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Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

China Communications 2024年第4期21卷 38-52页

作者： Jiang Fan Qin Junwei Liu Lei Tian Hui School of Communications and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy co

关键词： associative tasks cache-aided procedure double deep Q-network Internet of Medical Things(IoMT) multi-access edge computing(MEC)

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Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

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China Communications 2024年第1期21卷 131-147页

作者： Shuo Liu Pan Tang Jianhua Zhang Yue Yin Yu Tong Baobao Liu Guangyi Liu Liang Xia state key laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China China Mobile Research Institute Beijing 100053China

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)***,channel modeling is the foundation for designing efficient and robust VLC *** this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a *** on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical *** on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial ***,the simulated statistics of the proposed model are compared with the measured *** instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,***,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,***,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

关键词： channel characteristics channel measurement channel modeling 6G spatial lobe VLC

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Network Configuration Entity Extraction Method Based on Transformer with Multi-Head Attention Mechanism

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Computers, Materials & Continua 2024年第1期78卷 735-757页

作者： Yang Yang Zhenying Qu Zefan Yan Zhipeng Gao Ti Wang state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing100876China Product Development Department China Unicom Smart City Research InstituteBeijing100044China

Nowadays,ensuring thequality of networkserviceshas become increasingly *** are turning toknowledge graph technology,with a significant emphasis on entity extraction in the identification of device *** research paper presents a novel entity extraction method that leverages a combination of active learning and attention ***,an improved active learning approach is employed to select the most valuable unlabeled samples,which are subsequently submitted for expert *** approach successfully addresses the problems of isolated points and sample redundancy within the network configuration sample *** the labeled samples are utilized to train the model for network configuration entity ***,the multi-head self-attention of the transformer model is enhanced by introducing the Adaptive Weighting method based on the Laplace mixture *** enhancement enables the transformer model to dynamically adapt its focus to words in various positions,displaying exceptional adaptability to abnormal data and further elevating the accuracy of the proposed *** comparisons with Random Sampling(RANDOM),Maximum Normalized Log-Probability(MNLP),Least Confidence(LC),Token Entrop(TE),and Entropy Query by Bagging(EQB),the proposed method,Entropy Query by Bagging and Maximum Influence Active Learning(EQBMIAL),achieves comparable performance with only 40% of the samples on both datasets,while other algorithms require 50% of the ***,the entity extraction algorithm with the Adaptive Weighted Multi-head Attention mechanism(AW-MHA)is compared with BILSTM-CRF,Mutil_Attention-Bilstm-Crf,Deep_Neural_Model_NER and BERT_Transformer,achieving precision rates of 75.98% and 98.32% on the two datasets,*** tests demonstrate the statistical significance and effectiveness of the proposed algorithms in this paper.

关键词： Entity extraction network configuration knowledge graph active learning transformer

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SNR-adaptive deep joint source-channel coding scheme for image semantic transmission with convolutional block attention module

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The Journal of China Universities of Posts and Telecommunications 2024年第1期31卷 1-11页

作者： Yang Yujia Liu Yiming Zhang Wenjia Zhang Zhi state key laboratory of networking and Switch technology Beijing University of Posts and TelecommunicationsBeijing 100876China

With the development of deep learning(DL),joint source-channel coding(JSCC)solutions for end-to-end transmission have gained a lot of *** deep JSCC schemes support dynamically adjusting the rate according to different channel conditions during transmission,enhancing robustness in dynamic wireless ***,most of the existing adaptive JSCC schemes only consider different channel conditions,ignoring the different feature importance in the image processing and *** uniform compression of different features in the image may result in the compromise of critical image details,particularly in low signal-to-noise ratio(SNR)*** address the above issues,in this paper,a dual attention mechanism is introduced and an SNR-adaptive deep JSCC mechanism with a convolutional block attention module(CBAM)is proposed,in which matrix operations are applied to features in spatial and channel dimensions *** proposed solution concatenates the pooling feature with the SNR level and passes it sequentially through the channel attention network and spatial attention network to obtain the importance evaluation *** show that the proposed solution outperforms other baseline schemes in terms of peak SNR(PSNR)and structural similarity(SSIM),particularly in low SNR scenarios or when dealing with complex image content.

