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10th IEEE Smart World Congress, SWC 2024

作者： Feng, Shaowei Li, Zheng Zheng, Mengmeng Yang, Yang Wang, Xin Guo, Caili Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing100876 China China Telecom Digital Intelligence Technology Co. Ltd Beijing100089 China Capital Medical University Beijing Friendship Hospital Department of Urology Beijing100050 China Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing100876 China

ISBN: (纸本)9798331520861

Manual delineation of the kidney region in CT scans is a laborious process. Although existing models have achieved remarkable success in the realm of automated segmentation, they still encounter challenges in effectively modeling both the global and local information. To address this, we introduce Edge-Mix enhanced Mamba (EM-Mamba) for kidney segmentation, which is designed to capture global and local information from multi-scales. EM-Mamba leverages SegMamba as its backbone, utilizing Mamba's efficiency in extracting long-range dependencies. To further enhance the model's integration of local and global information, we introduce the Edge-Mix module, which captures edge information from the shallow layers of the network during the encoding phase and merges it with multi-scale features during the decoding phase. Additionally, a Multi-Scale Convolution (MSC) module is designed to enhance the capability of extracting effective information from 3D medical images, achieving a fusion of rich local and global information across multiple scales. The innovation of the EM-Mamba model lies in its integration of detailed and global information, as well as its robust feature extraction ability in 3D medical image analysis, offering a new solution for precise kidney segmentation. The experimental results show that our framework achieving a Dice score of 9 1. 9 5 % on the KiTS21 dataset and 86.35 % Dice score on our proprietary dataset called Kidney Parenchyma Segmentation (KPS). © 2024 IEEE.

关键词： Edge-Mix Mamba Medical image segmentation Total Kidney Volume

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Broadband Optically Transparent Absorber and Multi-Band Stealth Based on Organic Metasurface

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Chinese Physics Letters 2025年第5期42卷 93-99页

作者： Chuwen Lan Yutong Gao Zehua Gao Hongye Wang Ke Bi Ming Lei Guoan Zhao School of Information and Communication Engineering Beijing Laboratory of Advanced Information NetworksBeijing Key Laboratory of Network System Architecture and ConvergenceBeijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Information Photonics and Optical Communications School of ScienceBeijing University of Posts and TelecommunicationsBeijing 100876China School of Integrated Circuits Beijing University of Posts and TelecommunicationsBeijing 100876China Network Education College of Beijing University of Posts and Telecommunications Beijing 100876China

Optically transparent microwave absorbers and multi-band stealth have extensive potential applications in military defense and wireless communication fields, and thus have attracted considerable attention. So far,most related work is based on inorganic transparent conductive metasurfaces. In this paper, we proposed and experimentally demonstrated a flexible, broadband and optically transparent microwave absorber using an organic metasurface. The metasurface absorber is composed of a sandwich structure, in which electric resonances and magnetic resonances are induced resulting in broadband absorption. A spraying process was developed to prepare this metasurface absorber. Both simulations and experiment show that this metasurface has broadband microwave absorption and good optical transparency. We further found that by using a multi-layer structure, visible, radar,and infrared stealth(multi-band stealth) can be achieved simultaneously. With the advantages of excellent foldability and low cost, the proposed metasurfaces may have applications in military and wireless communication fields.

关键词： microwave absorber broadband microwave absorption organic metasurface metasurface absorber microwave absorbers inorganic transparent conductive metasurfaces military defense sandwich structure

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Reliability and Latency of MmWave Communications Based on Blockage Avoidance in Internet of Vehicles 13

Reliability and Latency of MmWave Communications Based on Bl...

