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Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

science China(Information sciences) 2023年第3期66卷 7-25页

作者： Guangxu ZHU Zhonghao LYU Xiang JIAO Peixi LIU Mingzhe CHEN Jie XU Shuguang CUI Ping ZHANG Shenzhen Research Institute of Big Data Future Network of Intelligence Institute (FNii) The Chinese University of Hong Kong (Shenzhen) School of Science and Engineering (SSE) The Chinese University of Hong Kong (Shenzhen) State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.

关键词： sixth-generation (6G) edge intelligence artificial intelligence of things (AIoT) integrated sensing communication and computation (ISCC)

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Joint Optimization of Latency and Energy Consumption for Mobile Edge Computing Based Proximity Detection in Road networks

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China communications 2022年第4期19卷 274-290页

作者： Tongyu Zhao Yaqiong Liu Guochu Shou Xinwei Yao School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and ConvergenceBeijing 100876China School of Computer Science and Technology Zhejiang University of TechnologyChina

In recent years, artificial intelligence and automotive industry have developed rapidly, and autonomous driving has gradually become the focus of the industry. In road networks, the problem of proximity detection refers to detecting whether two moving objects are close to each other or not in real time. However, the battery life and computing capability of mobile devices are limited in the actual scene,which results in high latency and energy consumption. Therefore, it is a tough problem to determine the proximity relationship between mobile users with low latency and energy consumption. In this article, we aim at finding a tradeoff between latency and energy consumption. We formalize the computation offloading problem base on mobile edge computing(MEC)into a constrained multiobjective optimization problem(CMOP) and utilize NSGA-II to solve it. The simulation results demonstrate that NSGA-II can find the Pareto set, which reduces the latency and energy consumption effectively. In addition, a large number of solutions provided by the Pareto set give us more choices of the offloading decision according to the actual situation.

关键词： proximity detection mobile edge computing road networks constrained multiobjective optimization

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Transmit Rate Enhancement for STAR-RIS-Assisted Uplink NOMA

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IEEE Transactions on Vehicular technology 2025年第5期74卷 7651-7665页

作者： Feng, Youhong Xu, Longzhu Li, Qiang Yan, Shihao Wang, Hong Ng, Derrick Wing Kwan Anhui Normal University School of Physics and Electronic information Wuhu241000 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Edith Cowan University School of Science and Security Research Institute JoondalupWA6027 Australia Nanjing University of Posts and Telecommunications School of Communication and Information Engineering Nanjing210003 China University of New South Wales School of Electrical Engineering and Telecommunications SydneyNSW2033 Australia

In this paper, a novel simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) enhanced uplink non-orthogonal multiple access (NOMA) communication network is investigated. Specifically, we tackle the transmit rate maximization problem for the strong user, subject to the constraints on total power consumption and the successive interference cancellation order, while guaranteeing the minimum quality-of-service requirement for the weak user. To address such a non-convex optimal problem, we introduce a novel, efficient, and low-complexity scheme. Specifically, the power allocation and receive beamforming optimization solutions are acquired in closed forms, and the transmission and reflection coefficients are obtained in semi-closed forms with a one-dimensional bisection search. Then, theoretical analysis demonstrates our proposed scheme has a lower complexity compared to the schemes with alternating direction method of multipliers (ADMM) and semidefinite relaxation (SDR) strategies, and the complexity advantage of our proposed scheme over the SDR and ADMM aided schemes becomes prominent when the number of RIS elements increase. Simulation results show that the proposed STAR-RIS-NOMA scheme achieves a better performance than the conventional STAR-RIS-aided orthogonal multiple access (OMA) scheme and STAR-RIS aided NOMA scheme adopting random phase shifts. More specifically, the proposed STAR-RIS-NOMA scheme outperforms the STAR-RIS-OMA scheme in terms of the strong user's rate, especially when the quality-of-service (QoS) requirements for weak user is high, or there is a significant difference channel quality between the reflecting and transmitting links. © 1967-2012 IEEE.

