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Asia-Pacific Conference on Microwave

作者： Xiaoyuan He Li Deng Yang Yang Beijing Laboratory of Advanced Information Networks & Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China School of Electrical and Data Engineering Tech Lab University of Technology Sydney Australia

A 3D-printed sub-terahertz lens for manipulating quasi-non-diffractive orbital angular momentum (OAM) waves is proposed in this paper. The proposed lens comprises all-dielectric elements that impose desired phase profiles on the incident waves by varying their height. Based on the concept of the Bessel beam launchers and the beam deflectors, quasi-non-diffractive OAM waves with a pre-defined deflection angle can be produced by the proposed lens. For verification, two lenses were 3D printed for producing OAM waves with a non-diffractive depth of 55.58λ c (λ c is the free-space wavelength at 140 GHz). Measured by a terahertz imaging camera, the desired quasi-non-diffractive OAM waves were observed behind the proposed lenses with expected non-diffractive performance and a large deflection angle of up to 47°.

关键词： Microwave measurement Terahertz wave imaging Three-dimensional displays Wavelength measurement Extraterrestrial measurements Cameras Orbits

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Energy Minimization for MEC-enabled Cellular-Connected UAV: Trajectory Optimization and Resource Scheduling

Energy Minimization for MEC-enabled Cellular-Connected UAV: ...

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IEEE Conference on Computer Communications Workshops, INFOCOM Wksps

作者： Zhaohua Lv Jianjun Hao Yijun Guo Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications

ISBN: (数字)9781728186955

ISBN: (纸本)9781728186962

Recent years, under the cooperation of 5G techniques which enables high rate and low delay communication, cellular-connected unmanned aerial vehicles (UAVs) have attracted tremendous attentions due to its broad applications. In this paper, we focus on a mobile edge computing (MEC) enabled cellular-connected UAV system, where a UAV carrying a fixed amount of computation tasks is deployed to fly from an initial location to a final location and served by ground base stations (GBSs) in the presence of a ground eavesdropper. During the flight, the UAV can offload part of the tasks to GBSs for remote execution. We aim to minimize the total energy consumption of UAV to complete the task, including computation energy, communication energy and flight-propulsion energy, by jointly optimizing UAV trajectory, computation task allocation, UAV-GBS association and transmit power allocation. To tackle the non-convexity of the original problem, we resort to the block coordinate decent and successive convex approximation techniques through decomposing it into three sub-problems, which are alternately solved until the algorithm converges. Numerical results show that the proposed design effectively saves UAV's energy consumption for completing the given tasks.

关键词： Task analysis Energy consumption Unmanned aerial vehicles Trajectory Resource management Computational modeling Central Processing Unit

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Federated Learning based Audio Semantic Communication over Wireless networks

Federated Learning based Audio Semantic Communication over W...

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2021 IEEE Global Communications Conference (GLOBECOM)

作者： Haonan Tong Zhaohui Yang Sihua Wang Ye Hu Walid Saad Changchuan Yin Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China University College London London UK Wireless@VT Virginia Tech Blacksburg VA USA

ISBN: (纸本)9781728181059

In this paper, the problem of audio based semantic communication is investigated over wireless networks. In the considered model, wireless edge devices must transmit large-sized audio data to a server using semantic communication techniques. The techniques enable the transmission of audio semantic information which captures the contextual features of audio signals. To extract the semantic information from audio signals, a wave to vector (wav2vec) architecture based autoencoder that consists of convolutional neural networks (CNNs) is proposed. The proposed autoencoder enables high-accuracy audio transmission with small amounts of data. To further improve the accuracy of semantic information extraction, federated learning (FL) is implemented over multiple devices and a server. Simulation results show that the proposed algorithm can converge effectively and can reduce the mean square error (MSE) between the recovered audio signals and the source audio signals by nearly 100 times, compared to a traditional coding scheme.

