检索结果-内蒙古大学图书馆

Joint DOA and TOA Estimation for Moving MIMO Radar Based on OFDM-ISAC Signals

IEEE Transactions on Vehicular technology 2025年

作者： Su, Tianshu Zhang, Zhi Chu, Jianhong Zhao, Ruizhe Huang, Yuzhen State Key Laboratory of Networking and Switching Technology Beijing100876 China Academy of Military Sciences of PLA Beijing100091 China

Integrated sensing and communication (ISAC) has emerged as a critical enabling technology for future communication networks because of its higher spectrum efficiency and lower hardware cost. Considering arrays will possibly be mounted on moving platforms in mobile ISAC scenarios, in this paper, array motion is introduced into monostatic multiple input multiple output (MIMO) radar based on orthogonal frequency division multiplexing ISAC (OFDM-ISAC) waveforms to improve the array aperture. Specifically, a time-frequency dual expansion (TFDE) framework, which exploits the channel state information (CSI) containing the entirety of the motion samplings and subcarrier information, is designed to construct a synthetic virtual array with an expanded aperture. With this TFDE framework, two array configurations are proposed and then analyzed, which can generate more virtual elements than the stationary MlMO array. Subsequently, taking into account the issues of parameter coupling, a reduced-complexity multiple signal classification with two-step decoupling (TSD-RC MUSIC) algorithm is pertinently designed to estimate the direction of arrival (DOA) and time of arrival (TOA) of targets while ensuring high estimation accuracy and low complexity. Numerical simulation verifies the effectiveness and superiority of the proposed TFDE framework and TSD-RC MUSIC algorithm under the proposed array configurations. © 1967-2012 IEEE.

关键词： Orthogonal frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

ACL: Adaptive Edge-Cloud Collaborative Learning for Heterogeneous Devices with Unlabeled Local Data

引用

IEEE Transactions on Mobile Computing 2025年

作者： Zhang, Zhengyuan Zhao, Dong Liu, Renhao Yao, Yuxing Li, Xiangyu Ma, Huadong Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology School of Computer Science Beijing100876 China

Edge-cloud collaborative learning emerges as a promising paradigm for adapting pre-trained deep neural network (DNN) models to the ever-changing edge data environments and specific downstream tasks. However, the heterogeneity of edge devices and unlabeled local data hinder the effectiveness of existing collaborative learning approaches. To address the above issues, we propose ACL, a novel adaptive edge-cloud collaborative learning paradigm for heterogeneous devices with unlabeled local data. In ACL, we first use FedNAS, a neural architecture search algorithm designed for collaborative learning to generate a customized model on each participating device, and then a lightweight semi-supervised collaborative learning framework HSSCL is used to fine-tune the pre-trained DNN model. Compared with the SOTA collaborative learning approaches, ACL achieves significant accuracy improvement, averaging 31.5% for image classification and 15.5% for object detection. Furthermore, it reduces time overhead by 3.1-5.1× and memory overhead by 6.3-12.5×. We will release our models and tools. © 2002-2012 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Intelligent Telemetry: P4-Driven Network Telemetry and Service Flow Intelligent Aviation Platform 20th

Intelligent Telemetry: P4-Driven Network Telemetry and Serv...

引用

20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024

作者： Gao, Jing Zhou, Fanqin Dong, Mianxiong Feng, Lei Ota, Kaoru Li, Zijian Fan, Jiawei State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China Department of Information and Electronic Engineering Muroran Institute of Technology Muroran050-8585 Japan Beijing University of Posts and Telecommunications Address Beijing Beijing100876 China

ISBN: (纸本)9789819628292

To address the current challenges in network monitoring and management, such as poor real-time performance, high cost, low accuracy, and slow fault detection and recovery, a P4-driven network telemetry and resource scheduling platform is designed and presented in this paper. This platform embeds telemetry information within data packets, achieving real-time monitoring and anomaly detection of network states. It significantly enhances the granularity and timeliness of network monitoring and employs a path rerouting mechanism for rapid network recovery. The platform boasts high scalability and customizability, allowing on-demand adjustment of telemetry strategies and parameters. It provides low-overhead, business-level telemetry information, offering comprehensive support for diverse services and advancing network management and service quality. This work provides a technical foundation for constructing the next generation of intelligent, efficient, and reliable networks through continuous research and practical application. © IFIP International Federation for Information Processing 2025.

