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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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Empirical Predictability Study of SDN Switches

Empirical Predictability Study of SDN Switches

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ACM/IEEE Symposium on Architectures for Networking and communications Systems (ANCS)

作者： Amaury van Bemten Nemanja Ðerić Amir Varasteh Andreas Blenk Stefan Schmid Wolfgang Kellerer Chair of Communication Networks Technical University of Munich Munich Germany Faculty of Computer Science University of Vienna Vienna Austria

To meet their increasingly stringent dependability requirements, communication networks need to be predictable, both in terms of correctness and performance. In principle, Software-Defined networks (SDN) enable such more predictable networks, however, these networks still depend the underlying switches. This paper presents an empirical study of the predictability of SDN switches. Our extensive benchmarking of seven hardware OpenFlow switches from four different manufacturers raises several concerns regarding the dependability of these switches. We uncover several incorrect and unpredictable behaviors and performance issues. In particular, we identify unpredictable behaviors related to the management of flows and buffers, and observe that existing quality-of-service mechanisms, such as priority queuing, introduce unexpected overheads. The latter, in turn, can lead to violations of latency guarantees. Based on our insights, we discuss first solutions toward more predictable architectures.

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Robust Deep Learning-Based Physical Layer communications: Strategies and Approaches

arXiv

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arXiv 2025年

作者： Zhu, Fenghao Wang, Xinquan Zhu, Chen Gong, Tierui Yang, Zhaohui Huang, Chongwen Chen, Xiaoming Zhang, Zhaoyang Debbah, Mérouane College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Polytechnic Institute Zhejiang University Hangzhou310015 China Nanyang Technological University Singapore639798 Singapore KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates

Deep learning (DL) has emerged as a transformative technology with immense potential to reshape the sixth-generation (6G) wireless communication network. By utilizing advanced algorithms for feature extraction and pattern recognition, DL provides unprecedented capabilities in optimizing the network efficiency and performance, particularly in physical layer communications. Although DL technologies present the great potential, they also face significant challenges related to the robustness, which are expected to intensify in the complex and demanding 6G environment. Specifically, current DL models typically exhibit substantial performance degradation in dynamic environments with time-varying channels, interference of noise and different scenarios, which affect their effectiveness in diverse real-world applications. This paper provides a comprehensive overview of strategies and approaches for robust DL-based methods in physical layer communications. First we introduce the key challenges that current DL models face. Then we delve into a detailed examination of DL approaches specifically tailored to enhance robustness in 6G, which are classified into data-driven and model-driven strategies. Finally, we verify the effectiveness of these methods by case studies and outline future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Feature Selection

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Modeling and Performance Analysis of IoT-over-LEO Satellite Systems under Realistic Operational Constraints: A Stochastic Geometry Approach

arXiv

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arXiv 2025年

作者： Dong, Wen-Yu Yang, Shaoshi Zhang, Ping Chen, Sheng School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Key Laboratory of Universal Wireless Communications Ministry of Education Beijing100876 China Key Laboratory of Mathematics and Information Networks Ministry of Education Beijing100876 China Key Laboratory of Networking and Switching Technology Beijing100876 China School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

The growing demand for reliable and extensive connectivity has made low Earth orbit (LEO) satellites aided Internet of Things (IoT) systems a critical area of research. However, current theoretical studies on IoT-over-LEO satellite systems often rely on unrealistic assumptions, such as infinite terrestrial areas and omnidirectional satellite coverage, leaving significant gaps in theoretical analysis for more realistic operational constraints. These constraints involve finite terrestrial area, limited satellite coverage, Earth curvature effect, integral uplink and downlink analysis, and link-dependent interference. To address these gaps, this paper proposes a novel stochastic geometry based model to rigorously analyze the performance of IoT-over-LEO satellite systems. By adopting a binomial point process (BPP) instead of the conventional Poisson point process (PPP), our model accurately characterizes the geographical distribution of a fixed number of IoT devices in a finite terrestrial region. This modeling framework enables the derivation of distance distribution functions for both the links from the terrestrial IoT devices to the satellites (T-S) and from the satellites to the Earth station (S-ES), while also accounting for limited satellite coverage and Earth curvature effects. To realistically represent channel conditions, the Nakagami fading model is employed for the TS links to characterize diverse small-scale fading environments, while the shadowed-Rician fading model is used for the S-ES links to capture the combined effects of shadowing and dominant line-of-sight paths. Furthermore, the analysis incorporates uplink and downlink interference, ensuring a comprehensive evaluation of system performance. The accuracy and effectiveness of our theoretical framework are validated through extensive Monte Carlo simulations. These results provide insights into key performance metrics, such as coverage probability and average ergodic rate, for both individual links and

