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Cross-modal communication technology: A survey

Fundamental Research 2024年

作者： Wei, Xin Wu, Dan Zhou, Liang Guizani, Mohsen School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing 210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China College of Communications Engineering Army Engineering University of PLA Nanjing 210007 China Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi 999041 United Arab Emirates

In the 5G era and beyond, multi-modal services that integrate audio, visual, and haptic signals are expected to become dominant applications. To support multi-modal services, the concept of cross-modal communications, which involves collaborative audio-visual and haptic interactions, has emerged. Despite significant research about cross-modal communication technology being conducted, a comprehensive literature review on this topic is lacking. To fill this gap, this paper presents a detailed survey on cross-modal communication technology. First, it provides a highly summarized description of representative research attempts in audio-visual and haptic communications, which serve as the foundation for cross-modal communications. Then, it delves into various aspects of cross-modal communications, including architectural, cross-modal coding, cross-modal transmission, cross-modal signal reconstruction, the essence of semantics, and prototype systems. Finally, it discusses conclusions and future research directions. This paper is expected to promote the theoretical research and practical applications of cross-modal communications. © 2023

关键词： Audio-visual Cross-modal communications Haptic Multi-modal service Semantics

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A Smart Content Caching and Replacement Scheme for UAV-Assisted Fog Computing network

A Smart Content Caching and Replacement Scheme for UAV-Assis...

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International Conference on wireless communications and Signal Processing (WCSP)

作者： Xujie Li Jichang Shen Ying Sun Ziya Wang Xuedong Zheng College of Computer and Information Engineering Hohai University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Key Lab for Wireless Sensor network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Nanjing China-Spacenet Satellite Telecom Co.Ltd China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

For unmanned aerial vehicle (UAV)-assisted fog computing system, content caching is an effective way to reduce network delay. How to smartly sense the future requirement of the user equipment and cache the contents in advance is a big challenge. Meanwhile, the impact of cache content size and other related factors on cache performance are often overlooked, which results in low cache hit ratio. Therefore, this paper proposes a smart caching and caching replacement scheme based on valuation function of content caching for UAV-assisted fog computing network. Firstly, the effect of the content popularity, content size and available cache storage space on system performance is analysed. Then the valuation function combing these factors is defined. Based on the presented valuation function, a smart content caching and caching replacement scheme for UAV-assisted fog computing network is proposed. Finally, the simulation results validate the effectiveness of the proposed scheme. The scheme can be applied into the design the deployment of the UVA-assisted fog computing network.

关键词： Edge computing Cost accounting Unmanned aerial vehicles Performance evaluation Delays Indexes Quality of service

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Traffic Matrix Prediction in SDN based on Spatial-Temporal Residual Graph Convolutional network

Traffic Matrix Prediction in SDN based on Spatial-Temporal R...

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Chinese Control and Decision Conference, CCDC

作者： Xintong Wang Yibo Sun Xuan Wang Enliang Wang Zhixin Sun Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China School of Information Technology and Electrical Engineering The University of Queensland Brisbane Brisbane Australia

Traffic prediction is the basis for dynamic network services and resource optimization. Software Defined networking (SDN) provides a global view for network measurement and management, and a reliable way for network information collection and network traffic prediction. Recently, SDN traffic prediction model enabled by deep learning mainly focuses on mining the temporal correlation of traffic data, while the modeling of its spatial correlation remains to be explored. From the perspective of the problem, a novel Spatial-Temporal Residual Graph Convolutional network (STRGCN) model for SDN Traffic Matrix (TM) prediction is proposed. Combined with SDN network topology, TM prediction is defined as time series data prediction in non-Euclidean space. Temporal Gated-Conv Blocks are based on Gated Convolutional Layer, and Spatial Graph-Conv Blocks are based on Graph Convolutional network (GCN). Through identity mapping between Spatial-Temporal Conv Blocks, the deep spatial and temporal features extraction is implemented. Tested by TM data from CERNET and GÉANT datasets, the accuracy and the timely performance of our model are evaluated. Experimental results suggest that the general performance of STRGCN for TM prediction in SDN is superior to the current deep learning models.

