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IEEE International Conference on Communications (ICC)

作者： Nuocheng Yang Sihua Wang Mingzhe Chen Changchuan Yin Christopher G. Brinton Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Collaborative federated learning (CFL) enables device cooperation in training shared machine learning models without reliance on a parameter server. However, the absence of a parameter server also impacts vulnerabilities associated with adversarial attacks, including privacy inference and Byzantine attacks. In this context, this paper introduces a novel CFL framework that enables each device to individually determine the subset of devices to transmit FL parameters to over the wireless network, based on its neighboring devices' location, current loss, and connection information, to achieve privacy protection and robust aggregation. This is formulated as an optimization problem whose goal is to minimize CFL training loss while satisfying the privacy preservation, robust aggregation, and transmission delay requirements. To solve this problem, a proximal policy optimization (PPO)-based reinforcement learning (RL) algorithm integrated with a graph neural network (GNN) is proposed. Compared to traditional algorithms that use global information with high computational complexity, the proposed GNN-RL method can be deployed on devices based on neighboring information with lower computational overhead. Simulation results show that the proposed algorithm can protect data privacy and increase identification accuracy by 15% compared to an algorithm in which devices are partially clustered for model aggregation.

关键词： Training Privacy Federated learning Simulation Collaboration Clustering algorithms Propagation losses

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

引用

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

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MPMAC and its security analysis

引用

Beijing Gongye Daxue Xuebao / Journal of Beijing University of technology 2008年第SUPPL. 2期34卷 62-66页

作者： Zhang, Shao-Lan Yang, Yi-Xian Xing, Guo-Bo Information Security Center State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China Key Laboratory of Network and Information Attack and Defense Technology of MOE Beijing University of Posts and Telecommunications Beijing 100876 China School of Computer Science and Technology Shandong Jianzhu University Jinan 250101 China

According to the weakness of mode of operation, a modified parallelizable message authentication code (MPMAC) is proposed. The mode to process the last block of message is improved to avoid the forgery attack with random message by using the fact that the block cipher has same output with the same input using a key. Its security is proved by quantifying the advantage of distinguishing message authentication code from the random function in terms of the quality of the block cipher as a pseudo-random permutation.

关键词： Authentication

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Enabling Ubiquitous Non-Orthogonal Multiple Access and Pervasive Federated Learning via STAR-RIS

Enabling Ubiquitous Non-Orthogonal Multiple Access and Perva...

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2021 IEEE Global Communications Conference (GLOBECOM)

作者： Wanli Ni Yuanwei Liu Yonina C. Eldar Zhaohui Yang Hui Tian State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of Electronic Engineering and Computer Science Queen Mary University of London London UK Math and CS Faculty Weizmann Institute of Science Rehovot Israel Centre for Telecommunications Research King's College London London UK

ISBN: (纸本)9781728181059

This paper proposes a new, compatible, unified framework which integrates non-orthogonal multiple access (NOMA) and over-the-air federated learning (AirFL) via concurrent communication. In particular, a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is leveraged to adjust the signal processing order for efficient interference mitigation and omni-directional coverage extension. With the aim of investigating the impact of non-ideal wireless communication on AirFL, we provide a closed-form expression for the optimality gap over a given number of communication rounds. This result reveals that the learning performance is significantly affected by the resource allocation scheme and channel noise. To minimize the derived optimality gap, a mixed-integer non-linear programming (MINLP) problem is formulated by jointly designing the transmit power at users and configuration mode at the STAR-RIS. Through developing an alternating optimization algorithm, a suboptimal solution for the original MINLP problem is obtained. Simulation results show that the learning performance in terms of training loss and test accuracy can be effectively improved with the aid of the STAR-RIS.