关键词： Distribution functions

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Multi-scale GCN-assisted two-stage network for joint segmentation of retinal layers and disc in peripapillary OCT images

arXiv

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arXiv 2021年

作者： Li, Jiaxuan Jin, Peiyao Zhu, Jianfeng Zou, Haidong Xu, Xun Tang, Min Zhou, Minwen Gan, Yu He, Jiangnan Ling, Yuye Su, Yikai John Hopcroft Center for Computer Science Shanghai Jiao Tong University Shanghai200240 China Department of Preventative Ophthalmology Shanghai Eye Disease Prevention and Treatment Center Shanghai Eye Hospital Shanghai200040 China Department of Ophthalmology Shanghai General Hospital Shanghai Jiao Tong University Shanghai200080 China Department of Electrical and Computer Engineering The University of Alabama AL35487 United States State Key Lab of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China

An accurate and automated tissue segmentation algorithm for retinal optical coherence tomography (OCT) images is crucial for the diagnosis of glaucoma. However, due to the presence of the optic disc, the anatomical structure of the peripapillary region of the retina is complicated and is challenging for segmentation. To address this issue, we developed a novel graph convolutional network (GCN)-assisted two-stage framework to simultaneously label the nine retinal layers and the optic disc. Specifically, a multi-scale global reasoning module is inserted between the encoder and decoder of a U-shape neural network to exploit anatomical prior knowledge and perform spatial reasoning. We conducted experiments on human peripapillary retinal OCT images. The Dice score of the proposed segmentation network is 0.820 ± 0.001 and the pixel accuracy is 0.830 ± 0.002, both of which outperform those from other state-of-the-art techniques. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical tomography

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Robust Deep Learning-Based Physical Layer communications: Strategies and Approaches

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IEEE Network 2025年

作者： Zhu, Fenghao Wang, Xinquan Zhu, Chen Gong, Tierui Yang, Zhaohui Huang, Chongwen Chen, Xiaoming Zhang, Zhaoyang Debbah, Merouane Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Zhejiang University Polytechnic Institute Hangzhou310015 China Nanyang Technological University 639798 Singapore Khalifa University KU6G Research Center Department of Computer and Information Engineering Abu Dhabi127788 United Arab Emirates

关键词： Feature Selection

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Herriott-cavity-assisted all-optical atomic vector magnetometer

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Physical Review A 2020年第5期101卷 053436-053436页

作者： B. Cai C.-P. Hao Z.-R. Qiu Q.-Q. Yu W. Xiao D. Sheng Hefei National Laboratory of Physical Sciences at the Microscale University of Science and Technology of China Hefei 230026 China Department of Precision Machinery and Precision Instrumentation Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes University of Science and Technology of China Hefei 230027 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science and Center for Quantum Information Technology Peking University Beijing 100871 China

We report an all-optical atomic vector magnetometer using dual Bell-Bloom optical pumping beams in a Rb vapor cell. This vector magnetometer consists of two orthogonal optical pumping beams, with amplitude modulations at Rb85 and Rb87 Larmor frequencies, respectively. We simultaneously detect atomic signals excited by these two pumping beams using a single probe beam in the third direction, and extract the field orientation information using the phase delays between the modulated atomic signals and the driving beams. By adding a Herriott cavity inside the vapor cell, we improve the magnetometer sensitivity. We study the performance of this vector magnetometer in a magnetic field ranging from 100 mG to 500 mG, and demonstrate a field angle sensitivity better than 10 μrad/Hz1/2 above 10 Hz.