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A WOA Based Switching PID Control for Overhead Crane

A WOA Based Switching PID Control for Overhead Crane

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Chinese Control Conference (CCC)

作者： Haoyong Yu Zhe Sun Yuhua Xu Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

Aiming at the problem that the amplitude of load oscillation is not easy to control in the movement process of overhead crane, this paper designs a switching PID control method based on whale optimization algorithm(WOA) to improve the performance of position control and anti-swing control for overhead crane. WOA is used to better adjust the parameters of PID controllers. The switching control is realized by a switching module, which defaults to the output of the Position PID Controller to provide control force for the trolley. When the absolute value of the load swing angle fed back by the crane system exceeds the warning value, the switching module immediately blocks the output of the Position PID Controller, and uses the Angle PID Controller to determine the control force. In addition, through theoretical analysis and simulation experiments under different conditions, the results verify the effectiveness of the WOA based switching control in position control and anti-swing control for overhead crane. Improve the efficiency and safety of overhead crane in practical industrial applications.

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LQR Control Method based on Improved Antlion Algorithm

LQR Control Method based on Improved Antlion Algorithm

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Chinese Control Conference (CCC)

作者： Zhe Sun Zhi Wen Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

In the face of the increasing demand of crane transportation speed and stability, an improved Ant-lion algorithm is proposed in this paper. On the original basis, the quasi-reverse learning method is used to improve the stability of the algorithm and make the initial data distributed evenly. Furthermore, an elite ant-lion growth mechanism is introduced to accelerate the convergence speed of the simulation and improve the simulation accuracy. Finally, the proposed algorithm is verified in the double pendulum system of crane based on LQR controller, and the feasibility and effectiveness of the proposed algorithm are proved by experiments.

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Delay Optimization Based on Improved Differential Evolutionary Algorithm for Task Offloading in Fog Computing networks

Delay Optimization Based on Improved Differential Evolutiona...

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International Conference on wireless communications and Signal Processing (WCSP)

作者： Xujie Li Guangzhao Zhang Xuedong Zheng Siyang Hua College of Computer and Information Hohai University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Key Lab for Wireless Sensor network and Communication Chinese Academy of Sciences Shanghai China Nanjing China-Spacenet Satellite Telecom Co. Ltd Nanjing China Talent Science and Technology Co. Ltd Nanjing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

With the rapid development of communication technology, more and more devices tend to be intelligent. Intelligent devices with computing functions can provide computing services to reduce total task completion time in fog computing networks. This paper aims at minimizing the total task completion time to study multi-user multi-node multi-task offloading problem. Firstly, the task offloading process of task node and fog node is modeled. Then, the system function of the total task completion time is constructed and an optimization problem with constraints is generated. The problem is NP-hard and difficult to be solved by traditional methods. Finally, the improved differential evolution (IDE) algorithm is used to solve the task offloading problem. Simulation results show that it has better performance and can significantly shorten the total task completion time compared with other algorithms.

关键词： Task analysis Delays Computational modeling Edge computing Optimization Signal to noise ratio wireless communication

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Deep learning for the design of non-Hermitian topolectrical circuits

arXiv

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arXiv 2024年

作者： Chen, Xi Sun, Jinyang Wang, Xiumei Jiang, Hengxuan Zhu, Dandan Zhou, Xingping College of Integrated Circuit Science and Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Portland Institute Nanjing University of Posts and Telecommunications Nanjing210003 China College of Electronic and Optical Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Institute of AI Education Shanghai East China Normal University Shanghai200333 China Institute of Quantum Information and Technology Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing210003 China

Non-Hermitian topological phases can produce some remarkable properties, compared with their Hermitian counterpart, such as the breakdown of conventional bulk-boundary correspondence and the non-Hermitian topological edge mode. Here, we introduce several algorithms with multi-layer perceptron (MLP), and convolutional neural network (CNN) in the field of deep learning, to predict the winding of eigenvalues non-Hermitian Hamiltonians. Subsequently, we use the smallest module of the periodic circuit as one unit to construct high-dimensional circuit data features. Further, we use the Dense Convolutional network (DenseNet), a type of convolutional neural network that utilizes dense connections between layers to design a non-Hermitian topolectrical Chern circuit, as the DenseNet algorithm is more suitable for processing high-dimensional data. Our results demonstrate the effectiveness of the deep learning network in capturing the global topological characteristics of a non-Hermitian system based on training data. © 2024, CC BY.

