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arXiv 2021年

作者： Wang, Sihua Chen, Mingzhe Yang, Zhaohui Yin, Changchuan Saad, Walid Cui, Shuguang Poor, H. Vincent 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 Princeton University PrincetonNJ08544 United States The Department of Engineering King’s College London WC2R 2LS United Kingdom The Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States Chinese University of Hong Kong Shenzhen518172 China

In this paper, the problem of minimizing the weighted sum of age of information (AoI) and total energy consumption of Internet of Things (IoT) devices is studied. In the considered model, each IoT device monitors a physical process that follows nonlinear dynamics. As the dynamics of the physical process vary over time, each device must find an optimal sampling frequency to sample the real-time dynamics of the physical system and send sampled information to a base station (BS). Due to limited wireless resources, the BS can only select a subset of devices to transmit their sampled information. Thus, edge devices must cooperatively sample their monitored dynamics based on the local observations and the BS must collect the sampled information from the devices immediately, hence avoiding the additional time and energy used for sampling and information transmission. To this end, it is necessary to jointly optimize the sampling policy of each device and the device selection scheme of the BS so as to accurately monitor the dynamics of the physical process using minimum energy. This problem is formulated as an optimization problem whose goal is to minimize the weighted sum of AoI cost and energy consumption. To solve this problem, we propose a novel distributed reinforcement learning (RL) approach for the sampling policy optimization. The proposed algorithm enables edge devices to cooperatively find the global optimal sampling policy using their own local observations. Given the sampling policy, the device selection scheme can be optimized thus minimizing the weighted sum of AoI and energy consumption of all devices. Simulations with real data of PM 2.5 pollution show that the proposed algorithm can reduce the sum of AoI by up to 17.8% and 33.9% and the total energy consumption by up to 13.2% and 35.1%, compared to a conventional deep Q network method and a uniform sampling policy. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy utilization

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Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks

arXiv

引用

arXiv 2018年

作者： Chen, Mingzhe Semiari, Omid Saad, Walid Liu, Xuanlin Yin, Changchuan Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Chinese University of Hong Kong Shenzhen518172 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States Department of Electrical and Computer Engineering University of Colorado Colorado Springs Colorado SpringsCO80918 United States Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States

In this paper, the problem of enhancing the virtual reality (VR) experience for wireless users is investigated by minimizing the occurrence of breaks in presence (BIP) that can detach the users from their virtual world. To measure the BIP for wireless VR users, a novel model that jointly considers the VR application type, transmission delay, VR video quality, and users’ awareness of the virtual environment is proposed. In the developed model, the base stations (BSs) transmit VR videos to the wireless VR users using directional transmission links so as to provide high data rates for the VR users, thus, reducing the number of BIP for each user. Since the body movements of a VR user may result in a blockage of its wireless link, the location and orientation of VR users must also be considered when minimizing BIP. The BIP minimization problem is formulated as an optimization problem which jointly considers the predictions of users’ locations, orientations, and their BS association. To predict the orientation and locations of VR users, a distributed learning algorithm based on the machine learning framework of deep (ESNs) is proposed. The proposed algorithm uses concept from federated learning to enable multiple BSs to locally train their deep ESNs using their collected data and cooperatively build a learning model to predict the entire users’ locations and orientations. Using these predictions, the user association policy that minimizes BIP is derived. Simulation results demonstrate that the developed algorithm reduces the users’ BIP by up to 16% and 26%, respectively, compared to centralized ESN and deep learning algorithms. Copyright © 2018, The Authors. All rights reserved.

