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IEEE/CIC International Conference on Communications in China (ICCC)

作者： Yuan, Shuo Sun, Yaohua Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

ISBN: (纸本)9798350378412

As data-intensive services continue to grow in demand, Satellite-terrestrial networks (STNs) face increasing challenges such as congestion on backhaul links, deteriorating quality of service (QoS) for users, and rising power consumption. Cache-aided STNs present a promising solution by enhancing content delivery and alleviating backhaul load. However, the dynamic nature of low earth orbit (LEO) satellites and the intricate interference between satellite beams and terrestrial stations introduce complexities in resource management. This paper formulates an optimization problem for dynamically cooperative multicast beamforming among satellite beams and terrestrial stations to minimize network costs, including power and backhaul traffic, while adhering to user QoS and resource limits. To tackle this non-convex problem, we propose a successive convex approximation-based iterative algorithm. Simulation results demonstrate the effectiveness of our proposed method and highlight the significant impacts of beam direction and caching strategies on network performance.

关键词： Beamforming

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Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

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China Communications 2024年第2期21卷 227-244页

作者： Meng Meng Bo Hu Shanzhi Chen Jianyin Zhang State Key Lab of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Lab of Wireless Mobile Communication China Academy of Telecommunication TechnologyBeijing 100191China Research Institute of China Mobile Beijing 100053China

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system *** optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method ***, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

关键词： convex optimization intelligent reflecting surface LEO satellite communication OFDM

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Hard sample semantic reconstruction for mandarin visual speech recognition

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DIGITAL SIGNAL PROCESSING 2025年 160卷

作者： Luo, Dawei Xie, Dongliang Zhang, Yuqing Xie, Wanpeng Sun, Baosheng Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Jinghang Res Inst Comp & Commun Beijing Peoples R China

Visual Speech Recognition (VSR) aims to recognize spoken words, phrases, and sentences without relying on audio. Lip movements provide limited semantic information, particularly in Mandarin, characterized by a high prevalence of homophones and near-homophones. In this work, we revisit challenging samples in Mandarin VSR and propose a new framework that leverages semantic reconstruction of hard samples. Our model employs an encoder-decoder architecture, encoding lip movement videos into feature representations processed through an iterative network for semantic reconstruction, ultimately generating text. We utilize three phonetic features to guide the reconstruction: homophone, near-homophone with the same Pinyin, and near-homophone with the same Finals. Furthermore, we implement resampling and sample weighting strategies to better facilitate the learning of challenging samples. The results demonstrate that our model significantly reduces character error rates (CER) for homophones and near-homophones while simultaneously decreasing semantic recognition errors. We provide a detailed analysis of samples with varying recognition difficulties and evaluate our method on the CMLR dataset and the ICSLR dataset. Additionally, we evaluate the generalization performance of our method using over 20,000 samples from previously unseen speakers. The results indicate that our method continues to achieve improvements even with unseen speakers.

关键词： Visual speech recognition Hard samples mining Phonetic guidance learning Semantic reconstruction

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HOLOCOM: Toward Immersive Communication and Interaction with Holographic Video

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IEEE WIRELESS COMMUNICATIONS 2025年第2期32卷 120-129页

作者： Zhu, Yuanwei Wang, Haowen Huang, Yakun Lu, Ping Shi, Wenzhe Zhang, Hengjia Qiao, Xiuquan Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Beijing Univ Posts & Telecommun Beijing 100088 Peoples R China State Key Lab Mobile Network & Mobile Multimedia T Beijing Peoples R China

This article reviews existing surveys and literature on holographic video communication, remote telepresence, and interaction. We first analyze the characteristics, key challenges, scenarios, and emerging applications of holographic video. Based on this analysis, we introduce HoloCom, a cloud-edge collaborative rendering architecture for large-scale communication and cross-platform interaction. The architecture supports mixed heterogeneous 3D content interaction, networking, and resource scheduling. Specifically, HoloCom incorporates two key methodologies using reinforcement learning techniques: quality of experience (QoE)-aware transcoding and system resource management. The QoE-aware transcoding method renders 3D videos into 2D views based on client network conditions and user viewports. The resource management method schedules transcoding tasks across cloud and edge servers to improve task execution efficiency. We implement HoloCom in a prototype system for museum interpretation, consisting of a cloud server, two edge servers, and three user devices. Evaluation results demonstrate that HoloCom achieves adaptive transcoding capabilities across heterogeneous devices and significantly reduces resource overhead for multi-user interactions, leading to a 23 percent improvement in average QoE and a 31 percent reduction in job delay. Finally, we outline future research directions and summarize the implications of the research.

关键词： Surveys Three-dimensional displays Telepresence Transcoding Streaming media Rendering (computer graphics) Real-time systems Resource management Servers Quality of experience

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Symbol Error Rate Analysis of Multi-IRS-Aided Distributed Space-Time Block Coding in MISO Wireless Communication Systems 25

Symbol Error Rate Analysis of Multi-IRS-Aided Distributed Sp...

