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Networks, communications and Intelligent Computing (NCIC), International Conference on

作者： Jie Lu Yuexia Zhang Junjie Li Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350371949

ISBN: (纸本)9798350371956

Since the advancement of mobile communication technology, traditional industries are gradually transforming and upgrading, which leads to problems such as insufficient computing resources and excessive energy consumption of Internet of Things (IoT) devices. To address this issue, a resource allocation algorithm for the mobile edge computing-assisted industrial IoT (IIoT) is proposed. First, a mobile edge computing-assisted IIoT network model was constructed. Using the collaboration between IoT devices, mobile edge computing (MEC) servers, and cloud servers, the issue of minimizing all IIoT devices energy cost was proposed. Subsequently, in order to address the optimization issue, obtain its optimal solution, the alternating direction method of multipliers (ADMM) algorithm is introduced. Finally, the ADMM algorithm's convergence was verified through an experimental simulation. In contrast to baseline algorithm 1 and algorithm 2, the ADMM algorithm can significantly diminish energy cost, proving the effectiveness of the proposed scheme.

关键词： Energy consumption Cloud computing Costs Computational modeling Convex functions Servers Resource management

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Frequency Agile Strategy Design of Radar Network for Wideband Sweep Jamming via Coalition Formation Game

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Liao, Maosen Xiong, Kui Zhang, Long Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China School of Information and Communication Engineering Chengdu611731 China UESTC Shenzhen Institute for Advanced Study Chengdu611731 China

This article proposes an intelligent frequency agile design strategy for radar network using coalition game theory to counter wideband sweep jamming, which is formulated as a two-stage decision-making problem. In the first stage, the entire frequency agile range is divided into several non-overlapping agile subrange, and each radar selects a frequency agile subrange to join, which is solved by the coalition formation algorithm. Then, after achieving a stable coalition partition, a distributed multi-agent reinforcement learning algorithm is developed to address the specific carrier frequency selection problem within each coalition. By combining these two stages of the frequency agile design strategy, a joint coalition formation game and distributed Q-learning algorithm (CFDQ) is proposed. Finally, numerical simulations are conducted to illustrate the superiority of the proposed algorithm over several typical frequency agile strategies. © 1965-2011 IEEE.

关键词： Jamming

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Joint Optimization of UAV Deployment and Directional Antenna Orientation for Multi-UAV Cooperative Sensing

Joint Optimization of UAV Deployment and Directional Antenna...

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IEEE Conference on Wireless communications and Networking

作者： Lingyun Zhou Wenqiang Pu Ming-yi You Rongqing Zhang Qingjiang Shi School of Software Engineering Tongji University Shanghai China Shenzhen Research Institute of Big Data Shenzhen China Science and Technology on Communication Information Security Control Laboratory Jiaxing China

In this paper, we consider the problem of cooperative sensing via a system of multi-unmanned aerial vehicles (UAVs), where each UAV is equipped with a directional antenna to cooperatively perform detection tasks for several targets of interest. To measure the perception ability of the system, we choose the detection probability as the metric, aiming to maximize the sum detection probability of targets by jointly optimizing UAVs’ deployment and directional antenna orientations. To tackle the inherent nonconvexity of the formulated problem, we first decompose it into two sub-problems, i.e., a slave problem for optimizing the antenna orientations with a given UAVs’ deployment, and a master problem for optimizing the UAVs’ deployment. By virtue of the slave problem structure, an efficient block coordinate descent (BCD) algorithm is developed. Meanwhile, to deal with the lack of the closed expression of the sum detection probability with respect to the UAVs’ deployment, we further develop an iterative algorithm to acquire an efficient solution with the aid of Gibbs Sampling (GS) approach. Extensive simulations demonstrate the efficacy of the proposed algorithm.

关键词： Antenna measurements Directional antennas Autonomous aerial vehicles Sensors Iterative methods Task analysis Optimization

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Trusted source noise model of discrete-modulated continuous-variable quantum key distribution

arXiv

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arXiv 2024年

作者： Wu, Mingze Li, Junhui Xu, Bingjie Yu, Song Zhang, Yichen State Key Laboratory of Information Photonics and Optical Communications School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing100876 China Science and Technology on Security Communication Laboratory Institute of Southwestern Communication Chengdu610041 China

