feasible solution to electricity shortage problem, but will incur extra charger deployment cost. In this paper, we focus on the problem that how to optimize such charger deployment cost, which is NP-hard. By transforming it into minimum-cost submodular cover problem, we devise an efficient approximation algorithm with a provable approximation ratio. The extensive simulation results reveal that our solution always outperforms the other solutions under whatever configurations. © 2023 IEEE.

关键词： Wireless sensor networks

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VECSim: A Simulation Platform for Multi-bitrate Video Caching Collaboratively in Edge Computing Network 25

VECSim: A Simulation Platform for Multi-bitrate Video Cachin...

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Chen, Peipei Xu, Xiaolong Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Jiangsu Nanjing China

ISBN: (纸本)9781665405270

The development of the mobile Internet has led to a shape increase in video traffic data. New Mobile Edge Computing (MEC) technology can reduce network operation and service delivery delays, so as to improving the QoE (Quality of Experience) of user. In MEC environment, this article builds a simulation platform for multi-bitrate video caching and scheduling scenarios VECSim (Video Edge CloudSim). VECSim provides a simulation environment specific to verify multi-bitrate video caching collaboratively and scheduling strategy in the Mobile Edge Computing scenarios. Unlike simple numerical simulations and complex real-world deployments, VECSim provides a simple interface that can be called by the user, besides, it can be used to provide larger-scale, more flexible request scenarios which are closer to the actual environment. Based on the edge computing simulation platform EdgeCloudSim, this platform adds and modifies quite a few functions so that it can be effectively used in multi-bitrate video caching and scheduling scenarios, which now includes seven main modules: Server Management Modules, Network Module, User Mobility Module, Task Loader Generator Module, Video Storage Module, Edge Client Management Module, and Edge Orchestrator Module. With this platform, researchers can easily and quickly verify their video caching and scheduling strategies. © 2022 IEEE.

关键词： Mobile edge computing

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FortisAVQA and MAVEN: a Benchmark dataset and Debiasing Framework for Robust Multimodal Reasoning

arXiv

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arXiv 2025年

作者： Ma, Jie Gao, Zhitao Chai, Qi Liu, Jun Wang, Pinghui Tao, Jing Su, Zhou Ministry of Education of Key Laboratory for Intelligent Networks and Network Security School of Cyber Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China Shannxi Provincial Key Laboratory of Big Data Knowledge Engineering School of Computer Science and Technology Xi’an Jiaotong University Shaanxi Xi’an710049 China Guangdong Guangzhou510000 China

Audio-Visual Question Answering (AVQA) is a challenging multimodal reasoning task requiring intelligent systems to answer natural language queries based on paired audio-video inputs accurately. However, existing AVQA approaches often suffer from overfitting to dataset biases, leading to poor robustness. Moreover, current datasets may not effectively diagnose these methods. To address these challenges, we first introduce a novel dataset, FortisAVQA, constructed in two stages: (1) rephrasing questions in the test split of the public MUSIC-AVQA dataset and (2) introducing distribution shifts across questions. The first stage expands the test space with greater diversity, while the second enables a refined robustness evaluation across rare, frequent, and overall question distributions. Second, we introduce a robust Multimodal Audio-Visual Epistemic Network (MAVEN) that leverages a multifaceted cycle collaborative debiasing strategy to mitigate bias learning. Experimental results demonstrate that our architecture achieves state-of-the-art performance on FortisAVQA, with a notable improvement of 7.81%. Extensive ablation studies on both datasets validate the effectiveness of our debiasing components. Additionally, our evaluation reveals the limited robustness of existing multimodal QA methods. We also verify the plug-and-play capability of our strategy by integrating it with various baseline models across both datasets. Our dataset and code are available at https://***/reml-group/fortisavqa. Copyright © 2025, The Authors. All rights reserved.

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AISLE: Self-supervised Representation Learning for the Investigation of Advanced Persistent Threat 7

AISLE: Self-supervised Representation Learning for the Inves...

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7th IEEE International Conference on data Science in Cyberspace, DSC 2022

作者： Jia, Zian Wang, Xiaosu Xiong, Yun Zhang, Yao Zhao, JinJing Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China National Key Laboratory of Science and Technology on Information System Security China

ISBN: (数字)9781665474801

ISBN: (纸本)9781665474801

Advanced Persistent Threats (APT) are difficult to detect and defend due to their high variability and concealment. Current APT detection and investigation approaches suffer from two major problems. First, most recent models heavily rely on heuristic rules derived from a large amount of expensive prior knowledge, which in turn prevents the models from generalizing to new types of APT attacks. Second, the development of existing fully supervised models is limited by the scarcity of APT attack data. In this paper, we first construct the provenance graph by introducing logical entities to reduce the dependency on prior knowledge. Then we propose a novel self-supervised representation-learning based model, AISLE, for the investigation of the APT attack, which consists of a graph structure encoder (GSE) and an entity interaction pattern encoder (IPE). The GSE employs a graph attention auto-encoder to effectively compress the structural information of the graph;and the IPE employs a LSTM auto-encoder to extract the interaction patterns of entities from their interaction history. The two entity embeddings calculated respectively by the two auto-encoders are concatenated to form the final representation of the entity, which is evaluated by the attack investigation module to identify attack entities. Our model is evaluated on ten real-world APT attacks in a realistic virtual environment. The results show that our model can achieve superior generalization ability and consistently outperform the latest state-of-the-art APT attack investigation approaches. © 2022 IEEE.