关键词： Phase change materials Performance evaluation Wireless networks Simulation Semantics Mean square error methods Collaborative work

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A Survey on Indoor Visible Light Positioning systems: Fundamentals, Applications, and Challenges

arXiv

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arXiv 2024年

作者： Zhu, Zhiyu Yang, Yang Chen, Mingzhe Guo, Caili Cheng, Julian Cui, Shuguang The Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Faculty of Applied Science School of Engineering The University of British Columbia KelownaBCV1V 1V7 Canada The Chinese University of Hong Kong Shenzhen518172 China

The growing demand for location-based services in areas like virtual reality, robot control, and navigation has intensified the focus on indoor localization. Visible light positioning (VLP), leveraging visible light communications (VLC), becomes a promising indoor positioning technology due to its high accuracy and low cost. This paper provides a comprehensive survey of VLP systems. In particular, since VLC lays the foundation for VLP, we first present a detailed overview of the principles of VLC. Then, we provide an in-depth overview of VLP algorithms. The performance of each positioning algorithm is also compared in terms of various metrics such as accuracy, coverage, and orientation limitation. Beyond the physical layer studies, the network design for a VLP system is also investigated, including multi-access technologies, resource allocation, and light-emitting diode (LED) placements. Next, the applications of the VLP systems are overviewed. Finally, this paper outlines open issues, challenges, and opportunities for the research field. In a nutshell, this paper constitutes the first holistic survey on VLP from state-of-the-art studies to practical uses. Copyright © 2024, The Authors. All rights reserved.

关键词： Resource allocation

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DQ-RM: Deep Reinforcement Learning-based Route Mutation Scheme for Multimedia Services 16

DQ-RM: Deep Reinforcement Learning-based Route Mutation Sche...

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16th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2020

作者： Zhang, Tao Xu, Changqiao Zhang, Bingchi Kuang, Xiaohui Wang, Yue Yang, Shujie Muntean, Gabriel-Miro State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of International Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Science and Technology on Information System Security Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Performance Engineering Lab. School of Electronic Engineering Dublin City University Dublin Ireland

ISBN: (纸本)9781728131290

Increasingly growing various multimedia services (e.g., interactive live video and so on) have brought tremendous pressure on existing static defense techniques. To cope with inherent drawback of static defense techniques, network Moving Target Defense (NMTD) such as route mutation (RM) was proposed. What's more, applying reinforcement learning (RL) into RM has been proved feasible in our previous work. But two main problems still need to be considered in this combination of RL with RM: 1) It lacks the consideration of multiple flows situation. 2) With the state-action space grow larger, current solution can't handle efficiently. In this paper, we propose a deep Q-learning method for RM (DQ-RM) to solve above two problems. Firstly, benefited from the satisfiability module theory, we formalize RM space considering single flow and multiple flows concurrently. Then we further propose a deep reinforcement learning-based RM scheme based on our previous work, which is suitable for large-scale state-action space. Finally, extensive experimental results highlight the improvement of DQ-RM in defense performance and convergence speed compared to the representative solution. © 2020 IEEE.

关键词： Reinforcement learning

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A Metasurfaced Circularly-Polarized Antenna for Electronic Toll Collection system 3

A Metasurfaced Circularly-Polarized Antenna for Electronic T...

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3rd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2020

作者： Chen, Junlong Feng, Botao Chung, Kwok L. Deng, Li College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China Civionics Research Laboratory Qingdao University of Technology Qingdao266033 China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781728190457

In this paper, a metasurfaced circularly-polarized (CP) antenna with a double-layer structure is proposed for the electronic toll collection (ETC) system. The antenna composed of dual layer of printed circuit board (PCB) with an overall height of 6 mm. The top-layer (Layer 2) is a metasurface that made with 4×4 unit-cells of chamfered square patches. The driven patch is printed with a U-slot at the bottom layer (Layer 1). The addition of metasurface helps to achieve narrow beam width with a high gain. The simulation results demonstrate that the proposed metasurfaced CP antenna exhibits a mandated right-hand narrow beamwidth in the desired ETC frequency band, whereas its broadside gain is obtained greater than 6.5 dBic. In addition, both the achieved impedance bandwidth and axial ratio bandwidth are sufficient to cover the entire ETC band (5.75 GHz-5.9 GHz). © 2020 IEEE.

关键词： Bandwidth

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Leveraging multiple legacy Wi-Fi links for human behavior sensing

arXiv

引用

arXiv 2021年

作者： Guo, Lingchao Lu, Zhaoming Wen, Xiangming Wang, Liming Gesbert, David Han, Zijun Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Communications Systems Department EURECOM Sophia Antipolis France

