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42nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2022

作者： Zhang, Ruoyi Deng, Jing Liu, Qi Xie, Xinlei Gong, Qingyuan Zhu, Chao Beijing Institute of Technology School of Cyberspace Science and Technology China Communication University of China State Key Laboratory of Media Convergence and Communication China School of Information and Electronics Beijing Institute of Technology China School of Computer Science Fudan University Shanghai Key Lab of Intelligent Information Processing China

ISBN: (数字)9781665488792

ISBN: (纸本)9781665488792

With the emerging telepresence applications, such as meta universe, tele-education and tele-social, there exist a large number of demands for sufficient network resources for visual streaming. However, transmitting the huge volume of the generated visual data through the meandering terrestrial networks would overwhelm the backbone networks and cause non-negligible latency. Mega-constellations, such as OneWeb and Starlink, is developing as one of 'New Infrastructure Construction', and could provide high-capacity and low-latency communication in a world-wide range. However, most of the existing mega-constellation networks' topology is fixed and would easily fall into congestion with the bursting traffic generated by the large-scale telepresence applications. To address this challenge, we propose a reconfigurable mega-constellation architecture by utilizing the permanent and temporary laser inter-satellite links (LISLs). Moreover, based on the mixed-integer linear programming (MILP), we design a routing system, FlyLISL, aiming at balancing the global traffic load by minimizing the maximum link utilization of all LISLs. To evaluate the effectiveness of FlyLISL, we simulate the performance of FlyLISL by comparing with the particle swarm optimization (PSO) and Random based routing strategies. Compared with reference works, FlyLISL reduces the maximum link utilization by up to 72.6%. © 2022 IEEE.

关键词： Mixed reality

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Designing of Decision Criterion on FCrSK in Time-Frequency Dual Selective Channel 22

Designing of Decision Criterion on FCrSK in Time-Frequency D...

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22nd IEEE International Conference on communication technology, ICCT 2022

作者： Nie, Xiaohong Yang, Chao Wang, Linan Zhang, Jing Zheng, Lin Science and Technology on Communication Networks Laboratory Hebei Shijiazhuang China Guilin University of Electronic Technology Key Lab. of Cognitive Radio and Information Processing Ministry of Education Guilin541004 China

ISBN: (纸本)9781665470674

With the increasement of frequency band and platform mobility, communication system faces more severe time-frequency double dispersion influence. Folded chirp-rate shift keying (FCrSK) modulation technique has been proposed to solve communication transmission problem in high dynamic doppler channel owe to its time-frequency shift invariance. However, it dose not consider some influence of time-frequency dual selective channel (TDSC). In this paper, spectrum structure of FCrSK after dechirp will be deduced in TDSC and a decision criterion for FCrSK is designed from spectral energy concentration to utilize multipath energy. And this decision criterion is more suitable for FCrSK in TDSC than frequency domain peak to average ratio (FPAR). Besides, the system has no rely on channel state information and has better performance at high SNR in TDSC than Lora. Furthermore, it is superior to Lora in and time-varing doppler channel. So FCrSK with this criterion can provide a good way for high reliability and low latency communication in future. © 2022 IEEE.

关键词： Channel state information

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Signal Tensor Model and Eigenvalue Distributions for THz Uplink UM-MIMO communications 15

Signal Tensor Model and Eigenvalue Distributions for THz Upl...

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15th IEEE International Conference on Wireless communications and Signal Processing, WCSP 2023

作者： Qi, Bin Zhang, Wensheng Li, Qiang Sun, Jian Liu, Zhi Wang, Chen Wang, Cheng-Xiang Shandong University Shandong Provincial Key Lab of Wireless Communication Technologies School of Information Science and Engineering Qingdao266237 China Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan430074 China Southeast University National Mobile Communications Research Laboratory School of Information Science and Engineering Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China

ISBN: (纸本)9798350324662

Tensor theory has been widely used in the research field of wireless communications. Tensor eigenvalues are usually considered key parameters of tensors. However, the exact physical or practical meanings of tensor eigenvalues in wireless communications are still unknown. In this paper, we investigate the distributions of tensor eigenvalues for Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) orthogonal frequency division multiplexing (OFDM) systems, in which the channel modeling problem using hybrid beamforming (HBF) is studied, aiming to study the properties of tensor eigenvalues in communication systems. The OFDM pilot is sent by the mobile station (MS) through a precoder with random phases. The received signal at the base station (BS) can be reassembled into a fifth-order tensor that follows CANDECOMP/PARAFAC decomposition (CPD) to represent channel information. The homotopy method is used to calculate all eigenvalues of signal tensors efficiently and accurately. The numerical results show that the non-zero eigenvalues of received signal tensors are distributed sparsely, and the eigenvalue of each tensor is a unique value. © 2023 IEEE.

