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Distributed adaptive prescribed-time orbit containment control for satellite cluster flight

Chinese Journal of Aeronautics 2024年第8期37卷 342-357页

作者： Tingting ZHANG Shijie ZHANG Huayi LI Xiangtian ZHAO Research Center of Satellite Technology Harbin Institute of TechnologyHarbin 150080China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

The distributed prescribed-time orbit containment control for the satellite cluster flight with multiple dynamic leaders is *** directed information communication topology between followers is taken into account in the overall *** the satellite mass is assumed to be constant,a distributed prescribed-time orbit containment controller is,firstly,presented to drive the followers into the dynamic convex hull produced by multiple ***,the parameter uncertainty is considered,and a prescribed-time sliding mode estimator is introduced to estimate the desired velocity of each *** on the estimated state,a novel distributed adaptive prescribed-time orbit containment control scheme is *** Lyapunov stability theory is utilized to prove the prescribed-time stability of the closed-loop ***,several numerical simulations and comparison of different control methods are provided to verify the effectiveness and superiority of the proposed control method.

关键词： Satellite cluster Orbit containment control Prescribed-time control Parameter uncertainty Directed communication graph

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Gain and phase errors active calibration method based on neural network for arrays with arbitrary geometry

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The Journal of China Universities of Posts and Telecommunications 2023年第2期30卷 8-17页

作者： Han Ziwen Zhang Zhi Guo Yu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

The manifold matrix of the received signals can be destroyed when the array is with the gain and phase errors,which will affect the performance of the traditional direction of arrival(DOA)estimation *** this paper,a novel active array calibration method for the gain and phase errors based on a cascaded neural network(GPECNN)was *** cascaded neural network contains two parts:signal-to-noise ratio(SNR)classification network and two sets of error estimation *** calibration subnetworks are activated according to the output of the SNR classification network,each of which consists of a gain error estimation network(GEEN)and a phase error estimation network(PEEN),*** disadvantage of neural network topology architecture is changing when the number of array elements varies is addressed by the proposed group calibration ***,due to the data characteristics of the input vector,the cascaded neural network can be applied to arrays with arbitrary geometry without repetitive *** results demonstrate that the GPECNN not only achieves a better balance between calibration performance and calibration complexity than other methods but also can be applied to arrays with different numbers of sensors or different shapes without repetitive training.

关键词： active array calibration cascaded neural network direction of arrival(DOA)estimation

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Container-Based Internet of Vehicles Edge Application Migration Mechanism

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Computers, Materials & Continua 2023年第6期75卷 4867-4891页

作者： Sujie Shao Shihan Tian Shaoyong Guo Xuesong Qiu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China

Internet of Vehicles(IoV)applications integrating with edge com-puting will significantly drive the growth of ***,the contradiction between the high-speed mobility of vehicles,the delay sensitivity of corre-sponding IoV applications and the limited coverage and resource capacity of distributed edge servers will pose challenges to the service continuity and stability of IoV *** application migration is a promising solution that can be supported by application containerization,a technology for seamless cross-edge-server application migration without user ***,this paper proposes the container-based IoV edge application migration mechanism,consisting of three *** first is the migration trigger determination algorithm for cross-border migration and service degra-dation migration,respectively,based on trajectory prediction and traffic awareness to improve the determination *** second is the migration target decision calculation model for minimizing the average migration time and maximizing the average service time to reduce migration times and improve the stability and adaptability of migration *** third is the migration decision algorithm based on the improved artificial bee colony algorithm to avoid local optimal migration *** results show that the proposed migration mechanism can reduce migration times,reduce average migration time,improve average service time and enhance the stability and adaptability of IoV application services.

关键词： Application migration container internet of vehicles edge computing

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Feasibility study of cooperative sensing: radar cross section, synchronization, cooperative cluster,performance and prototype

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Science China(Information Sciences) 2025年第5期68卷 194-212页

作者： Guangyi LIU Rongyan XI Tao JIANG Xiaoqian WANG Lincong HAN Jing JIN Jing DONG Yajuan WANG Yuxiang ZHANG Qixing WANG Jiangzhou WANG Future Research Laboratory China Mobile Research Institute State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications School of Engineering University of Kent

