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8th IEEE International Conference on Computer and Communications, ICCC 2022

作者： Zou, Zhuang Xie, Renchao Ren, Yuzheng Yu, F. Richard Huang, Tao Beijing University of Posts and Telecommunications State Key Lab. of Networking and Switching Technology Beijing China Carleton University Depart. of Systems and Computer Eng. OttawaON Canada

ISBN: (纸本)9781665450515

The computing first network (CFN) combines heterogeneous computing force information with network information and improves resource utilization and task execution efficiency through resource perception, service positioning, and task scheduling. However, since the heterogeneous computing force is difficult to express and perceive, and it is distributed on each node of the edge network, it is difficult to schedule tasks uniformly. Therefore, this paper proposes a CFN architecture based on information-centric network (ICN), which uses the naming mechanism of ICN to characterize the computing force and tasks, and the caching mechanism and routing and forwarding mechanism to improve the computing efficiency in the network. Under this network architecture, we study the scheduling problem of multi-user tasks in a period, model it as a multi-objective optimization model, and transform it into a Markov decision process (MDP) to enable control nodes to prioritize tasks and then schedule them to computing nodes for execution, which takes into account the task queue status and node resources. To solve the proposed problem, we use the deep reinforcement learning algorithm to approximate the optimal task scheduling solution. Finally, extensive simulation experiments are conducted to validate the effectiveness and superiority of the proposed scheme. © 2022 IEEE.

关键词： Reinforcement learning

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An NFT-based Distributed Auction Mechanism for Multi-Resource Trading in Computing Power Network 8

An NFT-based Distributed Auction Mechanism for Multi-Resourc...

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8th IEEE International Conference on Computer and Communications, ICCC 2022

作者： Han, Lu Xie, Renchao Ren, Yuzheng Yu, F. Richard Huang, Tao Beijing University of Posts and Telecommunications State Key Lab. of Networking and Switching Technology Beijing China Carleton University Depart. of Systems and Computer Eng. OttawaON Canada

ISBN: (纸本)9781665450515

As a recently proposed network architecture, the computing power network (CPN) combines the ability of end, edge, cloud computing, and transmission network to realize the flexible and efficient scheduling and transaction of ubiquitous multi-resources, such as computing, cache, communications, and intelligent models. However, in CPN, multi-resources are deployed in a distributed manner. So, efficient, reliable and distributed resource transaction solutions are sought. Therefore, in this paper, we propose a non-fungible token (NFT)-based resource transaction scheme for CPN. We use NFT to tokenize and describe multi-resources by metadata to enable applications to network multi-resources efficiently and ensure transaction se-curity. Also, we formulate the trading utility of sellers and buyers and present a trusted trading process. To improve the system efficiency by increasing the matching success rate and simplify the complexity of combinatorial resources matching, we design the decision and pricing policy by distributed double auction mechanism. Simulation results demonstrate the effectiveness of the proposed scheme. © 2022 IEEE.

关键词： Computing power

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Research and Experimental Validation for 3GPP ISAC Channel Modeling Standardization

arXiv

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arXiv 2025年

作者： Zhang, Yuxiang Zhang, Jianhua Zhang, Jiwei Pei, Yuanpeng Liu, Yameng Tian, Lei Jiang, Tao Liu, Guangyi China Mobile Research Institute Beijing Beijing100053 China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

Integrated Sensing and Communication (ISAC) is considered a key technology in 6G networks. An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems. The widely used Geometry-Based Stochastic Model (GBSM), typically applied in standardized channel modeling, mainly focuses on the statistical fading characteristics of the channel. However, it fails to capture the characteristics of targets in ISAC systems, such as their positions and velocities, as well as the impact of the targets on the background. To address this issue, this paper proposes an extended GBSM (E-GBSM) sensing channel model that incorporates newly discovered channel characteristics into a unified modeling framework. In this framework, the sensing channel is divided into target and background channels. For the target channel, the model introduces a concatenated modeling approach, while for the background channel, a parameter called the power control factor is introduced to assess impact of the target on the background channel, making the modeling framework applicable to both mono-static and bi-static sensing modes. To validate the proposed model’s effectiveness, measurements of target and background channels are conducted in both indoor and outdoor scenarios, covering various sensing targets such as metal plates, reconfigurable intelligent surfaces, human bodies, UAVs, and vehicles. The experimental results provide important theoretical support and empirical data for the standardization of ISAC channel modeling. Copyright © 2025, The Authors. All rights reserved.

关键词： Fading channels

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Virtual Power Plant Energy Storage Device state Assessment System Based on 5G Base Stations

Virtual Power Plant Energy Storage Device State Assessment S...

