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2005 Conference onOptical Network Design and Modelling: Towards the broadband-for-all era, ONDM 2005

作者： Gumaste, Ashwin Zheng, Si Qing Advanced Computer Networks and Architecture Laboratory University of Texas Dallas TX 75083

In this paper we propose a protection strategy for light-trail [1-4] networks for ring topologies. A light-trail is a multi-point lightpath, such that multiple users can take part in communication along the trail, through time (differentiated) non-overlapping connections. Dynamic connections between source-destination pairs can be set up and torn down without the need for optical switch reconfiguration. A light-trail hence represents an opportunistic medium that reduces the uncertainty of provisioning resources for dynamic connections. However, this multi-point flow model leads to a new set of problems in the area of protecting and restoring light-trail based networks. Conventional link protection or path protection techniques are not sufficient for light-trails because of the potential of having multiple possible source-destination pairs in the same trail over time. In this paper we propose a hardware scheme to protect light-trails and further prove its correctness. Further, the scheme is implemented through a failed-traffic assignment algorithm. Subsequently we consider alternative heuristic schemes for implementing the protection scheme proposed. We simulate and compare the simulation results to an analytical model developed. © 2005 IEEE.

关键词： Packet networks

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Cluster-Based Interference-Free MAC Protocol with Load Aware in Software Defined VANET

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China Communications 2020年第12期17卷 217-234页

作者： Yangshui Gao Tao Luo Xinxin He Zhilong Zhang Beijing Laboratory of Advanced Information Networks Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and TelecommunicationsBeijing 100876China School of Mathematics and Computer Dali UniversityDali 671003China

In order to reduce the interference,a novel,cluster-based medium access control(MAC)protocol with load aware for VANETs is proposed in this ***,all vehicles on roads are grouped into stable clusters in the light of their direction,number of neighbors,link reliability,and traffic *** utilizing the advantages of centralized control in software defined VANETs(SDVN),cluster stability can be maintained in ***,a contention-free MAC mechanism composed of inter-cluster multi-channel allocation and intra-cluster dynamic TDMA frame allocation is proposed to prevent co-channel interference and hidden terminal *** results show that the proposed protocol outperforms some existing protocols in cluster stability,delivery ratio,throughput and delay performance.

关键词： SDVN MAC co-channel interference non-safety services cluster

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Joint Optimization of Latency and Energy Consumption for Mobile Edge Computing Based Proximity Detection in Road networks

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China Communications 2022年第4期19卷 274-290页

作者： Tongyu Zhao Yaqiong Liu Guochu Shou Xinwei Yao School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and ConvergenceBeijing 100876China School of Computer Science and Technology Zhejiang University of TechnologyChina

In recent years, artificial intelligence and automotive industry have developed rapidly, and autonomous driving has gradually become the focus of the industry. In road networks, the problem of proximity detection refers to detecting whether two moving objects are close to each other or not in real time. However, the battery life and computing capability of mobile devices are limited in the actual scene,which results in high latency and energy consumption. Therefore, it is a tough problem to determine the proximity relationship between mobile users with low latency and energy consumption. In this article, we aim at finding a tradeoff between latency and energy consumption. We formalize the computation offloading problem base on mobile edge computing(MEC)into a constrained multiobjective optimization problem(CMOP) and utilize NSGA-II to solve it. The simulation results demonstrate that NSGA-II can find the Pareto set, which reduces the latency and energy consumption effectively. In addition, a large number of solutions provided by the Pareto set give us more choices of the offloading decision according to the actual situation.

关键词： proximity detection mobile edge computing road networks constrained multiobjective optimization

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Spectrum efficiency maximization with trajectory design in UAV-enabled mobile relaying

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The Journal of China Universities of Posts and Telecommunications 2019年第4期26卷 17-24页

作者： Sun Chuanzhi Hu Zhiqun Wen Xiangming Lu Zhaoming Qi Hang Beijing Laboratory of Advanced Information Networks Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and TelecommunicationsBeijing 100876China School of Computer and Information Engineering Hubei UniversityWuhan 430062China

With the advantages of low cost and high mobility,unmanned aerial vehicles(UAVs)have played an important role in wireless *** investigate a UAV-enabled mobile relaying system,where a UAV is used as a mobile relay to assist in the communication from a ground source to a ground destination since their direct link is *** the conventional mobile relay in which the UAV adopts straight line or circular trajectory,we consider a more general elliptical trajectory and use realistic channel *** assuming that the UAV employs time-division duplexing(TDD)based decode-and-forward(DF)relaying,we jointly optimize the time allocations and the UAV trajectory to formulate the maximization of spectrum efficiency(SE).The simulation results show that the trajectory we designed achieves a higher SE than the optimal circular trajectory and static relaying.