This paper investigates the potential of integrated sensing and communication(ISAC) for the upcoming sixth generation(6G) mobile communications system, which is expected to go beyond communication and incorporate sensing capabilities. A major challenge with conventional ISAC systems is the self-interference caused by using a base station(BS)as both the sensing transmitter and receiver, which requires complex and costly hardware upgrades to enable full *** address this issue, we propose a cooperative sensing approach, where node A acts as the transmitter and node B as the receiver. In this study, we analyze the scattering characteristics of targets in a cooperative sensing scenario and find that the radar cross section(RCS) of unmanned aerial vehicle(UAV) follows a lognormal distribution. We then propose a time-frequency synchronization method, a cooperative sensing cluster construction method, and a multi-node signal-level fusion method to accurately determine the target's position. Simulation results, incorporating non-ideal factors, show that the proposed system can achieve precise target positioning. The accuracy is improved by more than five times compared to mono-static sensing and over 25% compared to result-level fusion methods. Additionally, prototype experimental results validate the feasibility of the proposed system.

关键词： 6G integrated sensing and communication synchronization bistatic RCS multi-node collaboration cooperative cluster prototype

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Network Load Balancing with no Out-of-order Packet for RoCE

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IEEE Network 2024年第2期39卷 194-200页

作者： Luo, Huimin Zhang, Jiao Yu, Mingxuan Pan, Yongchen Pan, Tian Huang, Tao the State Key Laboratory of Networking and Switching Technology BUPT Beijing100876 China the Purple Mountain Laboratories Nanjing211111 China

—Remote Direct Memory Access (RDMA) is becoming a popular high-speed network technology. It uses kernel bypass and zero copy to allow the host to exchange data directly in memory, providing high throughput and low latency while reducing CPU overhead. However, RDMA is based on single-connection transmission and does not make good use of the end-to-end path diversity of the data center. At the same time, existing load balancing algorithms cannot be well applied to RDMA. In this paper, we focus on the flow characteristics of RDMA and load balancing algorithm for RDMA. We first observe the flow characteristics of RDMA and the transmission mode in the lossless environment through experiments, and analyze the reasons for this phenomenon. Then we propose Ursine, a load balancing algorithm for RDMA. It achieves fine-grained RDMA load balancing while avoiding packet out-of-order, and effectively utilizes the end-to-end path diversity in the data center. We implemented the prototype based on DPDK and verified through small-scale experiments that Ursine provides better performance than existing algorithms. Finally, we analyze and look forward to the future and development trends of RDMA load balancing. © 2024 IEEE.

关键词： HIgh speed networks

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Plume:Lightweight and Generalized Congestion Control with Deep Reinforcement Learning

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China Communications 2022年第12期19卷 101-117页

作者： Dehui Wei Jiao Zhang Xuan Zhang Chengyuan Huang State Key Laboratory of Networking and Switching Technology BUPT 100876China

Congestion control(CC)is always an important issue in the field of networking,and the enthusiasm for its research has never diminished in both academia and *** current years,due to the rapid development of machine learning(ML),the combination of reinforcement learning(RL)and CC has a striking ***,These complicated schemes lack generalization and are too heavyweight in storage and computing to be directly implemented in mobile *** order to address these problems,we propose Plume,a high-performance,lightweight and generalized RL-CC *** proposes a lightweight framework to reduce the overheads while preserving the original ***,Plume innovatively modifies the framework parameters of the reward function during the retraining process,so that the algorithm can be applied to a variety of *** results show that Plume can retain almost all the performance of the original model but the size and decision latency can be reduced by more than 50%and 20%,***,Plume has better performances in some special scenes.

关键词： congestion control deep reinforcement learning lightweight generalization

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An efficient quantum proactive incremental learning algorithm

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 45-53页

作者： Lingxiao Li Jing Li Yanqi Song Sujuan Qin Qiaoyan Wen Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing 100876China

In scenarios where a large amount of data needs to be learned,incremental learning can make full use of old knowledge,signif-icantly reduce the computational cost of the overall learning process,and maintain high *** this paper,taking the MaxCut problem as our example,we introduce the idea of incremental learning into quantum computing,and propose a Quantum Proactive Incremental Learning algorithm(QPIL).Instead of a one-off training of quantum circuit,QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices,proactively reducing large-scale problems to smaller ones to solve in steps,providing an efficient solution for ***,some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at ***,in each incremental phase,the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current *** perform experiments on 120 different small-scale graphs,and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR),time cost,anti-forgetting,and solv-ing *** particular,QPIL’s AR surpasses 20%of mainstream quantum baselines,and the time cost is less than 1/5 of *** idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale MaxCut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training MaxCut quantum computing

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Opportunistic admission and resource allocation for slicing enhanced IoT networks

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Digital Communications and Networks 2023年第6期9卷 1465-1476页

作者： Long Zhang Bin Cao Gang Feng National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu611731China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China