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Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Shan Peng Peng Xu Jiye Hu State Key Lab of Networking and Switching Technology Beijing University of Post and Telecommunications Beijing China Beijing Chuangzhi Xinke Technology Co. Ltd Beijing China

In recent years, the integration of new energy devices into the power system to replace traditional sources has become a trend. Virtual power plants can effectively combine various distributed resources on the demand side. The energy storage devices in 5G base stations, with their widespread coverage and abundant dormant resources, can contribute to regulating power supply and demand within virtual power plants while ensuring the energy efficiency of the base stations. However, the complex geographical distribution and diverse performance of these energy storage devices require a more accurate assessment and secure management. This paper designs and implements a virtual power plant energy storage device state assessment system based on 5G base stations. The system is designed for the interaction of multi-source data from distributed energy storage devices, employing containerized deployment of multidimensional data analysis tasks. It effectively handles a vast amount of information from energy storage devices with varying performance, accomplishing functions such as capacity assessment and safety assessment. Additionally, the system provides a visual interface and safety prompts for power supply-demand analysis and regulation, validating the feasibility of a virtual power plant based on 5G base stations. Finally, comprehensive testing using simulated distributed real-time data collection ensures the effectiveness and timeliness of data acquisition, analysis, application, and energy storage device control.

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Astudy of uplink and downlink channel spatial characteristics in an urban micro scenario at 28GHz

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Frontiers of Information technology & Electronic Engineering 2021年第4期22卷 488-502页

作者： Tao JIANG Jianhua ZHANG Pan TANG Lei TIAN State Key Lab of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

This paper presents an empirical study of the uplink and downlink azimuth angle of arrival(AoA)in an urban micro(UMi)scenario at 28 *** present,most UMi measurements are conducted in the downlink and then the uplink situation is inferred assuming channel *** the channel correlation coefficient of the uplink and downlink can be as high as 0.8,this does not mean that they are the *** a real uplink measurement can accurately describe its channel conditions,and this is what this study does.A receiver equipped with a rotatable horn antenna is mounted at the base station and the user terminal,respectively,in simulating the uplink and *** improve the angular resolution,we extract the multipath components(MPCs)using the space-alternating generalized expectation-maximization ***,a spatial lobe approach is used to cluster the MPCs in the power angular *** matching MPCs with objects in the environment,we find that direct propagation and first-order reflections are dominant in line-of-sight and non-line-of-sight *** comparing our measurement with those in standard channel models,we verify that the AoA of clusters follows a Gaussian distribution in the uplink and *** addition,a two-dimensional Gaussian distribution for ray AoA and power is established to reflect their correlation.

关键词： Channel measurements Millimeter-wave(mmWave) Uplink Downlink Azimuth angle of arrival

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Channel Measurement and Path Loss Modeling from 220 GHz to 330 GHz for 6G Wireless Communications

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China Communications 2021年第5期18卷 19-32页

作者： Pan Tang Jianhua Zhang Haoyu Tian Zhaowei Chang Jun Men Yuxiang Zhang Lei Tian Liang Xia Qixing Wang Jingsuo He State Key Lab of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China China Mobile Research Institute Beijing 100053China Capital Normal University Beijing 100048China

Terahertz(THz)communication has been envisioned as a key enabling technology for sixthgeneration(6G).In this paper,we present an extensive THz channel measurement campaign for 6G wireless communications from 220 GHz to 330 ***,the path loss is analyzed and modeled by using two single-frequency path loss models and a multiplefrequencies path loss *** is found that at most frequency points,the measured path loss is larger than that in the free *** at around 310 GHz,the propagation attenuation is relatively weaker compared to that in the free ***,the frequency dependence of path loss is observed and the frequency exponent of the multiple-frequencies path loss model is ***,the cellular performance of THz communication systems is investigated by using the obtained path loss *** results indicate that the current inter-site distance(ISD)for the indoor scenario is too small for THz ***,the tremendous capacity gain can be obtained by using THz bands compared to using microwave bands and millimeter wave ***,this work can give an insight into the design and optimization of THz communication systems for 6G.

关键词： terahertz channel measurement channel modeling path loss

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A Novel Wideband Geometry-Based Channel Model for HRIS-Assisted THz Inter-room Communications

A Novel Wideband Geometry-Based Channel Model for HRIS-Assis...

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IEEE International Conference on Communications in China (ICCC)

作者： Kaiheng Zhang Nan Ma Xiaoli Yang Ke Peng Yaning Chen Shaoyi Liu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China China Telecommunication Technology Lab China Academy of Information and Communications Technology Beijing China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

For terahertz (THz) inter-room communication, the presence of walls can significantly impact the communication between two rooms. Considering the non-stationarity of the channel, a hybrid reflecting and sensing reconfigurable intelligent surface (HRIS) is introduced to enhance communication quality. In this paper, we propose a novel three-dimensional (3D) nonstationary wideband geometry-based stochastic model (GBSM) for THz inter-room communications assisted by HRIS. This model takes into account the unique properties of THz and HRIS, incorporating a new power distribution method, different phase-shift methods and a Markovian birth-death process. The characteristic of THz, the effect of HRIS on the channel, the number of HRIS cells and different bits of HRIS are investigated. The simulation results demonstrate that the proposed GBSM accurately represents the characteristics of HRIS-assisted THz inter-room communication channels. By implementing an appropriate phase-shift scheme with HRIS, the channel performance can be significantly improved.