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13th International Conference on Wireless Communications and Signal Processing, WCSP 2021

作者： Cao, Yongxu He, Xinxin Yu, Congqing Yin, Changchuan Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing100876 China

ISBN: (纸本)9781665407854

The millimeter wave(mmWave) communication is a viable approach to support the Gbps data rates that would be required for raw sensor data exchange among autonomous vehicles. However, there is a main challenges resulting from the use of high-frequency bands: the mmWave blockage effect. In this paper, we propose a blockage avoidance based mmWave relay scheme for the Internet of Vehicles. Specifically, we first propose a mmWave link availability identification method based on the vehicle geometric relationship and the spatial correlation between sub-6 GHz signals and mmWave signals. Secondly, in order to improve the reliability of all vehicle sensor data transmission and reduce the overall transmission delay, a resource allocation scheme based on the real-time blocking relationship graph among multilane vehicles is proposed. The simulation show that compared with the baseline, the packet loss rate of proposed scheme is increased by 20%, and the transmission delay is reduced by 80%, which can realize stable, reliable and efficient transmission. © 2021 IEEE.

关键词： Millimeter waves

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Spatial-Temporal Alignment via Optimal Transport for Video-Text Retrieval

Spatial-Temporal Alignment via Optimal Transport for Video-T...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Feng, Zerun Zeng, Zhimin Guo, Caili Li, Zheng Zhang, Yufeng School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China China Telecom Dict Application Capability Center China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Video-text retrieval is one of the most popular branches in the cross-modal research area facing the exponential growth of multimedia services. Present methods typically mea-sure cross-modal similarities only by the cosine metric in a common space. However, this function ignores the in-herent discrepancy between videos and texts for reflecting spatial-temporal contents and fails to align them under the weakly supervised setting. To address this issue, we propose a novel Spatial-Temporal Optimal Transport (STOT) frame-work building upon advances in optimal transport. The spatial and temporal characteristics of videos and texts are carefully considered in STOT and associated by calculating a spatial-temporal alignment distance, which can be implemented as a regularizer for existing models to improve retrieval accu-racy. Extensive experiments are conducted on two video-text datasets with two models as base architectures to demonstrate the outperformance of our framework due to the powerful spatial-temporal alignment capability. © 2022 IEEE.

关键词： Multimedia services

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Location-Based Multi-site Coordination Beam Tracking for Vehicle mmWave Communications 15th

Location-Based Multi-site Coordination Beam Tracking for Veh...

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15th EAI International Conference on Communications and Networking, ChinaCom 2020

作者： He, Xingwen Liu, Danpu Zhang, Zhilong Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9783030677190

Millimeter wave (mmWave) system with massive multiple input multiple output (mMIMO) meets increasing data traffic requirements. However, fast beam tracking for vehicles with high mobility causes enormous overhead, especially in an ultra-dense network (UDN) with frequently base station (BS) handover. In this paper, we proposed a multi-site coordination beam tracking scheme utilizing the spatial correlation of channel state information (CSI) among different sites to reduce the signaling overhead for beam training and handover. The scenario is a hyper-cellular network (HCN) with one control-BS (CBS) and multiple traffic-BSs (TBSs). The proposed scheme consists of two stages. In the first stage, more accurate position measurement of the moving user equipment (UE) can be achieved by using uniform planar array (UPA), and Extended Kalman Filter (EKF) is exploited in CBS to predict the UE’s location in the next slot. In the second stage, the relationship between multi-site and UE’s location is used by the CBS to remotely infer the candidate beam between each TBS and the UE, and make a TBS handover decision when necessary. Given that it is the CBS in charge of beam tracking between all the TBSs and the UE centrally, the overhead for beam training and handover are both efficiently reduced. Simulation results based on realistic 3D scenario show that the proposed scheme can achieve 99% of the optimal spectral efficiency with fewer overhead for beam sweeping and handover signaling. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Extended Kalman filters

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Accurate Positioning with Single Vision Beacon: A Spatial Geometry Based Algorithm 15

Accurate Positioning with Single Vision Beacon: A Spatial Ge...