关键词： UAV mobile relay time allocations elliptical trajectory

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Protection and restoration scheme for light-trail WDM ring networks

Protection and restoration scheme for light-trail WDM ring n...

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International Conference on Optical Network Design and Modeling, ONDM

作者： A. Gumaste Si Qing Zheng Advanced Computer Networks and Architecture Laboratory University of Technology Dallas TX USA

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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Fusing Bluetooth with Pedestrian Dead Reckoning: A Floor Plan-Assisted Positioning Approach

arXiv

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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

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Application of machine learning to manufacturing: results from metal etch

Application of machine learning to manufacturing: results fr...

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IEEE/CHMT(CPMT) International Electronics Manufacturing Technology Symposium

作者： A. Chatterjee D. Croley V. Ramamurti Kui-Yu Chang Advanced Computer Architecture Laboratory Motorola Inc. Austin TX USA Laboratory for Artificial Neural Networks University of Texas Austin Austin TX USA

With the increasing availability of huge quantities of manufacturing data, and the pressures of continuous process improvement and scrap reduction, engineers are beginning to use machine learning techniques along with traditional statistical methods. In this paper, we discuss the application of standard machine learning techniques to analyze, classify, and predict the quality of metal etch using RIE. Three types of data were used to characterize a metal etch: in-process sensor data from the etch chamber, metrology data for critical dimension measurements before and after etch, and metal resistance measurements from probe tests. Three machine learning paradigms were applied: neural networks, induction learning, and case-based reasoning. This paper describes the techniques used, the results obtained, and the conclusions drawn.

关键词： Machine learning Etching Electrical resistance measurement Manufacturing processes Data engineering Statistical analysis Sensor phenomena and characterization Metrology Probes Testing

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Large Scale Model Enabled Semantic Communications Based on Robust Knowledge Distillation

Large Scale Model Enabled Semantic Communications Based on R...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Ding, Kuiyuan Liu, Fangfang Yang, Yang Chen, Mingzhe Guo, Caili 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 The 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

ISBN: (纸本)9798350351255

Large scale artificial intelligence (AI) models possess excellent capabilities in semantic representation and understanding, making them particularly well-suited for semantic encoding and decoding. However, the substantial scale of these AI models imposes unacceptable computational resources and communication delays. To address this issue, we propose a semantic communication scheme based on robust knowledge distillation (RKD-SC) for large scale model enabled semantic communications. In the considered system, a transmitter extracts the features of the source image for robust transmission and accurate image classification at the receiver. To effectively utilize the superior capability of large scale model while make the cost affordable, we first transfer knowledge from a large scale model to a smaller scale model to serve as the semantic encoder. Then, to enhance the robustness of the system against channel noise, we propose a channel-aware autoencoder (CAA) based on the Transformer architecture. Experimental results show that the encoder of proposed RKD-SC system can achieve over 93.3% of the performance of a large scale model while compressing 96.67% number of parameters. Code: https://***/echojayne/RKD-SC. © 2024 IEEE.

关键词： Channel coding

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Visible Light Positioning Based on a Single Luminaire: A Novel Visual Odometry Assisted Algorithm

Visible Light Positioning Based on a Single Luminaire: A Nov...

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IEEE International Conference on Communications (ICC)

作者： Zhiyu Zhu Yang Yang Mingzhe Chen Caili Guo Yipeng Bai Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering 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 Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Visible light positioning (VLP) is a promising positioning technique, which, however, typically requires multiple luminaires to achieve accurate positioning. This paper proposes a novel visual odometry (VO) assisted visible light positioning algorithm (VO-VLP) in achieving positioning with only a single luminaire. In the considered model, a user equipped with a camera jointly uses geometric features in the captured images and coordinates information obtained via visible light communication (VLC) for positioning. The proposed VLP algorithm does not rely on any extra inertial measurement unit and relaxes the tilted angle limitation at the user. In particular, VO-VLP first uses the circle feature of a luminaire to obtain dual normal vectors of the luminaire. Then, the basic principle of VO is used to eliminate the wrong normal vector by exploiting the geometric features in two consecutive images captured when the user moves. Finally, the pose and location of the user are obtained by using an artificially marked point on the luminaire's contour. VO-VLP can achieve accurate positioning with only a single luminaire and a camera. Simulation results show that the proposed indoor positioning algorithm can achieve a 97th-percentile positioning accuracy of around 10 cm.

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