关键词： Wireless communication Three-dimensional displays Channel capacity Simulation Human-robot interaction Power distribution Attenuation

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A Graph Routing Algorithm Enhancing Wireless Sensor Networks Lifetime

A Graph Routing Algorithm Enhancing Wireless Sensor Networks...

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2021 IEEE International Conference on Space-Air-Ground Computing, SAGC 2021

作者： Yuxin, Wang Gaofeng, Nie Hui, Tian Beijing Univ. of Posts and Telecommun. State Key Lab. of Networking and Switching Technology Beijing China

ISBN: (纸本)9781665400114

Industrial wireless sensor networks provide wireless communication for devices and sensors. With the limited resources and interference and changes of network conditions, reliability is particularly required in industrial environments. Based on centralized network management, graph routing, which uses redundant paths to ensure reliable transmission, has arisen. In order to enhance latency, lifetime and reliability performance metrics of network, this paper proposes a graph routing algorithm Q-learning Graph Routing Lifetime Enhanced (QGRLE). Routing graph is reconstructed periodically and latency, lifetime and reliability metrics in network are optimized dynamically. Power resources are fully utilized with the consideration of residual energy of nodes. Simulation results show the effectiveness of the proposed algorithms in latency and lifetime performance. © 2021 IEEE.

关键词： Wireless sensor networks

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SA-FedLora: Adaptive Parameter Allocation for Efficient Federated Learning with LoRA Tuning

arXiv

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arXiv 2024年

作者： Yang, Yuning Liu, Xiaohong Gao, Tianrun Xu, Xiaodong Wang, Guanyu State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China UCL Cancer Institute University College London London United Kingdom

Fine-tuning large-scale pre-trained models via transfer learning is an emerging important paradigm for a wide range of downstream tasks, with performance heavily reliant on extensive data. Federated learning (FL), as a distributed framework, provides a secure solution to train models on local datasets while safeguarding raw sensitive data. However, FL networks encounter high communication costs due to the massive parameters of large-scale pre-trained models, necessitating parameter-efficient methods. Notably, parameter efficient fine tuning, such as Low-Rank Adaptation (LoRA), has shown remarkable success in fine-tuning pre-trained models. However, prior research indicates that the fixed parameter budget may be prone to the overfitting or slower convergence. To address this challenge, we propose a Simulated Annealing-based Federated Learning with LoRA tuning (SA-FedLoRA) approach by reducing trainable parameters. Specifically, SA-FedLoRA comprises two stages: initiating and annealing. (1) In the initiating stage, we implement a parameter regularization approach during the early rounds of aggregation, aiming to mitigate client drift and accelerate the convergence for the subsequent tuning. (2) In the annealing stage, we allocate higher parameter budget during the early’heating’ phase and then gradually shrink the budget until the’cooling’ phase. This strategy not only facilitates convergence to the global optimum but also reduces communication costs. Experimental results demonstrate that SA-FedLoRA is an efficient FL, achieving superior performance to FedAvg and significantly reducing communication parameters by up to 93.62%. Copyright © 2024, The Authors. All rights reserved.

关键词： Simulated annealing

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Anomaly Detection of Nodes in Cloud Based on Transfer Learning

Anomaly Detection of Nodes in Cloud Based on Transfer Learni...

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International Conference on Computer and Communications (ICCC)

作者： Hao Wu Peng Xu Ben Yu Anyi Zhang School of Computer Science Beijing University of Posts and Telecommunications Beijing China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

The cloud platform is made up of a series of computing nodes and storage nodes. The timely detection and remediation of node anomalies in the cloud is of critical importance. Traditional anomaly detection methods struggle to effectively manage discontinuous changes in node status. To address this issue, we propose a method for anomaly detection of multidimensional time series data based on pre-trained models and transferring the problem to the image domain, named Sequence to Image Anomaly Detection (StI-AD). This method implements a multidimensional data anomaly detection method based on visual domain pre-training models. By transforming time series data into polar coordinates, the temporal correlation of the coordinates can be reflected. A series of experiments show that this method has a 5–7 percent improvement in accuracy compared to traditional anomaly detection methods and significantly shortens the model training cycle.

关键词： Adaptation models Visualization Correlation Accuracy Computational modeling Time series analysis Transfer learning Transforms Data models Anomaly detection

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