关键词： Convex optimization

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Perceptual Quality Assessment for Digital Human Heads 48

Perceptual Quality Assessment for Digital Human Heads

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Zhang, Zicheng Zhou, Yingjie Sun, Wei Min, Xiongkuo Wu, Yuzhe Zhai, Guangtao Shanghai Jiao Tong University Institute of Image Communication and Network Engineering China Peng Cheng Laboratory China Donghua University College of Information Science & Technology China

ISBN: (纸本)9781728163277

Digital humans are attracting more and more research interest during the last decade, the generation, representation, rendering, and animation of which have been put into large amounts of effort. However, the quality assessment of digital humans has fallen behind. Therefore, to tackle the challenge of digital human quality assessment issues, we propose the first large-scale quality assessment database for three-dimensional (3D) scanned digital human heads (DHHs). The constructed database consists of 55 reference DHHs and 1,540 distorted DHHs along with the subjective perceptual ratings. Then, a simple yet effective full-reference (FR) projection-based method is proposed to evaluate the visual quality of DHHs. The pretrained Swin Transformer tiny is employed for hierarchical feature extraction and the multi-head attention module is utilized for feature fusion. The experimental results reveal that the proposed method exhibits state-of-the-art performance among the mainstream FR metrics. The database is released at https://***/zzc-1998/DHHQA. © 2023 IEEE.

关键词： Digital human head full-reference projection-based quality assessment database

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50-km Weakly-coupled Transmission with L-band 4-LP-mode FM-EDFA

50-km Weakly-coupled Transmission with L-band 4-LP-mode FM-E...

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2024 Asia communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical communications, IPOC 2024

作者： Huang, Shuailuo Zhu, Baolong Qiao, Gang Gao, Yuyang Zuo, Mingqing Shen, Shikui Wang, Zelin He, Yongqi Chen, Zhangyuan Li, Juhao Chen, Zhangyuan Li, Juhao China Unicom Research Institute Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Fundamental Network Technology China Mobile Research Institute Beijing China Pengcheng National Laboratory Shenzhen China

ISBN: (纸本)9798350379266

关键词： Pulse amplitude modulation

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Properties of focused Laguerre–Gaussian beam propagating in anisotropic ocean turbulence

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Chinese Physics B 2024年第2期33卷 386-393页

作者：王新光马洋斌袁邱杰陈伟王乐赵生妹 College of Science Nanjing University of Posts and TelecommunicationsNanjing 210003China Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Lab of Broadband Wireless Communication and Sensor Network Technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China National Laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

We analyze the properties of a focused Laguerre–Gaussian(LG)beam propagating through anisotropic ocean turbulence based on the Huygens–Fresnel *** the Rytov approximation theory,we derive the analytical formula of the channel capacity of the focused LG beam in the anisotropic ocean turbulence,and analyze the relationship between the capacity and the light source parameters as well as the turbulent ocean *** is found that the focusing mirror can greatly enhance the channel capacity of the system at the geometric focal plane in oceanic *** results also demonstrate that the communication link can obtain high channel capacity by adopting longer beam wavelength,greater initial beam waist radius,and larger number of transmission ***,the capacity of the system increases with the decrease of the mean squared temperature dissipation rate,temperature-salinity contribution ratio and turbulence outer scale factor,and with the increase of the kinetic energy dissipation rate per unit mass of fluid,turbulence inner scale factor and anisotropy *** to a Hankel–Bessel beam with diffraction-free characteristics and unfocused LG beam,the focused LG beam shows superior anti-turbulence interference properties,which provide a theoretical reference for research and development of underwater optical communication links using focused LG beams.

关键词： vortex beam orbital angular momentum focusing mirror anisotropic turbulence

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AIR-PV: a benchmark dataset for photovoltaic panel extraction in optical remote sensing imagery

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science China(Information sciences) 2023年第4期66卷 122-123页

作者： Zhiyuan YAN Peijin WANG Feng XU Xian SUN Wenhui DIAO Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology(NIST) Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory for Information Science of Electromagnetic Waves(MoE) Fudan University

The energy crisis has been a hot topic of global *** devices, a typical new energy source, have progressed rapidly and become among the main sources of power generation in the world [1]. Most photovoltaic fields are often constructed in large areas, making it difficult to monitor photovoltaic panel situations. Combining remote sensing(RS) and deep learning [2],

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A Novel Virtual Node-Based Multi-Controller Management Architecture for LEO Mega-Constellation Satellite networks 15

A Novel Virtual Node-Based Multi-Controller Management Archi...