关键词： Telemetering

来源：评论

学校读者我要写书评

暂无评论

SDMCM - Semantic Digital Modulation Constellation Mapping Scheme for Semantic Communication

引用

IEEE Internet of Things Journal 2025年

作者： Teng, Lei An, Wannian Dong, Chen Xu, Xiaodong Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Peng Cheng Laboratory Shenzhen518066 China

The current state of semantic communication research is primarily based on analog modulation, whereas digital communication is more prevalent in practical applications. However, traditional digital modulation constellation mapping designs are not suitable for semantic communication, as they are primarily focused on minimizing the bit error rate of the transmitted data rather than the change in the numerical value of the semantic information. To address this issue, a semantic digital modulation constellation mapping (sDMCM) scheme based on pulse amplitude modulation (PAM) / quadrature amplitude modulation (QAM) is proposed, that considers the internal correlation of the semantic information. In addition, this paper proposes using the mean squared error (MSE) of the semantic information between the transmitter and receiver as a performance metric for semantic communication. This paper also provides the theoretical MSE performance of the proposed sDMCM through formula derivation. Finally, the simulation results match the theoretical results, demonstrating the rationality of the theoretical derivation. Comparing the proposed semantic digital modulation constellation mapping scheme with traditional mapping schemes such as Gray, Pseudo-Gray (Pe-Gray), and structural quadrant (SQ) constellations in an image semantic communication system under the additive white gaussian noise (AWGN) channel, the restored image can tolerate an SNR drop of about 3dB while maintaining the same multi-scale structure similarity (MS-SSIM) performance. In addition, sDMCM is applied in an industrial Internet of Things semantic communication system to validate its role in IoT applications. © 2014 IEEE.

关键词： Gaussian noise (electronic)

来源：评论

学校读者我要写书评

暂无评论

Cache-Aware Cooperative Multicast Beamforming in Dynamic Satellite-Terrestrial Networks

arXiv

引用

arXiv 2025年

作者： Yuan, Shuo Sun, Yaohua Peng, Mugen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China

With the burgeoning demand for data-intensive services, satellite-terrestrial networks (STNs) face increasing backhaul link congestion, deteriorating user quality of service (QoS), and escalating power consumption. Cache-aided STNs are acknowledged as a promising paradigm for accelerating content delivery to users and alleviating the load of backhaul links. However, the dynamic nature of low earth orbit (LEO) satellites and the complex interference among satellite beams and terrestrial base stations pose challenges in effectively managing limited edge resources. To address these issues, this paper proposes a method for dynamically scheduling caching and communication resources, aiming to reduce network costs in terms of transmission power consumption and backhaul traffic, while meeting user QoS demands and resource constraints. We formulate a mixed timescale problem to jointly optimize cache placement, LEO satellite beam direction, and cooperative multicast beamforming among satellite beams and base stations. To tackle this intricate problem, we propose a two-stage solution framework, where the primary problem is decoupled into a short-term content delivery subproblem and a long-term cache placement subproblem. The former subproblem is solved by designing an alternating optimization approach with whale optimization and successive convex approximation methods according to the cache placement state, while cache content in STNs is updated using an iterative algorithm that utilizes historical information. Simulation results demonstrate the effectiveness of our proposed algorithms, showcasing their convergence and significantly reducing transmission power consumption and backhaul traffic by up to 52%. Copyright © 2025, The Authors. All rights reserved.

关键词： Base stations

来源：评论

学校读者我要写书评

暂无评论

Torrent: Re-Architecting End-to-End Transmission for Cross-Datacenter RDMA Networks

Torrent: Re-Architecting End-to-End Transmission for Cross-D...

引用

IEEE Conference on Wireless Communications and networking

作者： Haoyu Pan Yuan Li Zirui Wan Jiao Zhang Tao Huang State key Laboratory of Networking and Switching Technology BUPT China Purple Mountain Laboratories Nanjing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Sustainability is becoming increasingly challenging in today's data centers with limited space, power and connectivity. Large cloud service providers interconnect geographically distributed datacenters for better scalability and availability. Applications running on cross-datacenter network impose great challenges in transport design. In this paper, we identify two inherent limitations of extending the existing transport technology, RDMA, and its Ethernet derivative, RoCE, to long-haul transmission. First, the on-chip resources of commodity RDMA NICs are insufficient for long-haul transmission. Second, applying existing traffic control schemes to inter-datacenter environment exhibits poor performance. Motivated by this, we propose Torrent, a switch-driven transport framework which partitions end-to-end control into three sub-control loops. To achieve the combined goals of fairness and high performance in cross-datacenter scenarios, Torrent employs fast acknowledgment and near-end congestion control on datacenter interconnection (DCI) switches. We implement Torrent prototypes on commodity programmable switches and evaluate it through real-world testbed experiments. Our results show that Torrent can achieve high link utilization over ultra-long distances and quickly converge congested flows to steady rates.

关键词： Data centers Scalability Prototypes switches Ethernet Traffic control System-on-chip Sustainable development Testing

来源：评论

学校读者我要写书评

暂无评论

FaVChat: Unlocking Fine-Grained Facial Video Understanding with Multimodal Large Language Models

arXiv

引用

arXiv 2025年

作者： Zhao, Fufangchen Li, Ming Xu, Linrui Jiang, Wenhao Gao, Jian Yan, Danfeng State Key Laboratory of Networking and Switching Technology BUPT China China Central South University China

