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SSRN 2023年

作者： He, Qingsu Zhang, Xu Han, Qingzhi Sun, Yalu Zhao, Min Wu, Muqing Feng, Xiaowei Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing Beijing100876 China State Grid Gansu Electric Power Company Gansu Lanzhou730050 China

Short-term wind power forecasting can help power systems accurately predict future power supply situations, which is of great significance for promoting the development of power markets, facilitating the popularization and application of new energy sources, and accelerating energy transition and sustainable development. However, the influencing factors of wind power are highly random, volatile, and uncontrollable, as well as the nonlinearity and non-smoothness of the data, which is a great challenge for the prediction accuracy of wind power. To address the above problems, a short-term wind power forecasting approach based on mean Intrinsic Mode Functions (M-IMF), adaptive grouping wavelet packet decomposition (AG-WPD), cross-correlation attention mechanism Convolutional Neural networks (CCAM-CNN), and Long Short-Term Memory Neural Network (LSTM) are proposed. Firstly, for the effect of different influence factors on wind power forecasting, a sample data organization method with the same power but different influence factor values is proposed. Then, an energy entropy feature extraction method based on the AG-WPD of M-IMF is used to enhance the diversity and expression ability of input features. In addition, to fully explore the inherent relationship between different features, a cross-correlation attention mechanism is proposed. In the end, a blended learning model based on CNN and LSTM is proposed to forecast wind power and the experimental results demonstrate that the proposed hybrid model has a significant advantage over other state-of-the-art models involved in this study in terms of prediction accuracy and stability. © 2023, The Authors. All rights reserved.

关键词： Long short-term memory

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RIS-Enhanced LEO Satellite Communication: Joint Passive Beamforming and Orientation Optimization

RIS-Enhanced LEO Satellite Communication: Joint Passive Beam...

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IEEE Globecom Workshops

作者： Ziyuan Zheng Wenpeng Jing Zhaoming Lu Xiangming Wen Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665459761

Low Earth orbit (LEO) satellite communication (SatCom) systems have emerged as a key enabler to provide ubiquitous connectivity in the upcoming generation networks. Yet the conflict between power-limited link budget and long-distance path loss restricts the universal application of LEO SatCom. Fortunately, the reconfigurable intelligent surface (RIS) technique can be an efficient solution to address this issue. In this paper, we incorporate a RIS into the LEO SatCom system to enhance its downlink transmission by introducing a controllable reflection link. A joint RIS passive beamforming and orientation optimization problem is formulated to maximize average throughput at the ground terminal (GT) during the service. The formulated non-convex problem has the unit-modulus constraint on the phase shifters and the piecewise RIS radiation coefficient function related to the predictable satellite trajectory. A two-stage optimization framework is proposed to equivalently solve two sequential subproblems. Specifically, for the passive beamforming subproblem, a closed-form solution is derived at first in compliance with the phase alignment principle. Then, an iterative algorithm is proposed to approximately solve the orientation optimization subproblem. Simulation results show the substantial performance gains on link budget and throughput achieved by the proposed RIS-assisted LEO SatCom scheme.

关键词： Satellites Array signal processing Simulation Low earth orbit satellites Performance gain Throughput Downlink

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Signal Subspace Tracking for AoA Estimation in ISAC systems

Signal Subspace Tracking for AoA Estimation in ISAC Systems

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IEEE Conference on Wireless Communications and Networking

作者： Shixu Dong Jingbo Zhao Zhaoming Lu J. Andrew Zhang Tianpu Yang Jiayin Deng Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China School of Electrical and Data Engineering University of Technology Sydney Sydney Australia China Mobile Group Design Institute CO. Ltd Beijing China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

In indoor integrated sensing and communication (ISAC) systems, angle of arrival (AoA) estimation for moving targets via reflected signals plays an important role in passive sensing. It is a challenging task in the presence of multiple static paths which cause significant interference to AoA estimation for dynamic paths. In this paper, we propose a subspace algorithm that achieves accurate AoA estimation for multiple targets using static communication transceivers in general indoor scenarios. We first use a complex vector to model static paths as a merged static path. Then we design a conditional pseudo-likelihood probability density function (PDF) based on the projection matrix of the signal subspace to bridge the signal subspace with the merged static path and AoAs of dynamic paths. We propose to utilize the Particle Filter to track merged static path and AoAs of dynamic paths via signal subspace. Thereby, the interference caused by static path signals can be eliminated and the accurate AoA estimation results are obtained. Simulation results are provided and validate the proposed algorithm.