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

作者： Dong, Yunyao Xu, Xiaofan Zhang, Yueyue Wang, Siming Du, Ping Xu, Du Zhang, Xiaoning University of Electronic Science and Technology of China School of Information and Communication Engineering Sichuan Chengdu China Shanghai Satellite Network Research Institute Co. Ltd Shanghai Key Laboratory of Satellite Network Shanghai China

ISBN: (纸本)9798350324662

The development of 6G communication has made low earth orbit (LEO) satellite networks to be a critical component of global communication systems. The high density of LEO satellites enables mobile devices to have continuous communication. However, managing satellites in mega-constellation LEO satellite networks poses a scalability challenge due to the large number of LEO satellite nodes. Besides, due to the high mobility of LEO satellites, inter-satellite handover frequently occurs, which leads to the degradation of traffic QoS (Quality of Service). To address these issues, in this paper, we propose a novel virtual node-based multi-controller management architecture for LEO-satellite constellation networks, that can effectively shield the dynamics of satellite network topology. In specific, we first redefine the virtual node as a geographical area with clear boundaries. Then, we set up domain controllers in each virtual node to manage the satellites. Besides, we propose a handover algorithm to reduce delay jitter and delay by jointly considering the probability of handover and the cost of rerouting. We conduct simulations on Starlink Phase I and the results show that compared with benchmark algorithms, the proposed architecture can reduce the delay jitter by more than 50% and the delay by 10%. © 2023 IEEE.

关键词： LEO satellite networks network management resource allocation software defined network (SDN)

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General Simultaneous Localization and Mapping Scheme for mmWave communication Systems

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IEEE Internet of Things Journal 2024年第12期11卷 22521-22536页

作者： Du, Tao Yang, Jie Wen, Chao-Kai Xia, Shuqiang Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory Of Measurement And Control Of Complex Systems Of Engineering Ministry Of Education The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China Institute Of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation The State Key Laboratory Of Mobile Network And Mobile Multimedia Technology Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China

Utilizing high-resolution antenna arrays and wide bandwidth of the millimeter-wave (mmWave) spectrum in 5G new radio (NR) mmWave communication systems holds the potential for high-throughput data transmission while enabling user localization and environmental mapping. However, the majority of existing simultaneous localization and mapping (SLAM) algorithms rely on methods akin to the extended Kalman filter for generating initial map features. These methods prove ineffective when the measurement dimension is insufficient. Furthermore, there is a notable absence of research exploring mmWave prototype systems to evaluate and compare the performance and viability of various SLAM algorithms. To address these challenges, we propose an innovative probability hypothesis density (PHD) generation scheme for birth events and have developed a prototype system. Our approach, referred to as PHD-SLAM, exhibits remarkable effectiveness even in scenarios where the measurement dimension falls short of map features. This means it can function seamlessly with only delay or angle information available. Additionally, we have designed a 28GHz mmWave beam scanning prototype system that leverages the 5G NR frame for accomplishing SLAM algorithms. Following this, we conducted extensive simulations and experimental evaluations to gauge the performance of several leading-edge SLAM algorithms under diverse mmWave circumstances, encompassing PHD-based and belief propagation (BP) SLAM algorithms. Our analysis reveals that both PHD and BP SLAM can achieve agent localization precision within a decimeter and mapping precision within a meter, capitalizing on the angle parameters of mmWave signals. While BP SLAM showcases reduced computational demand, its estimation precision is marginally inferior to that of PHD-SLAM. © 2014 IEEE.

关键词： Belief propagation

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Automatic skin lesion classification using a novel densely connected convolutional network integrated with an attention module

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Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 8943-8956页

作者： Shan, Pufang Chen, Jialei Fu, Chong Cao, Lin Tie, Ming Sham, Chiu-Wing School of Computer Science and Engineering Northeastern University Shenyang110819 China Engineering Research Center of Security Technology of Complex Network System Ministry of Education Shenyang China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang110819 China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China Science and Technology on Space Physics Laboratory Beijing100076 China School of Computer Science The University of Auckland Auckland New Zealand

Automated skin lesion classification in dermoscopy images remains challenging due to the existence of artefacts and intrinsic cutaneous features, diversity of lesion morphology, insufficiency of training data, and class imbalance problem. To address these challenges, we propose a new densely connected convolutional network termed AttDenseNet-121, which is obtained by integrating the convolutional block attention module (CBAM) into DenseNet-121. CBAM is a simple yet efficient attention module, which is further improved by adding a novel pooling layer (multiscale-pooling) to effectively enhance its attention capability. The optimized CBAM strengthens the representation power of DenseNet-121 by emphasizing meaningful features and suppressing unnecessary ones, thus significantly enhancing the classification performance. Besides, to handle the imbalanced dataset, we employ an improved focal loss function rather than the traditional cross-entropy loss function to train AttDenseNet-121. The improved focal loss is calculated from a different perspective compared with the original focal loss. It makes the distribution of positive samples and negative samples in each batch the same as that in the original data, successfully mitigating the negative influence of class imbalance on this multi-class classification task. We conduct extensive experiments on the public benchmark dataset (HAM10000) and the results indicate that our proposed method achieves superior performance compared with that of the baselines and state-of-the-art algorithms. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Convolution

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