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

IEEE Communications Surveys and Tutorials 2024年

作者： Zhu, Zhiyu Yang, Yang Chen, Mingzhe Guo, Caili Cheng, Julian Cui, Shuguang Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering and Institute for Data Science and Computing Coral GablesFL33146 United States Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China The University of British Columbia Faculty of Applied Science School of Engineering KelownaBCV1V 1V7 Canada 518172 Hong Kong

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. © 1998-2012 IEEE.

关键词： Resource allocation

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Content-driven Joint Resource Allocation Based on Vehicle-edge Synergy in Vehicular networks

Content-driven Joint Resource Allocation Based on Vehicle-ed...

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IEEE Wireless Communications and networking Conference Workshops (WCNCW)

作者： Xu Zhu Fangfang Liu Zhimin Zeng Caili Guo Jiujiu Chen Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781728195070;9781728195087

With the rapid growth of computer vision applications, a large amount of video data in vehicular networks are used for content analysis. As a representative technology in the field of artificial intelligence, deep learning has been widely used in video content understanding. However, deep learning models are usually accompanied by huge amount of calculation, which put great pressure on traditional wireless communication resource and Mobile Edge Computing (MEC) server. To solve this problem, in this paper, we first propose a DNN model segmentation strategy, and then propose a content-driven joint resource allocation scheme based on vehicle-edge synergy to maximize the accuracy of video content understanding under the constraints of communication and computing resources. Due to the real-time nature of resource allocation and the variability of the environment in vehicular networks, we design a Multi-agent Distributed Q-Learning algorithm to solve such multi-constrained nonlinear programming problems. Finally, the simulation results show that our proposed vehicle-edge synergy based joint resource allocation scheme has better video content understanding performance and system delay.

关键词： Deep learning Computational modeling Simulation Conferences Streaming media Programming Real-time systems

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Digital Over-the-Air Federated Learning in Multi-Antenna systems

arXiv

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arXiv 2023年

作者： Wang, Sihua Chen, Mingzhe Shen, Cong Yin, Changchuan Brinton, Christopher G. The Beijing Laboratory of Advanced Information Network The Beijing Key Laboratory of Network System Architecture and Convergence 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 Charles L. Brown Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA United States The School of Electrical and Computer Engineering Purdue University West LafayetteIN United States

In this paper, the performance optimization of federated learning (FL), when deployed over a realistic wireless multiple-input multiple-output (MIMO) communication system with digital modulation and over-the-air computation (AirComp) is studied. In particular, a MIMO system is considered in which edge devices transmit their local FL models (trained using their locally collected data) to a parameter server (PS) using beamforming to maximize the number of devices scheduled for transmission. The PS, acting as a central controller, generates a global FL model using the received local FL models and broadcasts it back to all devices. Due to the limited bandwidth in a wireless network, AirComp is adopted to enable efficient wireless data aggregation. However, fading of wireless channels can produce aggregate distortions in an AirComp-based FL scheme. To tackle this challenge, we propose a modified federated averaging (FedAvg) algorithm that combines digital modulation with AirComp to mitigate wireless fading while ensuring the communication efficiency. This is achieved by a joint transmit and receive beamforming design, which is formulated as an optimization problem to dynamically adjust the beamforming matrices based on current FL model parameters so as to minimize the transmitting error and ensure the FL performance. To achieve this goal, we first analytically characterize how the beamforming matrices affect the performance of the FedAvg in different iterations. Based on this relationship, an artificial neural network (ANN) is used to estimate the local FL models of all devices and adjust the beamforming matrices at the PS for future model transmission. The algorithmic advantages and improved performance of the proposed methodologies are demonstrated through extensive numerical experiments. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

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A Scalable Computation Offloading Scheme for MEC Based on Graph Neural networks

A Scalable Computation Offloading Scheme for MEC Based on Gr...