Network slicing is envisioned as one of the key techniques to meet the extremely diversified service requirements of the Internet of Things(IoT)as it provides an enhanced user experience and elastic resource *** the context of slicing enhanced IoT networks,both the Service Provider(SP)and Infrastructure Provider(InP)face challenges of ensuring efficient slice construction and high profit in dynamic *** challenges arise from randomly generated and departed slice requests from end-users,uncertain resource availability,and multidimensional resource *** and resource allocation for distinct demands of slice requests are the key issues in addressing these challenges and should be handled effectively in dynamic *** this end,we propose an Opportunistic Admission and Resource allocation(OAR)policy to deal with the issues of random slicing requests,uncertain resource availability,and heterogeneous *** key idea of OAR is to allow the SP to decide whether to accept slice requests immediately or defer them according to the load and price of *** cope with the random slice requests and uncertain resource availability,we formulated this issue as a Markov Decision Process(MDP)to obtain the optimal admission policy,with the aim of maximizing the system ***,the buyer-seller game theory approach was adopted to realize the optimal resource allocation,while motivating each SP and InP to maximize their *** numerical results show that the proposed OAR policy can make reasonable decisions effectively and steadily,and outperforms the baseline schemes in terms of the system reward.

关键词： Slice IoT Markov decision process Game theory Admission and resource allocation

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IncEFL:a sharing incentive mechanism for edge-assisted federated learning in industrial IoT

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Digital Communications and Networks 2025年第1期11卷 106-115页

作者： Jiewei Chen Shaoyong Guo Tao Shen Yan Feng Jian Gao Xuesong Qiu State Key Laboratory of Networking and Switching Technology Beijing University of Post and TelecommunicationsBeijing 100087China Kunming University of Science and Technology Kunming 650031China Yunnan Provincial Academy of Science and Technology Kunming 650228China

As the information sensing and processing capabilities of IoT devices increase,a large amount of data is being generated at the edge of Industrial IoT(IIoT),which has become a strong foundation for distributed Artificial Intelligence(AI)***,most users are reluctant to disclose their data due to network bandwidth limitations,device energy consumption,and privacy *** address this issue,this paper introduces an Edge-assisted Federated Learning(EFL)framework,along with an incentive mechanism for lightweight industrial data *** order to reduce the information asymmetry between data owners and users,an EFL model-sharing incentive mechanism based on contract theory is *** addition,a weight dispersion evaluation scheme based on Wasserstein distance is *** study models an optimization problem of node selection and sharing incentives to maximize the EFL model consumers'profit and ensure the quality of training *** incentive-based EFL algorithm with individual rationality and incentive compatibility constraints is ***,the experimental results verify the effectiveness of the proposed scheme in terms of positive incentives for contract design and performance analysis of EFL systems.

关键词： Federated learning Data sharing Edge intelligence Incentives Contract theory

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Energy Minimization for Heterogenous Traffic Coexistence with Puncturing in Mobile Edge Computing-Based Industrial Internet of Things

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China Communications 2024年第10期21卷 167-180页

作者： Wang Xue Wang Ying Fei Zixuan Zhao Junwei School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Networking and Switching Technology Beijing 100876China

Puncturing has been recognized as a promising technology to cope with the coexistence problem of enhanced mobile broadband(eMBB) and ultra-reliable low latency communications(URLLC)traffic. However, the steady performance of eMBB traffic while meeting the requirements of URLLC traffic with puncturing is a major challenge in some realistic scenarios. In this paper, we pay attention to the timely and energy-efficient processing for eMBB traffic in the industrial Internet of Things(IIoT), where mobile edge computing(MEC) is employed for data processing. Specifically, the performance of eMBB traffic and URLLC traffic in a MEC-based IIoT system is ensured by setting the threshold of tolerable delay and outage probability, respectively. Furthermore,considering the limited energy supply, an energy minimization problem of eMBB device is formulated under the above constraints, by jointly optimizing the resource blocks(RBs) punctured by URLLC traffic, data offloading and transmit power of eMBB device. With Markov's inequality, the problem is reformulated by transforming the probabilistic outage constraint into a deterministic constraint. Meanwhile, an iterative energy minimization algorithm(IEMA) is *** results demonstrate that our algorithm has a significant reduction in the energy consumption for eMBB device and achieves a better overall effect compared to several benchmarks.

关键词： energy minimization enhanced mobile broadband(eMBB)and ultra-reliable low latency communications(URLLC)coexistence industrial Internet of Things(IIoT) mobile edge computing(MEC) puncturing

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