Video-based multimodal large language models (VMLLMs) have demonstrated remarkable potential in cross-modal video understanding. However, their abilities in fine-grained face comprehension remain largely underexplored. Given its pivotal role in human-centric intelligence, developing VMLLMs for facial understanding holds a fundamental problem. To address this gap, we propose FaVChat, the first VMLLM specifically designed for fine-grained facial video understanding. To facilitate its training, we construct a large-scale facial video dataset comprising over 60k videos, with the majority annotated with 83 fine-grained facial attributes. These attributes are incorporated to enrich GPT-4o-generated captions, yielding 60k high-quality video-summary pairs and an additional 170k fine-grained question-answering (QA) pairs. To effectively capture rich facial clues, we propose a hybrid model architecture composed of a general visual encoder, a dedicated facial encoder, and a mixture-of-experts-enhanced adapter for adaptive fusion of multi-source visual features. To mitigate information loss during feature transformation, we extract multi-granularity representations from the facial encoder and integrate them into the subsequent LLM. This design enhances the model’s ability to comprehend and respond to questions involving diverse levels of visual details. We employ a progressive training paradigm, transitioning from video summarization to a high-quality subset of video QA, gradually increasing task complexity to enhance the model’s fine-grained visual perception. We conduct extensive zero-shot evaluation on a couple of public benchmarks, demonstrating that FaVChat consistently surpasses existing VMLLMs across multiple tasks. Copyright © 2025, The Authors. All rights reserved.

关键词： Video analysis

来源：评论

学校读者我要写书评

暂无评论

Satellite-Terrestrial Integrated Fog Networks: Architecture, Technologies, and Challenges

arXiv

引用

arXiv 2025年

作者： Yuan, Shuo Peng, Mugen Sun, Yaohua State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China

In the evolution of sixth-generation (6G) mobile communication networks, satellite-terrestrial integrated networks emerge as a promising paradigm, characterized by their wide coverage and reliable transmission capabilities. By integrating with cloud-based terrestrial mobile communication networks, the limitations of low Earth orbit (LEO) satellites, such as insufficient onboard computing capabilities and limited inter-satellite link capacity, can be addressed. In addition, to efficiently respond to the diverse integrated tasks of communication, remote sensing, and navigation, LEO constellations need to be capable of autonomous networking. To this end, this article presents a satellite-terrestrial integrated fog network for 6G. Its system architecture and key technologies are introduced to achieve flexible collaboration between fog satellites and terrestrial cloud computing centers. In particular, key techniques with diverse challenges and their corresponding solutions are discussed, including integrated waveform design and resource management based on fog satellite onboard processing, as well as mobility management and native artificial intelligence based on cloud-fog collaboration. Finally, future challenges and open issues are outlined. Copyright © 2025, The Authors. All rights reserved.

关键词： Satellite links

来源：评论

学校读者我要写书评

暂无评论

SVD-SESDG: Smart Contract Vulnerability Detection technology via Symbol Execution and state Variable Dependency Graph 6th

SVD-SESDG: Smart Contract Vulnerability Detection Technology...

引用

6th International Conference on Blockchain and Trustworthy Systems, BlockSys 2024

作者： Tan, Cong Wu, Jiahao Liu, Zhao Qin, Sujuan State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789819614103

Symbolic execution is a critical technique for detecting vulnerabilities in smart contracts on the blockchain. Existing tools struggle with high false positive rates and often fail to identify multi-function trigger vulnerabilities. To address these challenges, we introduce SVD-SESDG, which constructs a dependency graph for smart contract state variables to identify and analyze critical paths linked to potential vulnerabilities. By focusing on these paths and using actual state values to solve path constraints, SVD-SESDG enhances both efficiency and detection of complex vulnerabilities. Our experiments on an open-source dataset, targeting four types of vulnerabilities, demonstrate that SVD-SESDG significantly outperforms existing tools (Oyente, Mythril, TeEther) in reducing false positives and improving accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ethereum

来源：评论

学校读者我要写书评

暂无评论

EdgeMoE: Empowering Sparse Large Language Models on Mobile Devices

引用

IEEE Transactions on Mobile Computing 2025年

作者： Yi, Rongjie Guo, Liwei Wei, Shiyun Zhou, Ao Wang, Shangguang Xu, Mengwei Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China University of Electronic Science and Technology of China China Zhongguancun Laboratory Beijing China

Large language models (LLMs) such as GPTs and Mixtral-8x7B have revolutionized machine intelligence due to their exceptional abilities in generic ML tasks. Transiting LLMs from datacenters to edge devices brings benefits like better privacy and availability, but is challenged by their massive parameter size and thus unbearable runtime costs. To this end, we present EdgeMoE, an on-device inference engine for mixture-of-expert (MoE) LLMs - a popular form of sparse LLM that scales its parameter size with almost constant computing complexity. EdgeMoE achieves both memory- and compute-efficiency by partitioning the model into the storage hierarchy: non-expert weights are held in device memory;while expert weights are held on external storage and fetched to memory only when activated. This design is motivated by a key observation that expert weights are bulky but infrequently used due to sparse activation. To further reduce the expert I/O swapping overhead, EdgeMoE incorporates two novel techniques: (1) expert-wise bitwidth adaptation that reduces the expert sizes with tolerable accuracy loss;(2) expert preloading that predicts the activated experts ahead of time and preloads it with the compute-I/O pipeline. On popular MoE LLMs and edge devices, EdgeMoE showcase significant memory savings and speedup over competitive baselines. © 2002-2012 IEEE.

关键词： Inference engines

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：