Taking advantage of the rich information provided by Wi-Fi measurement setups, Wi-Fi-based human behavior sensing leveraging Channel State Information (CSI) measurements has received a lot of research attention in recent years. The CSI-based human sensing algorithms typically either rely on an explicit channel propagation model or, more recently, adopt machine learning so as to robustify feature extraction. In most related work, the considered CSI is extracted from a single dedicated Access Point (AP) communication setup. In this paper, we consider a more realistic setting where a legacy network of multiple APs is already deployed for communications purposes and leveraged for sensing benefits using machine learning. The use of legacy network presents challenges and opportunities as many Wi-Fi links can present with richer yet unequally useful data sets. In order to break the curse of dimensionality associated with training over a too large dimensional CSI, we propose a link selection mechanism based on Reinforcement Learning (RL) which allows for dimension reduction while preserving the data that is most relevant for human behavior sensing. The method is based on a sequential state decision-making process in which the CSI is modeled as a part of the state. From actual experiment results, our method is shown to perform better than state-of-the-art approaches in a scenario with multiple available Wi-Fi links. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel state information

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Learning multiscale correlations for human motion prediction

arXiv

引用

arXiv 2021年

作者： Zhou, Honghong Guo, Caili Zhang, Hao Wang, Yanjun Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing China China Telecom Dict Application Capability Center China

In spite of the great progress in human motion prediction, it is still a challenging task to predict those aperiodic and complicated motions. We believe that capturing the correlations among human body components is the key to understand the human motion. In this paper, we propose a novel multiscale graph convolution network (MGCN) to address this problem. Firstly, we design an adaptive multiscale interactional encoding module (MIEM) which is composed of two sub modules: scale transformation module (STM) and scale interaction module (SIM) to learn the human body correlations. Secondly, we apply a coarse-to-fine decoding strategy to decode the motions sequentially. We evaluate our approach on two standard benchmark datasets for human motion prediction: Human3.6M and CMU motion capture dataset. The experiments show that the proposed approach achieves the state-of-the-art performance for both short-term and long-term prediction especially in those complicated action category. We make codes publicly available at https://***/zhouhongh/MGCN. © 2021, CC BY-NC-ND.

关键词： Motion estimation

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Co-deployment of UAV and Ground Base Station for Data Collection in Wireless Sensor networks

Co-deployment of UAV and Ground Base Station for Data Collec...

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IEEE International Conference on Communications (ICC)

作者： Xinying Hu Yijun Guo Jianjun Hao Chenxi Li Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications China

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

In wireless sensor networks (WSNs) enabled by fixed ground infrastructure, sink nodes located at the margin of the coverage area often suffer from bad communication channels. In this paper, we use UAV-carried aerial base station (ABS) to assist ground base station (GBS) for data collection from sink nodes in WSN, and focus on the co-deployment of ABS and GBS from aspects of coverage partition and bandwidth resource allocation, aiming at minimizing the total energy consumption for uplink transmission of all the sensor nodes in WSN. In particular, we first derive the estimated energy consumption with the sink nodes' density instead of their exact positions. Then, to tackle the non-convexity of the original problem, we decomposing it into two subproblems, which are alternately solved to iteratively improve the sum energy consumption. Numerical results show that the proposed design significantly reduces the energy consumption of all sink nodes as compared to benchmark schemes.

关键词： Wireless sensor networks Energy consumption Bandwidth Data collection Base stations Unmanned aerial vehicles Uplink

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Exploration of Simulation Teaching Mode for Intelligent Information network Course

Exploration of Simulation Teaching Mode for Intelligent Info...

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International Conference on networking and network Applications (NaNA)

作者： Yue He Hui Li Yiming Li Qiang Wu Yuefeng Ji Rentao Gu Shaobin Fan Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications (BUPT) Beijing China School of Information and Communication Engineering BUPT Beijing China Beijing Key Laboratory of Network System Architecture and Convergence BUPT Beijing China China Unicom China

With the rapid development of information technology, the society’s demand for information technology talents has become particularly high; how colleges and universities devote themselves to cultivating professional information technology talents is an important direction at present. However, the teacher’s evaluation method stays at the exam-oriented education. In the university education, in order to help students with basic professional knowledge to learn more professional knowledge and skills, and to help teachers understand the characteristics of students more objectively, this article discusses how to improve the existing teaching environment and simulation teaching mode. A simulation teaching platform for the “Intelligent Information network” course is designed with multiple modules for complex network construction. Through the online network simulation teaching platform and the feedback obtained from the platform’s use, different students’ different problems can be found objectively, and the combination of theory and engineering, the combination of new and old knowledge, and the simplicity of complex software can be realized.

关键词： Knowledge engineering Education Complex networks Software Information technology

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