关键词： CP decomposition Homotopy method Tensor eigenvalue Terahertz communications UM-MIMO

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Self-Supervised Teaching and Learning of Representations on Graphs 23

Self-Supervised Teaching and Learning of Representations on ...

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2023 World Wide Web Conference, WWW 2023

作者： Wan, Liangtian Fu, Zhenqiang Sun, Lu Wang, Xianpeng Xu, Gang Yan, Xiaoran Xia, Feng Key Laboratory for Ubiquitous Network Service Software of Liaoning Province School of Software Dalian University of Technology Dalian China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian China State Key Laboratory of Marine Resource Utilization in South China Sea School of Information and Communication Engineering Hainan University Haikou China State Key Laboratory of Millimeter Waves School of Information Science and Engineering Southeast University Nanjing China Research Center of Big Data Intelligence Research Institute of Artificial Intelligence Zhejiang Lab Hangzhou China School of Computing Technologies Rmit University Melbourne Australia

ISBN: (纸本)9781450394161

Recent years have witnessed significant advances in graph contrastive learning (GCL), while most GCL models use graph neural networks as encoders based on supervised learning. In this work, we propose a novel graph learning model called GraphTL, which explores self-supervised teaching and learning of representations on graphs. One critical objective of GCL is to retain original graph information. For this purpose, we design an encoder based on the idea of unsupervised dimensionality reduction of locally linear embedding (LLE). Specifically, we map one iteration of the LLE to one layer of the network. To guide the encoder to better retain the original graph information, we propose an unbalanced contrastive model consisting of two views, which are the learning view and the teaching view, respectively. Furthermore, we consider the nodes that are identical in muti-views as positive node pairs, and design the node similarity scorer so that the model can select positive samples of a target node. Extensive experiments have been conducted over multiple datasets to evaluate the performance of GraphTL in comparison with baseline models. Results demonstrate that GraphTL can reduce distances between similar nodes while preserving network topological and feature information, yielding better performance in node classification. © 2023 ACM.

关键词： Classification (of information)

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Characterizing Kerr Optical Frequency Combs Using Quantum Interference

Characterizing Kerr Optical Frequency Combs Using Quantum In...

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2023 Asia communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Guo, Jin Fan, Yun-Ru Geng, Yong Deng, Guang-Wei Song, Hai-Zhi Wang, You You, Li-Xing Wang, Zhen Zhou, Heng Qiu, Kun Guo, Guang-Can Zhou, Qiang University of Electronic Science and Technology of China Key Lab of Optical Fiber Sensing and Communication Networks Chengdu China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Southwest Institute of Technical Physics Chengdu China Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu China University of Science and Technology of China Cas Key Laboratory of Quantum Information Hefei China

For the first time, we characterize the properties of Kerr optical frequency combs using quantum optics. The temporal FWHM of single soliton state is obtained as l109.8pm 6.5 fs within the Fourier transform limit. ... 详细信息

ISBN: (纸本)9798350312614

关键词： HOM interferometer Kerr optical frequency combs quantum interference

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Traditional Chinese Medicine Automated Diagnosis Based on Knowledge Graph Reasoning

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Computers, Materials & Continua 2022年第4期71卷 159-170页

作者： Dezheng Zhang Qi Jia Shibing Yang Xinliang Han Cong Xu Xin Liu Yonghong Xie School of Computer&Communication Engineering University of Science&Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Inspur Electronic Information Industry Co. Ltd.&State Key Laboratory of High-End Server&Storage TechnologyJinan250101China Surgical Simulation Research Lab Department of SurgeryUniversity of AlbertaEdmontonT6G 2E1AlbertaCanada