关键词： Graph neural networks

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A Tutorial on Movable Antennas for Wireless Networks

arXiv

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arXiv 2025年

作者： Zhu, Lipeng Ma, Wenyan Mei, Weidong Zeng, Yong Wu, Qingqing Ning, Boyu Xiao, Zhenyu Shao, Xiaodan Zhang, Jun Zhang, Rui Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Chengdu611731 China National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Electronic and Information Engineering Beihang University Beijing100191 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada State Key Laboratory of CNS/ATM MIIT Key Laboratory of Complex-field Intelligent Sensing Beijing Institute of Technology Beijing100081 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China

Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fixed antennas (FAs) to MAs offers tremendous new opportunities towards realizing more versatile, adaptive and efficient next-generation wireless networks such as 6G. In this paper, we provide a comprehensive tutorial on the fundamentals and advancements in the area of MA-empowered wireless networks. First, we overview the historical development and contemporary applications of MA technologies. Next, to characterize the continuous variation in wireless channels with respect to antenna position and/or orientation, we present new field-response channel models tailored for MAs, which are applicable to narrowband and wideband systems as well as far-field and near-field propagation conditions. Subsequently, we review the state-of-the-art architectures for implementing MAs and discuss their practical constraints. A general optimization framework is then formulated to fully exploit the spatial degrees of freedom (DoFs) in antenna movement for performance enhancement in wireless systems. In particular, we delve into two major design issues for MA systems. First, we address the intricate antenna movement optimization problem for various communication and/or sensing systems to maximize the performance gains achievable by MAs. Second, we deal with the challenging channel acquisition issue in MA systems for reconstructing the channel mapping between arbitrary antenna positions inside the transmitter and receiver regions. Moreover, we show existing prototypes developed for MA-aided communication/sensing and the experimental results based on them. Finally, the extension of MA design to other wireless systems and its synergy with other emerging wireless technologies are discussed. We also highlight promising research directions in this area to inspire future investigatio

关键词： Antenna arrays

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Transfer learning with active queries for relational data modeling across multiple information networks 25th

Transfer learning with active queries for relational data mo...

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25th International Conference on Neural Information Processing, ICONIP 2018

作者： Chen, Ke-Jia Zhang, Kai Jiang, Xi-Lin Wang, Yunyun Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications NanjingJiangsu210023 China

ISBN: (纸本)9783030041816

This paper studies the relationship prediction problem in multi-network scenarios, aiming to overcome the network sparsity challenge where the labeled data (connected node pairs) are much less than the unlabeled data (unconnected node pairs). The TAQIL framework is proposed by using transfer learning to get knowledge from the related source networks and then use active learning to query the labels of the most informative instances from the oracle in the target network. A new query function is also proposed in order to better use the parameters output by the transfer learning method. The alternate use of transfer learning and active learning allows adaptive transfer of knowledge across multiple networks to mitigate cold start and meantime improve the prediction accuracy with active queries in the target network. The experimental results on both non-network datasets and network datasets demonstrate the significant improvement in prediction accuracy compared with several benchmark methods and related state-of-art methods. © Springer Nature Switzerland AG 2018.

关键词： Forecasting

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Higher order implicit CNDG-PML algorithm for left-handed materials

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Journal of systems Engineering and Electronics 2021年第1期32卷 31-37页

作者： CHEN Yanfang WANG Liwei School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing Tianjin Zhongwei Aerospace Data System Technology Co.Ltd.Tianjin 300450China

By incorporating the higher order concept,the piecewise linear recursive convolution(PLRC)method and CrankNicolson Douglas-Gunn(CNDG)algorithm,the unconditionally stable complex frequency shifted nearly perfectly matched layer(CFS-NPML)is proposed to terminate the left-handed material(LHM)*** proposed scheme takes advantages of CFSNPML formulation,the higher order concept PLRC method and the unconditionally stable CNDG algorithm in terms of absorbing performance,computational efficiency,calculation accuracy and convenient implementation.A numerical example is carried out to demonstrate the effectiveness and efficiency of the proposed *** results indicate that the proposed scheme can not only have considerable absorbing performance but also maintain the unconditional stability of the algorithm with the enlargement of time steps.

关键词： complex frequency shifted nearly perfectly matched layer(CFS-NPML) Crank-Nicolson Douglas-Gunn(CNDG) left-handed material(LHM) piecewise linear recursive convolution(PLRC)

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Attacks Against Cross-Chain systems and Defense Approaches:A Contemporary Survey

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1647-1667页

作者： Li Duan Yangyang Sun Wei Ni Weiping Ding Jiqiang Liu Wei Wang IEEE the Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong UniversityBeijing 100044China the Guangxi Key Laboratory of Cryptography and Information Security Guilin 541004China the Communications and Signal Processing Team Data61 Business UnitCommonwealth Scientific and Industrial Research Organisation(CSIRO)Sydney NSW 2109Australia the School of Information Science and Technology Nantong UniversityNantong 226019China

The blockchain cross-chain is a significant technology for inter-chain interconnection and value transfer among different blockchain ***-chain overcomes the“information island”problem of the closed blockchain network and is increasingly applied to multiple critical areas such as finance and the internet of things(IoT).Blockchain can be divided into three main categories of blockchain networks:public blockchains,private blockchains,and consortium ***,there are differences in block structures,consensus mechanisms,and complex working mechanisms among heterogeneous *** fragility of the cross-chain system itself makes the cross-chain system face some potential security and privacy *** paper discusses security defects on the cross-chain implementation mechanism,and discusses the impact of the structural features of blockchain networks on cross-chain *** terms of cross-chain intercommunication,a cross-chain attack can be divided into a multi-chain combination attack,native chain attack,and inter-chain attack *** various security threats and attack paths faced by the cross-chain system are *** last,the corresponding security defense methods of cross-chain security threats and future research directions for cross-chain applications are put forward.

关键词： Blockchain cross-chain defense distributed private key control hash-locking notary security threats sidechain/relay

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