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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Yang, Boyu Yang, Yang Guo, Caili Zhu, Zhiyu Wang, Xuefei 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 China Spacesat Co. Ltd Beijing100876 China

ISBN: (纸本)9798350324662

This paper proposes a visual positioning algorithm based on feature points and triangular structures on a quick response code (V-FTQ), which can achieve precise position and orientation estimation using only a monocular camera and a single quick response (QR) code beacon. In the considered system, a few QR codes are placed on the ceiling, and a user holds a camera in hand to capture one QR code for positioning. In particular, we first propose an efficient matching mechanism to match the feature points of the captured QR beacon to their projections in the image plane of the camera. Then, based on the geometry relations between the feature points and their projections, V-FTQ is able to calculate the coordinates of the feature points in the camera coordinate. Next, the pose and position of the user are estimated based on linear algebra and spatial geometry. Finally, a singular solution elimination scheme is further proposed to effectively eliminate incorrect solutions estimated by V-FTQ, remaining correct pose and position. The simulation results demonstrate that V-FTQ outperforms similar algorithms in terms of precision and robustness to noise. © 2023 IEEE.

关键词： beacon camera Visual positioning

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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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Research of Epidemic Dynamics Model Considering Individual Movements and Urban Areas 7

Research of Epidemic Dynamics Model Considering Individual M...

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7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021

作者： Pan, Boxu Yang, Jie Wang, Yu Wang, Zehao Zhu, Yuangeng Zhang, Zhiqi Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing100876 China Aisino Corporation Beijing100195 China

ISBN: (纸本)9781665405829

With the rapid spread of COVID-19, hundreds of millions of people worldwide have been infected. In order to cope with the epidemic, experts from various countries have carried out a lot of research works. Most of these works chose to use the traditional SEIR model, but the traditional model doesn't consider the individual's movement in the city. Based on the transmission characteristics of COVID-19, this paper optimized the traditional SEIR model by combining the in-depth mining and processed multiple data, such as the real epidemic data published by some official organizations, as well as data with certain credibility obtained from reference papers, journals or newspapers. Compared with the traditional SEIR model, the proposed model takes into account the impact of individuals' movement and the division of urban functional areas. The outcomes can play a certain role in the prediction and analysis of the spread of the epidemic in cities with regular individuals' movements and functions of urban areas. © 2021 IEEE.

关键词： COVID-19

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Deterministic Overlay Networking for Edge Computing Distributed Cloud in Optical networks

Deterministic Overlay Networking for Edge Computing Distribu...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Mingyang Liu Guochu Shou Junli Xue Mengjie Guo Hongxing Li Yaqiong Liu Yihong Hu School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence

We propose a SD-TSN-based overlay network scheme to realize deterministic transmission for edge computing distributed cloud in optical network. A gateway is implemented to establish data transmission tunnels among clo...

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Arrival Angle Estimation Based on Transfer Learning in Complex Environments

Arrival Angle Estimation Based on Transfer Learning in Compl...

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International Conference on Computer and Communications (ICCC)

作者： Xingjian Li Xinghe Chu Luhan Wang Zhaoming Lu Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Infrmation Networks Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

Signal Angle-of-Arrival estimation has been widely studied as an important sensing technology in Integrated Sensing and Communications, but its performance is limited by complex multipath environments and the scale of antenna arrays. In recent years, learning-based signal angle-of-arrival estimation methods have made breakthroughs, but the effectiveness of learning methods is closely related to the richness of datasets. In the new generation of communication systems, the large-scale deployment of base stations for sensing needs, the data set is difficult to cover a large number of complex and changeable scenarios, and there are problems such as excessive collection scale and difficult labeling. In order to achieve effective estimation of signal angle-of-arrival in complex environments, this paper uses the method of transfer learning to reduce the cost of data set collection and improve the accuracy of estimation. The transfer learning in this paper uses a domain adversarial model to achieve unlabeled transfer from simple to complex scenes. The experiments set up multiple scenarios such as multi-source, multi-path, and array defects. The migration results show that the method can effectively improve the performance of angle-of-arrival estimation in most scenarios, and verify the adaptability of the proposed method to complex environments.

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