关键词： Virtual reality

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Signal Recognition Based on Signal Power Spectrum Fitting Feature Extraction

引用

Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications 2018年第2期41卷 114-118页

作者： Tian, Hao-Min Yin, Liang Ma, Yue Li, Shu-Fang Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Computer Network Research Center Beijing University of Posts and Telecommunications Beijing100876 China School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing100876 China

Aiming at the problem of communication signal service type identification, the author proposes a polynomial fitting factor that extracts the power spectrum of the signal using the linear regression algorithm and the polynomial fitting model in machine learning field as a unified feature of the signal to construct the training set. A multi-layer fully connected neural network classifier model was built on depth learning platform. Compared with the traditional ones, this method has advantages of unifying the radio signal without the need of individual service to extract the personalized features. The power spectrum data of code division multiple access(CDMA) uplink, CDMA downlink, extended global system for mobile(EGSM) uplink, EGSM downlink, wireless local area networks (WLAN) and long time evolution (LTE) signals in the actual radio monitoring data are selected as data set, and 97% classification accuracy is verified. that this method is proven feasible. © 2018, Editorial Department of Journal of Beijing University of Posts and Telecommunications. All right reserved.

关键词： Extraction

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Positioning Using Visible Light Communications: A Perspective Arcs Approach

arXiv

引用

arXiv 2022年

作者： Zhu, Zhiyu Guo, Caili Bao, Rongzhen Chen, Mingzhe Saad, Walid Yang, Yang 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 Engineering Princeton University Princeton NJ08544 United States Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States

Visible light positioning (VLP) is an accurate indoor positioning technology that uses luminaires as transmitters. In particular, circular luminaires are a common source type for VLP, that are typically treated only as point sources for positioning, while ignoring their geometry characteristics. In this paper, the arc feature of the circular luminaire and the coordinate information obtained via visible light communication (VLC) are jointly used for positioning, and a novel perspective arcs approach is proposed for VLC-enabled indoor positioning. The proposed approach does not rely on any inertial measurement unit and has no tilted angle limitaion at the user. First, a VLC assisted perspective circle and arc algorithm (V-PCA) is proposed for a scenario in which a complete luminaire and an incomplete one can be captured by the user. Based on plane and solid geometry theory, the relationship between the luminaire and the user is exploited to estimate the orientation and the coordinate of the luminaire in the camera coordinate system. Then, the pose and location of the user in the world coordinate system are obtained by single-view geometry theory. Considering the cases in which parts of VLC links are blocked, an anti-occlusion VLC assisted perspective arcs algorithm (OA-V-PA) is proposed. In OA-V-PA, an approximation method is developed to estimate the projection of the luminaire's center on the image and, then, to calculate the pose and location of the user. Simulation results show that the proposed indoor positioning algorithm can achieve a 90th percentile positioning accuracy of around 10 cm. Moreover, an experimental prototype is implemented to verify the feasibility. In the established prototype, a fused image processing method is proposed to simultaneously obtain the VLC information and the geometric information. Experimental results in the established prototype show that the average positioning accuracy is less than 5 cm for different tilted angles of the user.

关键词： Visible light communication

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Register pressure sensitive instruction speculative scheduling technology

引用

Jisuanji Yanjiu yu Fazhan/computer Research and Development 2009年第3期46卷 485-491页

作者： Huang, Lei Feng, Xiaobing Lü, Fang Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

Speculation is an important method to overcome control flow constraints during instruction scheduling. On the one hand, speculation can exploit more instruction-level parallelism and improve performance. However, on the other hand, it may also lengthen the live range of variables and increase the register pressure, which in turn results in spilling some variables to memory and deteriorating the performance. Previous work on register pressure sensitive instruction scheduling generally scheduled instructions conservatively when there were too many live variables in the scheduling region. But actually different variables have different spilling costs and different impacts on performance. Here a register pressure sensitive speculative instruction scheduling technology is presented, which not only considers the count of live variables, but also analyzes the benefits and the spilling costs brought by instructions' speculative motions. The decrement of cycles in critical path is calculated as benefit, while the spilled variables are predicted and their spilling cost is used as cost. Only the speculative motion with benefit greater than the cost is permitted in our method. This algorithm has been implemented in Godson Compiler for MIPS architecture. Experiment result shows that the method in this paper can obtain 1.44% speedup on average relative to its register pressure insensitive counterpart on SPEC CPU2000INT benchmarks.