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IEEE Globecom Workshops

作者： Tuan Wu Wenpeng Jing Xiangming Wen Zhaoming Lu Shuyue Zhao Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665423915

Recently, computation offloading has become a promising technology to support computation-intensive applications on resource-limited mobile devices (MDs). However, existing offloading schemes suffer from poor generalization and scalability to different applications, since they mainly consider one or a few specific task dependency topologies of the application. Different from the existing schemes, this paper introduces a novel neural network, i.e., graph neural network (GNN), to adapt to the diversity of the applications. Therefore, we propose a GNN and deep reinforcement learning (DRL)-based scheme that optimizes offloading to minimize the long-term average application completion time and MD’s energy consumption. Specifically, considering the variation of the wireless network, a fine-grained task-level scheduling mechanism is presented. In addition, a scalable GNN-enabled preprocessing network is designed to process the state of the various applications and the wireless network. Furthermore, we obtain the optimal scheduling policy via training based on policy gradient algorithm under the stochastic application arrival of the unlimited inter arrival time. Extensive simulations demonstrate the effectiveness and superiority of the proposed scheme under different average inter arrival times. Specifically, the proposed scheme can lower at least 172% of the application completion time and 45% of the energy consumption of the MD compared with other baseline schemes.

关键词： Training Performance evaluation Energy consumption Wireless networks Scalability Optimal scheduling Reinforcement learning

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Content-based Vehicle Selection and Resource Allocation for Federated Learning in IoV

Content-based Vehicle Selection and Resource Allocation for ...

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IEEE Wireless Communications and networking Conference Workshops (WCNCW)

作者： Siyu Wang Fangfang Liu Hailun Xia Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In order to use datasets collected from multiple vehicles to train a machine learning model while ensuring vehicle user privacy, federal learning framework was introduced into the Internet of Vehicles. Federated learning is a distributed learning framework. Under the federated learning framework, the packet error rate and wireless bandwidth have a great influence on the global model training process because the vehicle exchanges model parameters with the central server through the wireless channel. With limited bandwidth, the central server needs to select a more appropriate subset of vehicles candidates to participate in federated learning. In this paper, image classification is taken as a typical application in the Internet of vehicles. The dataset contents of different vehicles are different, and the selection of different subsets of vehicles will affect the accuracy and convergence rate of the global model. Therefore, an algorithm of vehicle selection and wireless resource allocation based on dataset content is proposed. Vehicles selection and wireless resource allocation are designed as an optimization problem by joint considerations of vehicle computing resource, datasets, and wireless resources with the goal of maximizing loss function decay of the global model. Finally, simulation with the CIFAR-10 dataset verifies that the vehicle selection and resource allocation algorithm based on the dataset content is superior to the baseline methods in terms of model accuracy and convergence rate.

关键词： Wireless communication Training Computational modeling Conferences Bandwidth Collaborative work Internet

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WiAgent: Link Selection for CSI-Based Activity Recognition in Densely Deployed Wi-Fi Environments

WiAgent: Link Selection for CSI-Based Activity Recognition i...

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IEEE Conference on Wireless Communications and networking

作者： Xinbin Shen Lingchao Guo Zhaoming Lu Xiangming Wen Shuang Zhou Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In this work, we address the issue of Wi-Fi-based human activity recognition (HAR) system in densely deployed Wi-Fi environments. With the benefit of sufficient information provided by Wi-Fi channel state information (CSI), HAR based on Wi-Fi has become an active research area in recent years. Traditional Wi-Fi CSI-based HAR applications usually focus on utilizing one Wi-Fi transmitter and one or several Wi-Fi receivers to extract the activity-related features, ignoring the communication among multiple Wi-Fi devices in the real world. In this paper, we present a novel Wi-Fi link selection model on the basis of continuous state decision-making process in which CSI is modeled as a part of the state. The model, referred to as WiAgent, takes an action of selecting one Wi-Fi link according to current state, and then updates the state for the choice of the next action. From extensive experiment results, our method performs better than other solutions in a given environment where multiple Wi-Fi transmitters exist.