关键词： semantic communication joint source-channel coding image transmission

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Dual-band dynamic reconfigurable intelligent surface for signal enhancement in millimeter wave

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Science China(Technological Sciences) 2024年第4期67卷 1133-1138页

作者： YAO HuiMing DU XinRun WANG HengBin GAO Song PANG YaChen ZHENG HaiRong GONG HuiWen LI Yi XU JianChun ZHANG JianHua BI Ke state key laboratory of Information Photonics and Optical Communications School of ScienceBeijing University of Posts and TelecommunicationsBeijing 100876China Beijing key laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and TelecommunicationsBeijing 100876China state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China

Millimeter wave with large bandwidth,high transmission rate,and low delay is considered a reliable alternative to cope with the spectrum ***,the fast attenuation and narrow beam characteristics make it difficult to achieve long-distance or wide-range ***,a 1-bit dual-band reflective reconfigurable intelligent surface(RIS)for signal enhancement in millimeter wave with 16×16 elements is designed,fabricated,and *** from most existent RIS,dynamic programming is realized at two separate frequency bands by integrating the PIN diodes and field-programmable gate array(FPGA).Particularly,the beam deflection,dual-beam,and multi-beam are created based on the coding theory and convolution operation,proving the effectiveness of wavefront ***,the far-field patterns and signal power with different coding sequences are measured and *** is indicated that the received signal power is 6–7 dB stronger than that without coding,which shows good agreement with the desired *** proposed reconfigurable metasurface exhibits great potential in beam forming,making it a promising candidate for progressive wireless communication applications.

关键词： dual-band millimeter wave reconfigurable intelligent surface signal enhancement

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FL-EASGD:Federated Learning Privacy Security Method Based on Homomorphic Encryption

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Computers, Materials & Continua 2024年第5期79卷 2361-2373页

作者： Hao Sun Xiubo Chen Kaiguo Yuan Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China

Federated learning ensures data privacy and security by sharing models among multiple computing nodes instead of plaintext ***,there is still a potential risk of privacy leakage,for example,attackers can obtain the original data through model inference ***,safeguarding the privacy of model parameters becomes *** proposed solution involves incorporating homomorphic encryption algorithms into the federated learning ***,the existing federated learning privacy protection scheme based on homomorphic encryption will greatly reduce the efficiency and robustness when there are performance differences between parties or abnormal *** solve the above problems,this paper proposes a privacy protection scheme named Federated Learning-Elastic Averaging Stochastic Gradient Descent(FL-EASGD)based on a fully homomorphic encryption ***,this paper introduces the homomorphic encryption algorithm into the FL-EASGD scheme to preventmodel plaintext leakage and realize privacy security in the process ofmodel ***,this paper designs a robust model aggregation algorithm by adding time variables and constraint coefficients,which ensures the accuracy of model prediction while solving performance differences such as computation speed and node anomalies such as downtime of each *** addition,the scheme in this paper preserves the independent exploration of the local model by the nodes of each party,making the model more applicable to the local data ***,experimental analysis shows that when there are abnormalities in the participants,the efficiency and accuracy of the whole protocol are not significantly affected.

关键词： Federated learning homomorphic encryption privacy security stochastic gradient descent

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Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

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China Communications 2024年第2期21卷 227-244页

作者： Meng Meng Bo Hu Shanzhi Chen Jianyin Zhang state key Lab of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China state key Lab of Wireless Mobile Communication China Academy of Telecommunication TechnologyBeijing 100191China Research Institute of China Mobile Beijing 100053China

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system *** optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method ***, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

关键词： convex optimization intelligent reflecting surface LEO satellite communication OFDM

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Semantic information processing for interoperability in the Industrial Internet of Things

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Fundamental Research 2024年第1期4卷 8-12页

作者： Shengshi Yao Yanpeng Lu Kai Niu Jincheng Dai Chao Dong Ping Zhang key laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China The state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China

With the advent of the Internet of Everything(IoE),the concept of fully interconnected systems has become a reality,and the need for seamless communication and interoperability among different industrial systems has become more pressing than ever *** address the challenges posed by massive data traffic,we demonstrate the potentials of semantic information processing in industrial manufacturing processes and then propose a brief framework of semantic processing and communication system for industrial *** particular,the scheme is featured with task-orientation and collaborative *** illustrate its applicability,we provide examples of time series and images,as typical industrial data sources,for practical tasks,such as lifecycle estimation and surface defect *** results show that semantic information processing achieves a more efficient way of information processing and exchanging,compared to conventional methods,which is crucial for handling the demands of future interconnected industrial networks.

关键词： Semantic communication Intelligent manufacturing Signal processing Industrial Internet Task-oriented communication

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Design Framework of Unsourced Multiple Access for 6G Massive IoT

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China Communications 2024年第1期21卷 1-12页

作者： Chunlin Yan Siying Lyu Sen Wang Yuhong Huang Xiaodong Xu China Mobile Communication Research Institute Beijing 100053China ZGC Institute of Ubiquitous-X Innovation and Applications Beijing 100080China state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating *** a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

关键词： channel coding compressed sensing massive Internet-of-Things(IoT) sparse interleaverdivision multiple access(SIDMA) the sixth generation(6G)mobile communications unsourced multiple access

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Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

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China Communications 2024年第4期21卷 104-119页

作者： Huang Xiaoge Yin Hongbo Cao Bin Wang Yongsheng Chen Qianbin Zhang Jie School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Communication and Information Engineering University of SheffieldUnited Kingdom

Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)*** ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus *** to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious ***,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network *** results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.

关键词： blockchain energy consumption fog computing network Internet of Things latency

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