关键词： Wireless communication Training NOMA Closed-form solutions Simulation Signal processing algorithms Signal processing

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Corrections to "Computer Vision Aided mmWave Beam Alignment in V2X Communications"

arXiv

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arXiv 2024年

作者： Xu, Weihua Gao, Feifei Tao, Xiaoming Zhang, Jianhua Alkhateeb, Ahmed Department of Automation Tsinghua University Beijing100084 China Department of Electronic Engineering Tsinghua University Beijing100084 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712-1687 United States

In this document, we revise the results of [1] based on more reasonable assumptions regarding data shuffling and parameter setup of deep neural networks (DNNs). Thus, the simulation results can now more reasonably demonstrate the performance of both the proposed and compared beam alignment methods. We revise the simulation steps and make moderate modifications to the design of the vehicle distribution feature (VDF) for the proposed vision based beam alignment when the MS location is available (VBALA). Specifically, we replace the 2D grids of the VDF with 3D grids and utilize the vehicle locations to expand the dimensions of the VDF. Then, we revise the simulation results of Fig. 11, Fig. 12, Fig. 13, Fig. 14, and Fig. 15 in [1] to reaffirm the validity of the conclusions. Copyright © 2024, The Authors. All rights reserved.

关键词： Vehicle-to-grid

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Generative AI for Advanced UAV networking

arXiv

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arXiv 2024年

作者： Sun, Geng Xie, Wenwen Niyato, Dusit Du, Hongyang Kang, Jiawen Wu, Jing Sun, Sumei Zhang, Ping The College of Computer Science and Technology Jilin University Changchun130012 China The College of Computing and Data Science Nanyang Technological University 639798 Singapore The College of Computer Science and Technology Jilin University Changchun130012 China The School of Automation Guangdong University of Technology Guangzhou510006 China The Institute for Infocomm Research Agency for Science Technology and Research Singapore639798 Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China

With the impressive achievements of chatGPT and Sora, generative artificial intelligence (GAI) has received increasing attention. Not limited to the field of content generation, GAI is also widely used to solve the problems in wireless communication scenarios due to its powerful learning and generalization capabilities. Therefore, we discuss key applications of GAI in improving unmanned aerial vehicle (UAV) communication and networking performance in this article. Specifically, we first review the key technologies of GAI and the important roles of UAV networking. Then, we show how GAI can improve the communication, networking, and security performances of UAV systems. Subsequently, we propose a novel framework of GAI for advanced UAV networking, and then present a case study of UAV-enabled spectrum map estimation and transmission rate optimization based on the proposed framework to verify the effectiveness of GAI-enabled UAV systems. Finally, we discuss some important open directions. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Empowering Computing and Networks Convergence System with Distributed Cooperative Routing

arXiv

引用

arXiv 2024年

作者： Hu, Yujiao Jia, Qingmin Shen, Meng Xie, Renchao Huang, Tao Yu, F. Richard Future Network Research Center Purple Mountain Laboratories Nanjing211111 China Pervasive Communication Research Center Purple Mountain Laboratories Nanjing211111 China The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The Department of Systems and Computer Engineering Carleton University Ottawa Canada

The emergence of intelligent applications and recent advances in the fields of computing and networks are driving the development of computing and networks convergence (CNC) system. However, existing researches failed to achieve comprehensive scheduling optimization of computing and network resources. This shortfall results in some requirements of computing requests unable to be guaranteed in an end-to-end service pattern, negatively impacting the development of CNC systems. In this article, we propose a distributed cooperative routing framework for the CNC system to ensure the deadline requirements and minimize the computation cost of requests. The framework includes trading plane, management plane, control plane and forwarding plane. The cross-plane cooperative end-to-end routing schemes consider both computation efficiency of heterogeneous servers and the network congestion degrees while making routing plan, thereby determining where to execute requests and corresponding routing paths. Simulations results substantiates the performance of our routing schemes in scheduling computing requests in the CNC system. © 2024, CC BY-NC-ND.

关键词： Routing protocols

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Residual Time Aware Forwarding for Randomly Duty-Cycled Wireless Sensor Networks

Residual Time Aware Forwarding for Randomly Duty-Cycled Wire...