关键词： Training Transmitters Conferences Decision making Receivers Activity recognition Feature extraction

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An One-dimensional Holographic Antenna for RFID Reader 3

An One-dimensional Holographic Antenna for RFID Reader

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

作者： Ren, Xiaokui Deng, Li Li, Shufang Zhang, Chen Feng, Botao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China

A one-dimensional holographic metasurface antenna that can achieve full-angle symmetrical dual-beam rapid scanning while keeping its position unchanged is proposed. The principle of holographic antenna and beam deflec... 详细信息

ISBN: (纸本)9781728190457

关键词： Holography

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Highly Efficient Generation of Non-diffraction Bessel Beams with Metasurface 3

Highly Efficient Generation of Non-diffraction Bessel Beams ...

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

作者： Zeng, Ting Deng, Li Li, Shufang Feng, Botao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728190457

A reflection metasurface that can generate non-diffraction Bessel beams and achieve anomalous reflection with high efficiency at 5.8 GHz is proposed in this paper. The unit it utilizes has excellent amplitude and phase characteristics, greatly facilitating the construction of the proposed metasurface and laying a solid foundation for the improvement of efficiency. According to non-diffraction theory and anomalous reflection law, two metasurfaces are designed for comparison. The simulation results show that the designed metasurfaces successfully realize the non-diffractive beam with a focusing distance of 126 mm (2.44 λ0), and can bend the normally reflected wave to the direction 10° from the +z direction in a vertical plane 45° away from the +x direction. The average efficiency of the metasurface within the focusing range is as high as 84.5%, thus could be used as radio energy transmission, telecommunication multiplexing and accurate detection devices. © 2020 IEEE.

关键词： Diffraction

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Reflective Metasurface for Controlling the Beam Divergence Angles of Dual-mode OAM Waves 3

Reflective Metasurface for Controlling the Beam Divergence A...

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

作者： He, Xiaoyuan Deng, Li Feng, Botao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture Convergence Beijing University of Posts and Telecommunications Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728190457

For dealing with the problem of receiving multimode orbital-angular momentum (OAM) waves resulting from different beam divergence angles of OAM waves with different topological charges, it is essential to control the beam divergence angles of OAM waves. In this paper, a method is proposed to control the beam divergence angles of multi-mode OAM waves without modifying the inherent topological charges by a reflective metasurface. Based on this method, a reflective metasurface is properly designed to generate dual-mode OAM waves with equal beam divergence angle. As a dual-mode OAM waves generator, the reflective metasurface is composed of 31x31 metal-insulator-metal elements which is capable to manipulate dual-polarized electromagnetic waves (EMWs) independently. Furthermore, as a beam divergence controller, the reflective metasurface is properly divided into two regions that are responsible for +1 mode and +3 mode OAM waves generations. In this way, dual-mode OAM waves with equal beam divergence angle can be generated by the proposed reflective metasurface. The proposed design provides an efficient technology to control the beam divergence angles of multi-mode OAM waves flexibly, which is conductive to simplify the receiving device in OAM based communication systems. © 2020 IEEE.

关键词： Topology

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Use OFDM in OAM Communication to Redcuce Multi-path Effects 3

Use OFDM in OAM Communication to Redcuce Multi-path Effects

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

作者： Shu, Jingyue Deng, Li Li, Shufang Feng, Botao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture Convergence Beijing University of Posts and Telecommunications Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728190457

The orbital angular momentum (OAM) has raised great attention for its potential to enhance the capacity of wireless communication system. The performance of OAM communication is dependent on the accuracy of phase information. In multi-path channel, the accuracy is destroyed. In this paper, we use orthogonal frequency division multiplexing (OFDM)before OAM modulation to enhance communication performance. © 2020 IEEE.

关键词： Orthogonal frequency division multiplexing

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