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Dynamic Scene Graph Generation of Point Clouds with Structural Representation Learning

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Tsinghua Science and Technology 2024年第1期29卷 232-243页

作者： Chao Qi Jianqin Yin Zhicheng Zhang Jin Tang School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China Standard and Metrology Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China

Scene graphs of point clouds help to understand object-level relationships in the 3D *** graph generation methods work on 2D structured data,which cannot be used for the 3D unstructured point cloud *** point-cloud-based methods generate the scene graph with an additional graph structure that needs labor-intensive manual *** address these problems,we explore a method to convert the point clouds into structured data and generate graphs without given ***,we cluster points with similar augmented features into groups and establish their relationships,resulting in an initial structural representation of the point ***,we propose a Dynamic Graph Generation Network(DGGN)to judge the semantic labels of targets of different *** dynamically splits and merges point groups,resulting in a scene graph with high *** show that our methods outperform other baseline *** output reliable graphs describing the object-level relationships without additional manual labeled data.

关键词： scene graph generation structural representation point cloud

Dual-band dynamic reconfigurable intelligent surface for signal enhancement in millimeter wave

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Science china(Technological Sciences) 2024年第4期67卷 1133-1138页

作者： YAO HuiMing DU XinRun WANG HengBin GAO Song PANG YaChen ZHENG HaiRong GONG HuiWen LI Yi XU JianChun ZHANG JianHua BI Ke State Key Laboratory of Information Photonics and Optical Communications School of ScienceBeijing University of Posts and TelecommunicationsBeijing 100876China beijing Key Laboratory of Intelligent telecommunications Software and Multimedia Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

Millimeter wave with large bandwidth,high transmission rate,and low delay is considered a reliable alternative to cope with the spectrum ***,the fast attenuation and narrow beam characteristics make it difficult to achieve long-distance or wide-range ***,a 1-bit dual-band reflective reconfigurable intelligent surface(RIS)for signal enhancement in millimeter wave with 16×16 elements is designed,fabricated,and *** from most existent RIS,dynamic programming is realized at two separate frequency bands by integrating the PIN diodes and field-programmable gate array(FPGA).Particularly,the beam deflection,dual-beam,and multi-beam are created based on the coding theory and convolution operation,proving the effectiveness of wavefront ***,the far-field patterns and signal power with different coding sequences are measured and *** is indicated that the received signal power is 6–7 dB stronger than that without coding,which shows good agreement with the desired *** proposed reconfigurable metasurface exhibits great potential in beam forming,making it a promising candidate for progressive wireless communication applications.

关键词： dual-band millimeter wave reconfigurable intelligent surface signal enhancement

Quick Hosting Capacity Evaluation Based on Distributed Dispatching for Smart Distribution Network Planning with Distributed Generation

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 128-140页

作者： Bing Sun Ruipeng Jing Leijiao Ge Yuan Zeng Shimeng Dong Luyang Hou the School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China State Grid corporation of china BeijingChina the School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijingChina

The smart distribution network(SDN)is integrat ing increasing distributed generation(DG)and energy storage(ES).Hosting capacity evaluation is important for SDN plan ning with *** and ES are usually invested by users or a third party,and they may form friendly microgrids(MGs)and operate *** centralized dispatching meth od no longer suits for hosting capacity evaluation of SDN.A quick hosting capacity evaluation method based on distributed optimal dispatching is ***,a multi-objective DG hosting capacity evaluation model is established,and the host ing capacity for DG is determined by the optimal DG planning *** steady-state security region method is applied to speed up the solving process of the DG hosting capacity evalua tion ***,the optimal dispatching models are estab lished for MG and SDN respectively to realize the operating *** the distributed dispatching strategy,the dual-side optimal operation of SDN-MGs can be realized by several iterations of power exchange ***,an SDN with four MGs is conducted considering multiple flexible *** shows that the DG hosting capacity of SDN oversteps the sum of the maximum active power demand and the rated branch ***,the annual DG electricity oversteps the maximum active power demand value.

关键词： Smart distribution network(SDN) microgrid hosting capacity multi-objective optimization distributed opti mal dispatching flexible resource

Floquet spectrum and universal dynamics of a periodically driven two-atom system

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Chinese Physics B 2024年第2期33卷 436-443页

作者：谢文柱周正强李轩崔思淼孙明远 School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China

We investigate the Floquet spectrum and excitation properties of a two-ultracold-atom system with periodically driven interaction in a three-dimensional harmonic *** interaction between the atoms is changed by varying the s-wave scattering length in two ways,the cosine and the square-wave *** is found that as the driving frequency increases,the Floquet spectrum exhibits two main features for both modulations,the accumulating and the spreading of the quasienergy levels,which further lead to different dynamical *** accumulation is associated with collective excitations and the persistent growth of the energy,while the spread indicates that the energy is bounded at all *** initial scattering length,the driving frequency and amplitude can all significantly change the Floquet spectrum as well as the ***,the corresponding relation between them is valid ***,we propose a mechanism for selectively exciting the system to one specific state by using the avoided crossing of two quasienergy levels,which could guide preparation of a desired state in experiments.