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IEEE International Conference on Computational Science and Engineering, CSE

作者： Long Cheng Canfeng Chen Jian Ma Lei Shu Hongyang Chen Laurence T. Yang State Key Laboratory of Networking & Switching Technology Beijing University of Posts and Telecommunications Beijing China Nokia Research Center Beijing China Digital Enterprise Research Institute National University of Ireland Galway Ireland Institute of Industrial Science University of Tokyo Tokyo Japan Department of Computer Science Saint Francis Xavier University Canada

This paper studies data forwarding in wireless sensor networks (WSNs) where sensor nodes are randomly duty-cycled to save energy. The duty-cycling operation requires the data delivery strategy to be more adaptive for the dynamics caused by the uncertainty of node working schedules. However, the existing maximum-advance routing scheme, at each step the forwarding node selects the node closest to the destination as its next hop forwarder among neighbors, performs poorly in randomly duty-cycled *** this paper, we propose a new residual time aware (RTA) routing metric for randomly duty-cycled WSNs. RTA is designed to be responsive to the dynamics caused by duty-cycling operation. We also present a residual time aware forwarding (RTAF) strategy using this metric for randomly duty-cycled WSNs. Simulation results demonstrate that our proposed RTAF strategy reduces the retransmissions and delivery delay introduced by the duty-cycling operation. Therefore, it is shown that RTAF increases the data delivery ratio and average advance per hop, and significantly reduces the end-to-end delivery latency.

关键词： Wireless sensor networks Routing Sensor phenomena and characterization Computer networks Uncertainty Dynamic scheduling Delay Sleep Telecommunication computing Data engineering

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Computer Vision Aided mmWave Beam Alignment in V2X Communications

arXiv

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arXiv 2022年

作者： Xu, Weihua Gao, Feifei Tao, Xiaoming Zhang, Jianhua Alkhateeb, Ahmed Department of Automation Tsinghua University Beijing100084 China The Department of Electronic Engineering Tsinghua University Beijing100084 China The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712-1687 United States

Visual information, captured for example by cameras, can effectively reflect the sizes and locations of the environmental scattering objects, and thereby can be used to infer communications parameters like propagation directions, receiver powers, as well as the blockage status. In this paper, we propose a novel beam alignment framework that leverages images taken by cameras installed at the mobile user. Specifically, we utilize 3D object detection techniques to extract the size and location information of the dynamic vehicles around the mobile user, and design a deep neural network (DNN) to infer the optimal beam pair for transceivers without any pilot signal overhead. Moreover, to avoid performing beam alignment too frequently or too slowly, a beam coherence time (BCT) prediction method is developed based on the vision information. This can effectively improve the transmission rate compared with the beam alignment approach with the fixed BCT. Simulation results show that the proposed vision based beam alignment methods outperform the existing LIDAR and vision based solutions, and demand for much lower hardware cost and communication overhead. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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A Novel Scheduling Scheme for Earth Observation in LEO Satellite Systems

A Novel Scheduling Scheme for Earth Observation in LEO Satel...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Ting Xiong Ran Zhang Changqing Luo Jiang Liu Geyong Min Tao Huang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing P.R. China Purple Mountain Laboratories Nanjing P.R. China Department of Computer Science Virginia Commonwealth University Richmond VA Department of Computer Science University of Exeter Exeter U.K.

Earth observation applications, such as emergency surveillance and disaster relief, are thriving due to the availability of earth observation satellites that provide timely and objective observation data at different spatial and temporal scales. Such observation data is processed at the satellite edge with orbital edge computing, leading to potentially reduced bandwidth cost and transmission delay. However, most existing studies primarily focus on optimizing computation offloading but ignore the consideration of object observation and observation data transmission. To fill this gap, this paper proposes a novel scheduling approach that jointly considers observation satellites, relay satellites, and computing satellites in LEO satellite systems, aiming to maximize the number of completed observation tasks while taking into account various requirements of observation, transmission, and computation resources. Specifically, we first formulate the problem of jointly scheduling observation, relay, and computing satellites to maximize the number of accomplished observation tasks. Then, we decompose the formulated problem into two sub-problems and design a resource-aware algorithm called ORCA to determine the optimal scheduling of observation, relay, and computing satellites. Simulation results demonstrate that ORCA outperforms existing algorithms in terms of completing a number of observation tasks.

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