关键词： Costs

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Federated learning for task and resource allocation in wireless high altitude balloon networks

arXiv

引用

arXiv 2020年

作者： Wang, Sihua Chen, Mingzhe Yin, Changchuan Saad, Walid Hong, Choong Seon Cui, Shuguang Vincent Poor, H. Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States Department of Computer Science and Engineering Kyung Hee University Korea Republic of Chinese University of Hong Kong Shenzhen518172 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

In this paper, the problem of minimizing energy and time consumption for task computation and transmission is studied in a mobile edge computing (MEC)-enabled balloon network. In the considered network, each user needs to process a computational task in each time instant, where high-altitude balloons (HABs), acting as flying wireless base stations, can use their powerful computational abilities to process the tasks offloaded from their associated users. Since the data size of each user's computational task varies over time, the HABs must dynamically adjust the user association, service sequence, and task partition scheme to meet the users' needs. This problem is posed as an optimization problem whose goal is to minimize the energy and time consumption for task computing and transmission by adjusting the user association, service sequence, and task allocation scheme. To solve this problem, a support vector machine (SVM)-based federated learning (FL) algorithm is proposed to determine the user association proactively. The proposed SVM-based FL method enables each HAB to cooperatively build an SVM model that can determine all user associations without any transmissions of either user historical associations or computational tasks to other HABs. Given the prediction of the optimal user association, the service sequence and task allocation of each user can be optimized so as to minimize the weighted sum of the energy and time consumption. Simulations with real data of city cellular traffic from the OMNILab at Shanghai Jiao Tong University show that the proposed algorithm can reduce the weighted sum of the energy and time consumption of all users by up to 16.1% compared to a conventional centralized method. Copyright © 2020, The Authors. All rights reserved.

关键词： Support vector machines

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Adaptive Information Bottleneck Guided Joint Source and Channel Coding for Image Transmission

arXiv

引用

arXiv 2022年

作者： Sun, Lunan Yang, Yang Chen, Mingzhe Guo, Caili Saad, Walid Poor, H. Vincent 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 Net works School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Wireless@VT Group Bradley Department of Electrical and Computer Engineering Virginia Tech ArlingtonVA United States The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Joint source and channel coding (JSCC) for image transmission has attracted increasing attention due to its robustness and high efficiency. However, the existing deep JSCC research mainly focuses on minimizing the distortion between the transmitted and received information under a fixed number of available channels. Therefore, the transmitted rate may be far more than its required minimum value. In this paper, an adaptive information bottleneck (IB) guided joint source and channel coding (AIB-JSCC) method is proposed for image transmission. The goal of AIB-JSCC is to reduce the transmission rate while improving the image reconstruction quality. In particular, a new IB objective for image transmission is proposed so as to minimize the distortion and the transmission rate. A mathematically tractable lower bound on the proposed objective is derived, and then, adopted as the loss function of AIB-JSCC. To trade off compression and reconstruction quality, an adaptive algorithm is proposed to adjust the hyperparameter of the proposed loss function dynamically according to the distortion during the training. Experimental results show that AIB-JSCC can significantly reduce the required amount of transmitted data and improve the reconstruction quality and downstream task accuracy. Copyright © 2022, The Authors. All rights reserved.

关键词： Economic and social effects

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

引用

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

arXiv

引用

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

关键词： Resource allocation

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A Self-Repairable Microprocessor

引用

ECS Transactions 2009年第1期18卷

作者： Yuanjiang Xie Xiang Fu Zijian He Yang Zhao Yu Hu Xiaowei Li Institute of Computing Technology Chinese Academy of Sciences Department of Computer Science and Engineering University of California Riverside Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences No. 6 Ke-Xue-Yuan South Road Beijing Beijing 100190 China

With increasing defect density, microprocessors, especially the embedded caches, will encounter more faults. Adding spare resources to replace defective components is a widely accepted method for yield enhancement. In this work, a repair method using content addressable memory combined with spare bits, as well as a novel fault injection method is proposed. With the proposed fault injection technique, various numbers and types of faults can be flexibly injected into the silicon. A wireless sensor network system using our self-repairable microprocessor (SRP) is developed to prove the effectiveness of the proposed technique.

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