关键词： Atomic & molecular processes in external fields Optical pumping Zeeman effect

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Deterministic and Stochastic Simulators for Non-Isotropic V2V-MIMO Wideband Channels

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China communications 2018年第7期15卷 18-29页

作者： Yiran Li Xiang Cheng Nan Zhang State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Wireless Algorithm Department Product Research and Development System ZTE Corporation

In this paper, we consider a novel two-dimensional(2D) geometry-based stochastic model(GBSM) for multiple-input multiple-output(MIMO) vehicle-to-vehicle(V2V) wideband fading channels. The proposed model employs the combination of a two-ring model and a multiple confocal ellipses model, where the signal is sum of the line-of-sight(Lo S) component, single-bounced(SB) rays, and double-bounced(DB) rays. Based on the reference model, we derive some expressions of channel statistical properties, including space-time correlation function(STCF), Doppler spectral power density(DPSD), envelope level crossing rate(LCR) and average fade duration(AFD). In addition, corresponding deterministic and stochastic simulation models are developed based on the reference model. Moreover, we compare the statistical properties of the reference model and the two simulation models in different scenarios and investigate the impact of different vehicular traffic densities(VTDs) on the channel statistical properties of the proposed model. Finally, the great agreement between simulation models and the reference model demonstrates not only the utility of simulation models, but also the correctness of theoretical derivations and simulations.

关键词： vehicle-to-vehicle wideband channels simulation model statistical properties

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Field Trial of Stable Radio Frequency Transfer System in 100 km Metropolitan Optical Fiber Link

Field Trial of Stable Radio Frequency Transfer System in 100...

引用

IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Chenxia Liu Shujin Zhou Zhuoze Zhao Hao Gao Jinting Cong Jianming Shang Xing Chen Bin Luo Song Yu Hong Guo State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Center for Quantum Information Technology Center for Computational Science and Engineering Peking University Beijing China

ISBN: (数字)9781728164304

ISBN: (纸本)9781728167534

We report on a stable radio frequency (RF) transfer experiment via 100 km metropolitan optical fiber link in Beijing area. The link connecting Daniufang and Fangzhuang is composed of two parallel 50-km dark optical fibers with a total loss of 31 dB. The dual phase locked loops (dual-PLL) configuration is designed in our stable fiber-optic RF transfer system. The measured fractional frequency stability (ADEV) of 2.4 GHz RF signal transmission system approaches 1.7×10 -14 @1 s and 2.5×10 -17 @10000 s.

关键词： Optical attenuators Optical fibers Phase locked loops Repeaters Radio frequency Optical noise Signal to noise ratio

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TOAN: Target-Oriented Alignment Network for fine-grained image categorization with few labeled samples

arXiv

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arXiv 2020年

作者： Huang, Huaxi Zhang, Junjie Yu, Litao Zhang, Jian Wu, Qiang Xu, Chang The Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW2007 Australia The Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute of Advanced Communication and Data Science Shanghai University Shanghai200444 China The School of Computer Science University of Sydney SydneyNSW2006 Australia

In this paper, we study the fine-grained categorization problem under the few-shot setting, i.e., each fine-grained class only contains a few labeled examples, termed Fine-Grained Few-Shot classification (FGFS). The core predicament in FGFS is the high intra-class variance yet low inter-class fluctuations in the dataset. In traditional fine-grained classification, the high intra-class variance can be somewhat relieved by conducting the supervised training on the abundant labeled samples. However, with few labeled examples, it is hard for the FGFS model to learn a robust class representation with the significantly higher intra-class variance. Moreover, the inter- and intra-class variance are closely related. The significant intra-class variance in FGFS often aggravates the low inter-class variance issue. To address the above challenges, we propose a Target-Oriented Alignment Network (TOAN) to tackle the FGFS problem from both intra- and inter-class perspective. To reduce the intra-class variance, we propose a target-oriented matching mechanism to reformulate the spatial features of each support image to match the query ones in the embedding space. To enhance the inter-class discrimination, we devise discriminative fine-grained features by integrating local compositional concept representations with the global second-order pooling. We conducted extensive experiments on four public datasets for fine-grained categorization, and the results show the proposed TOAN obtains the state-of-the-art. © 2020, CC BY-NC-SA.

关键词： Image classification

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