Syndrome differentiation is the core diagnosis method of Traditional Chinese Medicine(TCM).We propose a method that simulates syndrome differentiation through deductive reasoning on a knowledge graph to achieve automated diagnosis in *** analyze the reasoning path patterns from symptom to syndromes on the knowledge *** are two kinds of path patterns in the knowledge graph:one-hop and *** one-hop path pattern maps the symptom to syndromes *** two-hop path pattern maps the symptom to syndromes through the nature of disease,etiology,and pathomechanism to support the diagnostic *** the different support strengths for the knowledge paths in reasoning,we design a dynamic weight *** utilize Naïve Bayes and TF-IDF to implement the reasoning method and the weighted score *** proposed method reasons the syndrome results by calculating the possibility according to the weighted score of the path in the knowledge graph based on the reasoning path *** evaluate the method with clinical records and clinical practice in *** preliminary results suggest that the method achieves high performance and can help TCM doctors make better diagnosis decisions in ***,the method is robust and explainable under the guide of the knowledge *** could help TCM physicians,especially primary physicians in rural areas,and provide clinical decision support in clinical practice.

关键词： Traditional Chinese medicine automated diagnosis knowledge graph Naïve Bayes syndrome differentiation

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A Hybrid Genetic Algorithm for Hierarchical Routing in Wireless Sensor Networks 1

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13th International Conference on information Systems and Advanced Technologies, ICISAT 2023

作者： Messiaid, Abd Essalam Bezziane, Mohamed Ben Brik, Bouziane Kettouche, Souhila Benguenane, Messaoud Siham, Hasan Sami, Lemtenneche LINATI Laboratory Department of Computer Science Faculty of New Technologies of Information and Communication University of Kasdi Merbah Ouargla Algeria Computer Science Department College of Computing and Information Sharjah University Sharjah United Arab Emirates Lab. of Computer Science Larbi Ben M’hidi University Oum Elbouaghi Algeria Faculty of Technology De Montfort University Gateway House LeicesterLE1 9BH United Kingdom

ISBN: (数字)9783031605949

ISBN: (纸本)9783031605932

Data transmission in wireless sensor networks (WSNs) is recognized as an interesting field of research due to the specificities of this type of network, where energy consumption is considered one of the major challenges of communication protocol options. Hierarchical data routing in Wireless Sensor Networks (WSNs) represents a distinct category of routing protocols. This category includes approaches that implement a reorganization of the physical network into a logical hierarchy system, aimed at optimizing energy consumption. In this paper, we propose a new scheme named Genetic-Firefly (GF) for the Hierarchical routing based on the hybridization of the genetic algorithm to select an alternative of cluster heads (CHs) with the firefly bio-inspired technique that allows forming clusters. The simulation of GF and the Low Energy Adaptive Clustering Hierarchy protocol (LEACH) has proved that our proposal has achieved good results in terms of the energy consumed, network lifetime, and received data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Energy utilization

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DAFT-Spread Affine Frequency Division Multiple Access for Downlink Transmission

DAFT-Spread Affine Frequency Division Multiple Access for Do...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Tao, Yiwei Wen, Miaowen Ge, Yao Mao, Tianqi Xiao, Lixia Li, Jun South China University of Technology School of Electronic and Information Engineering Guangzhou510641 China Nanyang Technological University Continental-NTU Corporate Lab 639798 Singapore Beijing Institute of Technology Miit Key Laboratory of Complex-Field Intelligent Sensing Beijing100081 China Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan430074 China Guangzhou University School of Electronics and Communication Engineering Guangzhou510006 China

ISBN: (纸本)9798350351255

Affine frequency division multiplexing (AFDM) and orthogonal AFDM access (O-AFDMA) are promising techniques based on chirp signals, which are able to suppress the performance deterioration caused by Doppler shifts in high-mobility scenarios. However, the high peak-to-average power ratio (PAPR) in AFDM or O-AFDMA is still a crucial problem, which severely limits their practical applications. In this paper, we propose a discrete affine Fourier transform (DAFT)-spread AFDMA scheme based on the properties of the AFDM systems, named DAFT-s-AFDMA to significantly reduce the PAPR by resorting to the DAFT. We formulate the transmitted time-domain signals of the proposed DAFT-s-AFDMA schemes with localized and interleaved chirp subcarrier allocation strategies. Accordingly, we derive the guidelines for setting the DAFT parameters, revealing the insights of PAPR reduction. Finally, simulation results of PAPR comparison in terms of the complementary cumulative distribution function (CCDF) show that the proposed DAFT-s-AFDMA schemes with localized and interleaved strategies can both attain better PAPR performances than the conventional O-AFDMA scheme. © 2024 IEEE.