Discrete-modulated continuous-variable quantum key distribution offers a pragmatic solution, greatly simplifying experimental procedures while retaining robust integration with classical optical communication. Theoretical analyses have progressively validated the comprehensive security of this protocol, paving the way for practical experimentation. However, imperfect source in practical implementations introduce noise. The traditional approach is to assume that eavesdroppers can control all of the source noise, which overestimates the ability of eavesdroppers and underestimates secret key rate. In fact, some parts of source noise are intrinsic and cannot be manipulated by eavesdropper, so they can be seen as trusted noise. We tailor a trusted model specifically for the discrete-modulated protocol and upgrade the security analysis accordingly. Simulation results demonstrate that this approach successfully mitigates negative impact of imperfect source on system performance while maintaining security of the protocol. Furthermore, our method can be used in conjunction with trusted detector noise model, effectively reducing the influence of both source and detector noise in experimental setup. This is a meaningful contribution to the practical deployment of discrete-modulated continuous-variable quantum key distribution systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum cryptography

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A Robust Two-Dimensional DOA Estimation Approach Based on Convolutional Attention Network

A Robust Two-Dimensional DOA Estimation Approach Based on Co...

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International Joint Conference on Neural Networks (IJCNN)

作者： Rui Xiao Ming–Yi You Rui Zhou Qingjiang Shi School of Software Engineering Tongji University Shanghai China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Shenzhen Research Institute of Big Data Shenzhen China

The direction of arrival (DOA) estimation of the signal is an important task in radio signal positioning. Various methods have been investigated to cope with the DOA task. However, since the imperfect interference factors are often present in practical antenna arrays, the performance of DOA estimation is often significantly degraded. Besides, few methods deal with the DOA estimation for signals of multiple frequencies. In this paper, we consider the problem of two-dimensional DOA estimation in the presence of imperfect factors, and propose a novel approach where the convolutional attention network is used for DOA estimation. The frequency information is introduced as a token added to the network, which improves the network robustness while taking into account the case of the signal of multiple frequencies. Besides, we extend the mean square error (MSE) to the design of a new loss function for training to improve the accuracy of the model. The advantages of the proposed DOA estimation scheme are demonstrated through numerical experiments.

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A Collaborative Jamming Algorithm Based on Multi-UAV Scheduling

A Collaborative Jamming Algorithm Based on Multi-UAV Schedul...

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International Conference on communication technology (ICCT)

作者： Yixin Jiang Lingyun Zhou Yijia Tang Ya Tu Chunhong Liu Qingjiang Shi School of Software Engineering Tongji University Shanghai China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Shenzhen Research Institute of Big Data Shenzhen China

In this paper, we consider the problem of multi-unmanned aerial vehicles' (UAVs), scheduling for cooperative jamming, where UAVs equipped with directional antennas perform collaborative jamming tasks against several targets of interest. To ensure effective jamming towards the targets, we formulate it as an non-convex optimization problem, aiming to minimize the communication performance of the targets by jointly optimizing UAVs' deployment and directional antenna orientations. Due to the unique structure of the problem, we derive an equivalent transformation by introducing a set of auxiliary matrices. Subsequently, we propose an efficient iterative algorithm based on the alternating direction method of multi-pliers (ADMM), which decomposes the problem into multiple tractable subproblems solved in closed-form or by gradient projection method. Extensive simulations validate the efficacy of the proposed algorithm.

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Tunable Cascaded Trisection Bandpass Filter with Constant Absolute Bandwidth 13

Tunable Cascaded Trisection Bandpass Filter with Constant Ab...

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13th International Conference on Microwave and Millimeter Wave technology, ICMMT 2021

作者： Yang, JingJing Xiang, Qianyin Jia, Dinghong Huang, Xiaoguo Feng, Quanyuan Southwest Jiaotong University School Of Information Science And Technology Chengdu611756 China He 41st Institute Of CETC Qingdao266555 China Science And Technology On Communication Information Security Control Laboratory Jiaxing314033 China

ISBN: (纸本)9781665434379

A novel cascade trisection (CT) coupling structure based on half-wavelength resonators is proposed for designing constant absolute bandwidth (CABW) tunable bandpass filters. Third-order tunable bandpass filter (BPF) which can realize CABW and a high side cross coupling transmission zero (Tz) is designed based on the proposed CT structure. Measurement results show that the central frequency tuning range of desinged filter is from 1.47 GHz to 1.83 GHz with -3dB bandwidth of 108.75±2.05 MHz, and the high side 3dB to 25dB attenuation slope is 327.32623.57 dB/GHz. © 2021 IEEE.