关键词： Floquet spectrum universal dynamics two-atom system avoided crossing

A credibility-aware swarm-federated deep learning framework in internet of vehicles

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Digital Communications and Networks 2024年第1期10卷 150-157页

作者： Zhe Wang Xinhang Li Tianhao Wu Chen Xu Lin Zhang School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing100876China

Although Federated Deep Learning(FDL)enables distributed machine learning in the Internet of Vehicles(IoV),it requires multiple clients to upload model parameters,thus still existing unavoidable communication overhead and data privacy *** recently proposed Swarm Learning(SL)provides a decentralized machine learning approach for unit edge computing and blockchain-based coordination.A Swarm-Federated Deep Learning framework in the IoV system(IoV-SFDL)that integrates SL into the FDL framework is proposed in this *** IoV-SFDL organizes vehicles to generate local SL models with adjacent vehicles based on the blockchain empowered SL,then aggregates the global FDL model among different SL groups with a credibility weights prediction *** experimental results show that compared with the baseline frameworks,the proposed IoV-SFDL framework reduces the overhead of client-to-server communication by 16.72%,while the model performance improves by about 5.02%for the same training iterations.

关键词： Swarm learning Federated deep learning Internet of vehicles Privacy Efficiency

Combining graph neural network with deep reinforcement learning for resource allocation in computing force networks

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Frontiers of Information Technology & Electronic Engineering 2024年第5期25卷 701-712页

作者： Xueying HAN Mingxi XIE Ke YU Xiaohong HUANG Zongpeng DU Huijuan YAO School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Infrastructure Network Technology Research China Mobile Research InstituteBeijing 100032China

Fueled by the explosive growth of ultra-low-latency and real-time applications with specific computing and network performance requirements,the computing force network(CFN)has become a hot research *** primary CFN challenge is to leverage network resources and computing *** recent advances in deep reinforcement learning(DRL)have brought significant improvement in network optimization,these methods still suffer from topology changes and fail to generalize for those topologies not seen in *** paper proposes a graph neural network(GNN)based DRL framework to accommodate network trafic and computing resources jointly and *** taking advantage of the generalization capability in GNN,the proposed method can operate over variable topologies and obtain higher performance than the other DRL methods.

关键词： Computing force network Routing optimization Deep learning Graph neural network Resource allocation

Resource Allocation for Cognitive Network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning

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china Communications 2024年第6期21卷 53-68页

作者： Zhang Zhenyu Zhang Yong Yuan Siyu Cheng Zhenjie School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China beijing Key Laboratory of Work Safety Intelligent Monitoring(beijing University of Posts and telecommunications) Beijing 100876China

In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay *** users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)*** design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation *** objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of *** results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS ***,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.

关键词： cognitive radio deep reinforcement learning network slicing power-domain non-orthogonal multiple access resource allocation

Variability Analysis for a Two-station Queueing Network in Heavy Traffic with Arrival Processes Driven by Queues

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Acta Mathematicae Applicatae Sinica 2024年第2期40卷 445-466页

作者： Jian CAO Yong-jiang GUO Kai-ming YANG School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China

The law of the iterated logarithm(LIL)for the performance measures of a two-station queueing network with arrivals modulated by independent queues is developed by a strong approximation *** convenience,two arrival processes modulated by queues comprise the external system,all others are belong to the internal *** is well known that the exogenous arrival has a great influence on the asymptotic variability of performance measures in *** the considered queueing network in heavy traffic,we get all the LILs for the queue length,workload,busy time,idle time and departure processes,and present them by some simple functions of the primitive *** LILs tell us some interesting insights,such as,the LILs of busy and idle times are zero and they reflect a small variability around their fluid approximations,the LIL of departure has nothing to do with the arrival process,both of the two phenomena well explain the service station’s situation of being busy all the *** external system shows us a distinguishing effect on the performance measures:an underloaded(overloaded,critically loaded)external system affects the internal system through its arrival(departure,arrival and departure together).In addition,we also get the strong approximation of the network as an auxiliary result.

关键词： two-station queueing network the law of the iterated logarithm(LIL) strong approximation fluid approximation

On the Strong Approximation for a Simple Reentrant Line in Light Traffic Under First-buffer First-served Service Discipline

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Acta Mathematicae Applicatae Sinica 2024年第3期40卷 823-839页

作者： Kai-ming YANG Yong-jiang GUO School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China

For a 2-station and 3-class reentrant line under first-buffer first-served(FBFS)service discipline in light traffic,we firstly construct the strong approximations for performance measures including the queue length,workload,busy time and idle time *** on the obtained strong approximations,we use a strong approximation method to find all the law of the iterated logarithms(LILs)for the above four performance measures,which are expressed as some functions of system parameters:means and variances of interarrival and service times,and characterize the fluctuations around their fluid approximations.

关键词： reentrant line queueing network FBFS service discipline strong approximation LIL Brownian motion