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IEEE Wireless Communications and networking Conference (IEEE WCNC)

作者： Wang, Xudong Feng, Lei Zhou, Fanqin Li, Wenjing Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

ISBN: (纸本)9798350303582;9798350303599

The intelligent reflecting surface (IRS) serves to manipulate information and modulate signals, facilitating space-time coding in wireless communication. This study presents an innovative model for implementing space-time block coding (STBC), where the base station transmits multiple symbols to a user using multiple IRSs. These IRSs manipulate phase shifts to establish robust links. Initially, statistical characterizations are derived for the sum of independent generalized gamma (GG) random variables, providing expressions for the end-to-end signal-to-noise ratio (SNR). Subsequently, a closed-form expression for symbol error rate (SER) is developed to evaluate reliability performance. Additionally, an asymptotic expression for SER at high transmission power is supplied to outline performance limits. Simulation results reveal that the STBC system assisted by multiple IRSs attains comparable or superior performance when contrasted with the STBC system that employs multiple amplify-and-forward (AF) relays, utilizing a restricted number of reflecting units.

关键词： Intelligent reflecting surface space-time block coding phase shift relay

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Task-Oriented and Semantic-Aware Heterogeneous Networks for Artificial Intelligence of Things: Performance Analysis and Optimization

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IEEE INTERNET OF THINGS JOURNAL 2024年第1期11卷 228-242页

作者： Xu, Xiaodong Xu, Bingxuan Han, Shujun Dong, Chen Xiong, Huachao Meng, Rui Zhang, Ping Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Peng Cheng Lab Dept Broadband Commun Shenzhen 518066 Peoples R China

We propose a novel task-oriented and semantic-aware heterogeneous networks (TOSA-HetNets) framework for multitype Artificial Intelligence of Things (AIoT) devices with various requirements, where the dense edge servers with different transmission capabilities, computing resources, and power consumption are divided into different layers to provide on-demand collaboration for AIoT devices located in accessible areas. Moreover, we propose a device-edge collaboration intelligent tasks inference scheme between edge servers and AIoT devices in TOSA-HetNets, it includes AIoT devices performing semantic features extraction and uploading the corresponding semantic features to the associated edge servers, multiple layers of edge servers collaborating with AIoT devices to execute the intelligent tasks and transmit the intelligent task results back to AIoT devices. To investigate the performance of TOSA-HetNets in supporting device-edge collaboration intelligent tasks inference, we adopt stochastic geometry to obtain the closed-form expressions of average task success probability, power consumption, and network throughput in the downlink transmission. Furthermore, we define a metric of average achievable task back-transmission energy efficiency (TBT-EE) to measure the information bit of successfully transmitted correct intelligent task results with unit power consumption, which is a function of average task success probability, average network throughput on the unit area, and the total power consumption. Meanwhile, we maximize the average achievable TBT-EE by optimizing the density of edge servers and the average semantic compression ratio. Simulation results verify the correctness of the obtained closed-form expressions and show that the edge servers' density and average semantic compression ratio have different influences on the performance of TOSA-HetNets.

关键词： Task analysis Servers Semantics Artificial intelligence Internet of Things Performance evaluation Collaboration Artificial Intelligence of Things (AIoT) device-edge collaboration inference stochastic geometry (SG) task back-transmission energy efficiency (TBT-EE) task-oriented and semantic-aware heterogeneous networks (TOSA-HetNets)

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Access Optimization in 802.11ax WLAN for Load Balancing and Competition Avoidance of IPTV Traffic

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IEEE TRANSACTIONS ON BROADCASTING 2024年第2期70卷 401-412页

作者： Shao, Sujie Zhang, Linlin Qi, Fei Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China China Telecom Res Inst Beijing 102209 Peoples R China

With the improvement of terminal intelligence and the enrichment of digital content, terminal density is showing an explosive growth trend, and the traffic carried by IPTV and other services is rapidly increasing. HDHB WLAN (High-Density High-Bandwidth Wireless LAN) is becoming a dominant form of wireless LAN. However, the RSSI-based access mode has led to a notable load imbalance, and the resource competition mode based on random access intensifies the difficulty of access resource acquisition, which exacerbates the traffic challenges faced by WLAN. IEEE 802.11ax somewhat alleviates traffic pressure, but it does not fundamentally solve these problems. This paper introduces an access optimization mechanism for the 802.11ax HDHB WLAN, which aims to achieve load balancing while considering competition avoidance, alleviating the pressure of IPTV traffic. First, an 802.11ax access optimization architecture for HDHB WLAN is constructed, aimed at alleviating traffic pressure and meeting the quality requirements of IPTV and other services by modifying access processes of terminals. Next, a terminal information acquisition and interactive access control strategy based on the trigger frame is devised to obtain accurate parameter information and facilitate orderly concurrent access control for high-density terminals. Additionally, a load balancing and competition avoidance oriented access control method for HDHB WLAN is proposed, including an access optimization control model, and an access strategy generation algorithm based on the Improved DQN algorithm. Finally, simulation results show that the global throughput and load balancing of HDHB WLAN are improved, consequently reducing overall WLAN traffic pressure.