关键词： Bandwidth

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Hybrid Beamforming Design for Bistatic Integrated Sensing and communication Systems

arXiv

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arXiv 2025年

作者： Mao, Tianhao Yang, Jie Liang, Le Jin, Shi National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

Integrated sensing and communication (ISAC) in millimeter wave is a key enabler for next-generation networks, which leverages large bandwidth and extensive antenna arrays, benefiting both communication and sensing functionalities. The associated high costs can be mitigated by adopting a hybrid beamforming structure. However, the well-studied monostatic ISAC systems face challenges related to full-duplex operation. To address this issue, this paper focuses on a three-dimensional bistatic configuration that requires only half-duplex base stations. To intuitively evaluate the error bound of bistatic sensing using orthogonal frequency division multiplexing waveforms, we propose a positioning scheme that combines angle-of-arrival and time-of-arrival estimation, deriving the closed-form expression of the position error bound (PEB). Using this PEB, we develop two hybrid beamforming algorithms for joint waveform design, aimed at maximizing achievable spectral efficiency (SE) while ensuring a predefined PEB threshold. The first algorithm leverages a Riemannian trust-region approach, achieving superior performance in terms of global optima and convergence speed compared to conventional gradient-based methods, but with higher complexity. In contrast, the second algorithm, which employs orthogonal matching pursuit, offers a more computationally efficient solution, delivering reasonable SE while maintaining the PEB constraint. Numerical results are provided to validate the effectiveness of the proposed designs. Copyright © 2025, The Authors. All rights reserved.

关键词： Orthogonal frequency division multiplexing

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PathMLP: Smooth Path Towards High-order Homophily

arXiv

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arXiv 2023年

作者： Zhou, Jiajun Xie, Chenxuan Gong, Shengbo Qian, Jiaxu Yu, Shanqing Xuan, Qi Yang, Xiaoniu Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China Binjiang Institute of Artificial Intelligence Hangzhou310056 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou310023 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

Real-world graphs exhibit increasing heterophily, where nodes no longer tend to be connected to nodes with the same label, challenging the homophily assumption of classical graph neural networks (GNNs) and impeding their performance. Intriguingly, from the observation of heterophilous data, we notice that certain high-order information exhibits higher homophily, which motivates us to involve high-order information in node representation learning. However, common practices in GNNs to acquire high-order information mainly through increasing model depth and altering message-passing mechanisms, which, albeit effective to a certain extent, suffer from three shortcomings: 1) oversmoothing due to excessive model depth and propagation times;2) high-order information is not fully utilized;3) low computational efficiency. In this regard, we design a similarity-based path sampling strategy to capture smooth paths containing high-order homophily. Then we propose a lightweight model based on multi-layer perceptrons (MLP), named PathMLP, which can encode messages carried by paths via simple transformation and concatenation operations, and effectively learn node representations in heterophilous graphs through adaptive path aggregation. Extensive experiments demonstrate that our method outperforms baselines on 16 out of 20 datasets, underlining its effectiveness and superiority in alleviating the heterophily problem. In addition, our method is immune to over-smoothing and has high computational efficiency. The source code will be available in https://***/Graph4Sec-Team/PathMLP. Copyright © 2023, The Authors. All rights reserved.

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An Electromagnetic Signal Classification Method Inspired by the Visual Characteristics of Biological Dual-Channel

SSRN

引用

SSRN 2022年

作者： Dai, Shaogang Zhou, Huaji Science and Technology on Communication Information Security Control Laboratory Jiaxing314000 China School of communication engineering Hangzhou Dianzi University Hangzhou310018 China

Automatic modulation classification of electromagnetic signals has an important role in the field of civil and military signal processing, for which research is mainly based on deep learning methods. However, existing deep learning models generally suffer from problems such as network redundancy and non-interpretability. Since the biological visual system has extraordinary visual signal recognition ability, and the system has been widely studied at the micro (neuron), mesoscopic (visual pathway) and macro (visual cortex) levels, this paper constructs a biological dual-channel visual neural network (BDVNN) inspired by the visual characteristics of biological dual-channel for efficient classification of the electromagnetic signals. The input part of BDVNN simulates the dual-channel structure of lateral geniculate nucleus (LGN), building a dual-channel parallel module composed of convolution kernels of different scales to extract the overall coarse features and local fine features from the input signal, respectively. The dual-channel module internally uses atrous convolution to simulate the sparse coding characteristics of LGN, aiming to reduce the model parameters as well as increase the recognition efficiency. The middle part of BDVNN simulates the fusion of primary visual cortex receptive fields to fuse coarse features with fine features, which facilitates the further extraction of advanced features in subsequent layers of the network. In the setting of the number of network layers, the BDVNN model refers to the biological visual pathway hierarchy to meet the lightweight characteristics so as to significantly reduce the training cost. For the RadioML2016.10a dataset, the recognition accuracy of BDVNN is 9.73%, 92.45% and 93.64% under the signal-to-noise ratio of -20dB, 2dB and 18dB, respectively, with 2%~17% improvement over the rest of mainstream algorithms. For the ACARS dataset, the average recognition accuracy of BDVNN for 20 signals is 95.2%, which is also bett

关键词： Network layers

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