关键词： Eigenvalues and eigenfunctions

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Photonic Modes Prediction via Multi-Modal Diffusion Model

arXiv

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arXiv 2024年

作者： Sun, Jinyang Chen, Xi Wang, Xiumei Zhu, Dandan Zhou, Xingping Portland Institute Nanjing University of Posts and Telecommunications Nanjing210003 China College of Integrated Circuit Science and Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China College of Electronic and Optical Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Institute of AI Education Shanghai East China Normal University Shanghai200333 China Institute of Quantum Information and Technology Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing210003 China

The concept of photonic modes is the cornerstone in optics and photonics, which can describe the propagation of the light. The Maxwell's equations play the role in calculating the mode field based on the structure information, while this process needs a great deal of computations, especially in the handle with a three-dimensional model. To overcome this obstacle, we introduce the Multi-Modal Diffusion model to predict the photonic modes in one certain structure. The Contrastive Language–Image Pre-training (CLIP) model is used to build the connections between photonic structures and the corresponding modes. Then we exemplify Stable Diffusion (SD) model to realize the function of optical fields generation from structure information. Our work introduces Multi-Modal deep learning to construct complex mapping between structural information and light field as high-dimensional vectors, and generates light field images based on this mapping. © 2024, CC BY.

关键词： Maxwell equations

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Secure and Efficient Signature Scheme Based on NTRU for Mobile Payment

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Journal of Physics: Conference Series 2017年第1期910卷

作者： Yunhao Xia Lirong You Zhe Sun Zhixin Sun Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing P. R. China Zhongtian Technology Corporation Nantong P. R. China

Mobile payment becomes more and more popular, however the traditional public-key encryption algorithm has higher requirements for hardware which is not suitable for mobile terminals of limited computing resources. In addition, these public-key encryption algorithms do not have the ability of anti-quantum computing. This paper researches public-key encryption algorithm NTRU for quantum computation through analyzing the influence of parameter q and k on the probability of generating reasonable signature value. Two methods are proposed to improve the probability of generating reasonable signature value. Firstly, increase the value of parameter q. Secondly, add the authentication condition that meet the reasonable signature requirements during the signature phase. Experimental results show that the proposed signature scheme can realize the zero leakage of the private key information of the signature value, and increase the probability of generating the reasonable signature value. It also improve rate of the signature, and avoid the invalid signature propagation in the network, but the scheme for parameter selection has certain restrictions.

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A Normalization Model for Analyzing Multi-Tier Millimeter Wave Cellular networks

arXiv

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arXiv 2017年

作者： Xiong, Siqing Wang, Lijun Kwak, Kyung Sup Bai, Zhiquan Wang, Jiang Li, Qiang Han, Tao School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China School of Electronic Information Wuhan University Wuhan China Faculty of information science and technology Wenhua College Wuhan China Department of Information and Communication Inha university Incheon Korea Republic of School of Information Science and Engineering Shandong University Jinan China Shanghai Research Center for Wireless Communications Shanghai China Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Key lab of wireless sensor network and communication Chinese Academy of Sciences Shanghai China

—Based on the distinguishing features of multi-tier millimeter wave (mmWave) networks such as different transmit powers, different directivity gains from directional beamforming alignment and path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) links, we introduce a normalization model to simplify the analysis of multi-tier mmWave cellular networks. The highlight of the model is that we convert a multi-tier mmWave cellular network into a single-tier mmWave network, where all the base stations (BSs) have the same normalized transmit power 1 and the densities of BSs scaled by LOS or NLOS scaling factors respectively follow piecewise constant function which has multiple demarcation points. On this basis, expressions for computing the coverage probability are obtained in general case with beamforming alignment errors and the special case with perfect beamforming alignment in the communication. According to corresponding numerical exploration, we conclude that the normalization model for multi-tier mmWave cellular networks fully meets requirements of network performance analysis, and it is simpler and clearer than the untransformed model. Besides, an unexpected but sensible finding is that there is an optimal beam width that maximizes coverage probability in the case with beamforming alignment errors. Copyright © 2017, The Authors. All rights reserved.

关键词： wireless networks

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