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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

Spectral and energy efficiency of ACO-OFDM in visible light communication systems

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arXiv 2021年

作者： Ma, Shuai Yang, Ruixin Deng, Xiong Ling, Xintong Zhang, Xun Zhou, Fuhui Li, Shiyin Ng, Derrick Wing Kwan School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China EindhovenNL Netherlands National Mobile Communications Research Laboratory Southeast University The Purple Mountain Laboratories Nanjing China Institut Suprieur dElectronique de Paris ISEP Paris France College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing210000 China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Nanjing University of Aeronautics and Astronautics School of Electrical Engineering and Telecommunications University of New SouthWales SydneyNSW2052 Australia

In this paper, we study the spectral efficiency (SE) and energy efficiency (EE) of asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) for visible light communication (VLC). Firstly, we derive the achievable rates for Gaussian distributions inputs and practical finite-alphabet inputs. Then, we investigate the SE maximization problems subject to both the total transmit power constraint and the average optical power constraint with the above two inputs, respectively. By exploiting the relationship between the mutual information and the minimum mean-squared error, an optimal power allocation scheme is proposed to maximize the SE with finite-alphabet inputs. To reduce the computational complexity of the power allocation scheme, we derive a closed-form lower bound of the SE. Also, considering the quality of service, we further tackle the non-convex EE maximization problems of ACO-OFDM with the two inputs, respectively. The problems are solved by the proposed Dinkelbach-type iterative algorithm. In each iteration, the interior point algorithm is applied to obtain the optimal power *** performance of the proposed power allocation schemes for the SE and EE maximization are validated through numerical analysis. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

A Novel Channel Estimation Scheme for Frequency-Selective mmWave Massive MIMO systems

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A Novel Channel Estimation Scheme for Frequency-Selective mm...

International Conference on Wireless communications and Signal Processing (WCSP)

作者： Zhigang Song Jian Sun Wensheng Zhang Cheng-Xiang Wang Minggao Zhang Shandong Provincial Key Lab of Wireless Communication Technologies School of Information Science and Engineering Shandong University Qingdao China The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing China National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

In this paper, a two-stage channel estimation scheme is presented for frequency-selective millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with hybrid precoding. Specifically, at the first stage, likelihood function with respective to the channel angle of departure (AoD) and angle of arrival (AoA) are maximized by the deterministic maximum likelihood (DML) estimator to obtain a coarse channel estimate. At the second stage, a space-alternating generalized expectation-maximization (SAGE) based algorithm is proposed to refine the channel parameters. In addition, an angle paring scheme is proposed to paired the AoA and AoD. Simulation results show the better performance of the proposed method.

关键词：

Artificial intelligence enabled radio propagation for communications-Part II: Scenario identification and channel modeling

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arXiv 2021年

作者： Huang, Chen He, Ruisi Ai, Bo Molisch, Andreas F. Lau, Buon Kiong Haneda, Katsuyuki Liu, Bo Wang, Cheng-Xiang Yang, Mi Oestges, Claude Zhong, Zhangdui The Purple Mountain Laboratories Nanjing211111 China The National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China The State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China Peng Cheng Laboratory Shenzhen518055 China The Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States The Department of Electrical and Information Technology Lund University Lund22100 Sweden The Department of Radio Science and Engineering Aalto University Aalto00076 Finland The School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The Institute of Information and Communication Technologies Electronics and Applied Mathematics Universite Catholique de Louvain Louvain-la-Neuve 1348 Belgium

This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. In Part I, we introduced AI and ML as well as provided a comprehensive survey on ML enabled channel characterization and antenna-channel optimization, and in this part (Part II) we review state-of-the-art literature on scenario identification and channel modeling here. In particular, the key ideas of ML for scenario identification and channel modeling/prediction are presented, and the widely used ML methods for propagation scenario identification and channel modeling and prediction are analyzed and compared. Based on the state-of-art, the future challenges of AI/ML-based channel data processing techniques are given as well. © 2021, CC BY-NC-ND.

关键词： Machine learning

A TDMA-like access scheme with splitting request and transmission for vehicular networks

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arXiv 2019年

作者： Peng, Shenglong He, Xuan Du, Junyi Guan, Yong Liang Zhou, Liang National Key Lab of Science and Technology on Communications Center for Intelligent Networking and Communications Center for Cyber Security University of Electronic Science and Technology of China Chengdu China CETC Key Lab of Avionic Information System Southwest China Institute of Electronic Technology Chengdu China School of Electrical and Electronic Engineering Nanyang Technological University Singapore

In this paper, we consider safety message transmission in a dense vehicular network. With increasing vehicular network density, the collision rate increases when multiple vehicles transmit safety messages simultaneously. To address this issue, we propose a request-transmission split time division multiple access (TDMA) scheme, referred to as RTS-TDMA. In our scheme, we divide a frame into three phases, i.e., a contention access phase, a broadcast feedback phase, and a contentionfree transmission phase. Each vehicle selects a repetition rate according to a given probability distribution and repeats the transmission of its request packet to improve the reliability of the request. In addition, a roadside unit acts as the coordinator and uses a successive interference cancellation technique to resolve request collisions. RTS-TDMA also reduces the request time percentage by containing only the vehicle identity in each request packet. Both theoretical analysis and numerical results verify that the RTS-TDMA scheme can provide higher throughput than the coded slotted ALOHA scheme. Copyright © 2019, The Authors. All rights reserved.

关键词： Time division multiple access

Coalition game based user association for mmWave mobile relay systems in rail traffic scenarios

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arXiv 2021年

作者： Chen, Chen Niu, Yong Mao, Shiwen Zhang, Xiaodan Han, Zhu Ai, Bo Gao, Meilin Xiao, Huahua Wang, Ning The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The School of Management Shenzhen Institute of Information Technology Shenzhen518172 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China The Tsinghua Space Center Tsinghua University Beijing100091 China The ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. Copyright © 2021, The Authors. All rights reserved.