关键词： Distribution functions

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Reinforcement Learning Based Dynamic Spectrum Access in Cognitive Internet of Vehicles

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China communications 2021年第7期18卷 58-68页

作者： Xin Liu Can Sun Mu Zhou Bin Lin Yuto Lim School of Information and Communication Engineering Dalian University of TechnologyDalian 116024China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China Department of Communication Engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian 116026China School of Information Science Japan Advanced Institute of Science and TechnologyIshikawa 923-1292Japan

Cognitive Internet of Vehicles(CIoV)can improve spectrum utilization by accessing the spectrum licensed to primary user(PU)under the premise of not disturbing the PU’s ***,the traditional static spectrum access makes the CIoV unable to adapt to the various spectrum *** this paper,a reinforcement learning based dynamic spectrum access scheme is proposed to improve the transmission performance of the CIoV in the licensed spectrum,and avoid causing harmful interference to the *** frame structure of the CIoV is separated into sensing period and access period,whereby the CIoV can optimize the transmission parameters in the access period according to the spectrum decisions in the sensing *** both detection probability and false alarm probability,a Q-learning based spectrum access algorithm is proposed for the CIoV to intelligently select the optimal channel,bandwidth and transmit power under the dynamic spectrum states and various spectrum sensing *** simulations have shown that compared with the traditional non-learning spectrum access algorithm,the proposed Q-learning algorithm can effectively improve the spectral efficiency and throughput of the CIoV as well as decrease the interference power to the PU.

关键词： cognitive Internet of vehicles reinforcement learning dynamic spectrum access Q-learning spectral efficiency

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Scloud+: An Efficient LWE-Based KEM Without Ring/Module Structure 9th

Scloud+: An Efficient LWE-Based KEM Without Ring/Module Stru...

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9th International Conference on Security Standardisation Research, SSR 2024

作者： Wang, Anyu Zheng, Zhongxiang Zhao, Chunhuan Qiu, Zhiyuan Zeng, Guang Yuan, Ye Mu, Changchun Wang, Xiaoyun Institute for Advanced Study BNRist Tsinghua University Beijing China School of Computer and Cyber Sciences Communication University of China Beijing China Shield Lab Huawei Technologies Beijing China Shandong Institute of Blockchain Jinan China Digital Currency Institute the People’s Bank of China China Zhongguancun Laboratory Beijing China National Financial Cryptography Research Center Beijing China Key Laboratory of Cryptologic Technology and Information Security School of Cyber Science and Technology Shandong University Qingdao China

ISBN: (纸本)9783031875403

We present Scloud+, an LWE-based key encapsulation mechanism (KEM). The key feature of Scloud+ is its use of the unstructured-LWE problem (i.e., without algebraic structures such as rings or modules) and its incorporation of ternary secrets and lattice coding to enhance performance. A notable advantage of the unstructured-LWE problem is its resistance to potential attacks exploiting algebraic structures, making it a conservative choice for constructing high-security schemes. However, a key disadvantage of such schemes is their limited computational and communication efficiency. Scloud+ utilizes ternary secrets and BW32 lattice codes to enhance noise control and ensure robust error correction during decryption, enabling smaller parameters while maintaining low decryption failure probabilities. Equipped with these techniques, Scloud+ exhibits a significant improvement in efficiency. When compared with FrodoKEM for parameter sets targeting 128, 192, and 256 bits of security respectively, Scloud+ achieves practical performance with a public key size approximately 0.71∼0.87x and a ciphertext size approximately 0.56∼0.78x that of FrodoKEM. The encapsulation plus decapsulation time is approximately 0.74∼0.84x that of FrodoKEM. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Quantum cryptography

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