关键词： WLAN access 802.11ax load balancing competition avoidance

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A Shared Cluster-Based Stochastic Channel Model for Integrated Sensing and Communication Systems

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IEEE TRANSACTIONS ON VEHICULAR techNOLOGY 2024年第5期73卷 6032-6044页

作者： Liu, Yameng Zhang, Jianhua Zhang, Yuxiang Yuan, Zhiqiang Liu, Guangyi Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China China Mobile Res Inst Beijing 100053 Peoples R China

Integrated Sensing And Communication (ISAC) has been recognized as a promising technology in the 6G communication. A realistic channel model is a prerequisite for designing ISAC systems. Most existing channel models independently generate the communication and sensing channels under the same framework. However, due to the multiplexing of hardware resources and the same environment, signals enabled for communication and sensing may experience shared propagation scatterers. This practical sharing feature necessities the joint generation of communication and sensing channels for realistic modeling, where the shared clusters (contributed by the shared scatterers) should be reconstructed. In this paper, we first conduct communication and sensing channel measurements for an indoor scenario at 28 GHz. The power-angular-delay profiles of multipath components are obtained, and the shared scatterers by communication and sensing channels are intuitively observed. Then, a stochastic ISAC channel model is proposed to capture the sharing feature, where shared and non-shared clusters by the two channels are defined and superimposed. To extract those clusters from measured ISAC channels, a KPowerMeans-based joint clustering algorithm is novelly introduced. Finally, stochastic channel characteristics are analyzed, and empirical simulations validate that the channel Sharing Degree (SD) increases with more shared clusters. The proposed model can realistically capture the sharing feature of ISAC channels and is able to evaluate and simulate the channel SD values, which is valuable for the design and deployment of ISAC systems.

关键词： Sensors Antenna measurements Horn antennas Channel models Rotation measurement Position measurement Delays Integrated sensing and communication (ISAC) channel measurements and modeling shared cluster joint clustering sharing degree (SD)

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Queuing Analysis of Energy Harvesting-Aided NOMA-MEC Network

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IEEE TRANSACTIONS ON VEHICULAR techNOLOGY 2024年第9期73卷 14068-14073页

作者： Meng, Yue Zhang, Zhi Huang, Yuzhen Zhang, Ping Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Acad Mil Sci PLA Beijing 100097 Peoples R China

Non-orthogonal multiple access (NOMA) and energy harvesting (EH) have emerged as promising technologies to improve the energy efficiency and capacity of mobile edge computing (MEC) network. In this network, the mobile users utilize harvested energy to support the tasks computed locally or offloaded to MEC server through NOMA transmission. We propose an analytical framework to comprehensively explore the performance of the task processing procedure under EH-aided NOMA-MEC network. Specifically, taking into account the EH constraint, local computing capacity, and NOMA offloading constraint, a four-dimensional Markov chain is introduced to model the task processing in each mobile user. To obtain the steady state of this Markov chain, we employ queuing theory to construct a discrete-time Geo/G/1 queue. By deriving the successful computation probability and the successful offloading probability, the mean response time for task completion is derived, which is a critical performance metric for the network. Numerical simulations are provided to verify the accuracy and facilitate the performance of the proposed framework.

关键词： Task analysis NOMA Servers Energy consumption Computational modeling Signal to noise ratio Resource management MEC EH queuing analysis

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EACE: A document-level event argument extraction model with argument constraint enhancement

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INFORMATION PROCESSING & MANAGEMENT 2024年第1期61卷

作者： Zhou, Ji Shuang, Kai Wang, Qiwei Yao, Xuyang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China China Telecom Res Inst Beijing 102209 Peoples R China

There are two key challenges remaining for the document-level event argument extraction tasks: long-range dependency and same-role argument assignment. The existing methods could not effectively handle the above two challenges at the same time, resulting in argument misidentification and over-or under-extraction, reducing the precision and recall of event argument extraction. In this paper, we propose a document-level event argument extraction model with argument constraint enhancement (EACE), which constructs the argument constraint tree using the hierarchical constraints between arguments to address the above two challenges simultaneously. Specifically, EACE first constructs an argument constraint decoder and uses abstractive summarization to establish the long-range hierarchical constraint relationships between arguments and to obtain the trunk structure of the argument constraint tree, which improves argument identification precision. Secondly, EACE calculates dynamic branch thresholds to expand the branch structure of the argument constraint tree and improve the recall of argument extraction. Extensive experiments on WIKIEVENTS and RAMS have shown that EACE outperforms the baseline models by 2.2% F1 and 0.2% F1, respectively. Moreover, it exceeds the baseline model (PAIE) by up to 17.1% F1 in the same-role argument assignment setting in WIKIEVENTS.

关键词： Event argument extraction Event constraint Document-level Abstractive summarization

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