关键词： Game theory

From concept to action: a united, holistic and One Health approach to respond to the climate change crisis

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Infectious Diseases of Poverty 2022年第1期11卷 68-73页

作者： Renhe Zhang Xu Tang Jian Liu Martin Visbeck Huadong Guo Virginia Murray Catherine Mcgillycuddy Bing Ke Gretchen Kalonji Panmao Zhai Xiaoming Shi Jiahai Lu Xiaonong Zhou Haidong Kan Qunli Han Qian Ye Yong Luo Jianmin Chen Wenjia Cai Huiling Ouyang Riyanti Djalante Alexander Baklanov Lu Ren Guy Brasseur George Fu Gao Lei Zhou Integrated Research on Disaster Risk International Centre of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health&Institute of Atmospheric Sciences Fudan UniversityShanghai200438China Science Division United Nations Environment Programme(UNEP)United Nations AvenueGigiriPO Box 30552Nairobi00100Kenya GEOMAR Helmholtz Centre for Ocean Research Kiel and Kiel University KielGermany Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences Chinese Academy of SciencesBeijingChina UK Health Security Agency LondonSE18UGUK The Administrative Center for China’s Agenda 21 Ministry of Science and Technology of ChinaBeijing100038China Institute for Disaster Management and Reconstruction Sichuan UniversityChengdu610207China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing100081China China CDC Key Laboratory of Environment and Population Health National Institute of Environmental HealthChinese Center for Disease Control and PreventionBeijing100021China One Health Center of Excellence for Research and Training School of Public HealthSun Yat-Sen UniversityGuangzhouChina National Institute of Parasitic Diseases Chinese Center for Disease Control and Prevention(Chinese Center for Tropical Diseases Research)ShanghaiChina Integrated Research On Disaster Risk-IPO BeijingChina State Key Lab of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing100875China Ministry of Education Key Laboratory for Earth System Modeling and Department of Earth System ScienceTsinghua UniversityBeijingChina ASEAN Secretariat Indonesia Integrated Research on Disaster Risk(IRDR)JakartaIndonesia Science and Innovation Department World Meteorological Organization(WMO)7 bisAvenue de la PaixBP2300CH-1211Geneva 2Switzerland Max Planck Institute for Meteorology HamburgGermany Chinese Center for Dis

It is unequivocal that human influence has warmed the planet,which is seriously affecting the planetary health including human *** climate change should not only be a slogan,but requires a united,holistic action and a paradigm shift from crisis response to an ambitious and integrated approach *** the urgent needs to tackle the risk connection between climate change and One Health,the four key messages and recommendations that with the intent to guide further research and to promote international cooperation to achieve a more climate-resilient world are provided.

关键词： Climate change One Health International coordination and cooperation Risk-oriented recommendations

Low-latency federated learning over wireless channels with differential privacy

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arXiv 2021年

作者： Wei, Kang Li, Jun Ma, Chuan Ding, Ming Chen, Cailian Jin, Shi Han, Zhu Poor, H. Vincent School of Electrical and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China Data61 CSIRO SydneyNSW2015 Australia The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

In federated learning (FL), model training is distributed over clients and local models are aggregated by a central server. The performance of uploaded models in such situations can vary widely due to imbalanced data distributions, potential demands on privacy protections, and quality of transmissions. In this paper, we aim to minimize FL training delay over wireless channels, constrained by overall training performance as well as each client's differential privacy (DP) requirement. We solve this problem in the framework of multi-agent multiarmed bandit (MAMAB) to deal with the situation where there are multiple clients confornting different unknown transmission environments, e.g., channel fading and interferences. Specifically, we first transform the long-term constraints on both training performance and each client's DP into a virtual queue based on the Lyapunov drift technique. Then, we convert the MAMAB to a max-min bipartite matching problem at each communication round, by estimating rewards with the upper confidence bound (UCB) approach. More importantly, we propose two efficient solutions to this matching problem, i.e., modified Hungarian algorithm and greedy matching with a better alternative (GMBA), in which the first one can achieve the optimal solution with a high complexity while the second one approaches a better tradeoff by enabling a verified low-complexity with little performance loss. In addition, we develop an upper bound on the expected regret of this MAMAB based FL framework, which shows a linear growth over the logarithm of communication rounds, justifying its theoretical feasibility. Extensive experimental results are conducted to validate the effectiveness of our proposed algorithms, and the impacts of various parameters on the FL performance over wireless edge networks are also discussed. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

Standard Analysis for Transfer Delay in CTCS-3

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Chinese Journal of Electronics 2017年第5期26卷 1057-1063页

作者： CAO Yuan MA Lianchuan XIAO Shuo ZHANG Xia XU Wei National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University School of Computer Sciences and Technology China University of Mining & Technology National Mobile Communications Research Lab. Southeast University

According to the standard for the GSM for railway(GSM-R) wireless systems in China train control system level 3(CTCS-3),the control data transfer delay should be no larger than 500 ms with greater than99% *** of both non-redundant networks and intercross redundant networks and cases of single Mobile terminals(MTs) and redundant MTs on one train are considered,and the corresponding vehicle-ground communication models,delay models,and fault models are *** simulation results confirm that the transfer delay can meet the standard requirements under all *** particular,the probability is greater than 99.996% for redundant MTs and networks,and the standard of transfer delay in CTCS-3 will be improved inevitably.

关键词： China train control system level 3(CTCS-3) GSM for railway(GSM-R) Data transfer delay Deterministic and stochastic petri net(DSPN)