关键词： Target tracking Accuracy Heuristic algorithms Simulation Estimation Interference Probability density function

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Multicast SFC Embedding in Software-Defined SAGIN with Heterogeneous Network Resources

Multicast SFC Embedding in Software-Defined SAGIN with Heter...

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IEEE Conference on Wireless Communications and Networking

作者： Deyang Sun Hang Li Zixuan Kong Zhenghe Zhu Yawen Chen Zhaoming Lu Xiangming Wen Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing University of Posts and Telecommunications Beijing China Network and Information Technology Center Changchun Institute of Optics Fine Mechanics and Physics (CIOMP) Chinese Academy of Sciences Changchun China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Space-Air-Ground Integrated Network (SAGIN) is emerged as a promising paradigm to realize the vision of global coverage of sixth generation (6G) communication network. As an efficient communication pattern, multicast communication can be widespread among the ever increasing communication requests in the seamless access SAG IN. However, given the extensive network scale, time varying characteristic and heterogeneity of SAG IN, the coordination of heterogeneous networks brings challenges to resource allocation. With virtualization technologies, the physical resources within SAGIN can be virtualized as Virtual Network Functions (VNFs) in virtual resource pool. To ensure that multicast services can be provided, the network deploys Multicast Service Function Chains (MSFCs) where the service flows is processed by VNFs in order during the transmission. In this paper, we study the problem of jointly optimizing VNF placement and multicast routing within SAG IN while considering that different network segments are equipped with different physical network resources and cost coefficients. We formulate it as an Integer Linear Programming (ILP) problem with the objective of maximizing network revenue while minimizing resource cost of computation and bandwidth. Since it is NP-hard, a low complexity heuristic algorithm is developed to find an efficient solution within polynomial time. Simulation results demonstrate the effectiveness of our proposed model and algorithm, and the deployment cost and blocking rate can be significantly reduced in SAGIN compared with independent terrestrial network.

关键词： Costs Multicast algorithms Service function chaining Simulation Heuristic algorithms Computational modeling Space-air-ground integrated networks

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Exploration of Simulation Teaching Mode for Intelligent Information Network Course

Exploration of Simulation Teaching Mode for Intelligent Info...

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2021 International Conference on Networking and Network Applications, NaNA 2021

作者： He, Yue Li, Hui Li, Yiming Wu, Qiang Ji, Yuefeng Gu, Rentao Fan, Shaobin Beijing Laboratory of Advanced Information Networks Beijing100876 China BUPT Beijing Key Laboratory of Network System Architecture and Convergence Beijing100876 China BUPT School of Information and Communication Engineering Beijing100876 China China Unicom China

ISBN: (纸本)9781665441582

With the rapid development of information technology, the society's demand for information technology talents has become particularly high;how colleges and universities devote themselves to cultivating professional information technology talents is an important direction at present. However, the teacher's evaluation method stays at the exam-oriented education. In the university education, in order to help students with basic professional knowledge to learn more professional knowledge and skills, and to help teachers understand the characteristics of students more objectively, this article discusses how to improve the existing teaching environment and simulation teaching mode. A simulation teaching platform for the "Intelligent Information Network"course is designed with multiple modules for complex network construction. Through the online network simulation teaching platform and the feedback obtained from the platform's use, different students' different problems can be found objectively, and the combination of theory and engineering, the combination of new and old knowledge, and the simplicity of complex software can be realized. © 2021 IEEE.

关键词： Students

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Generation of Multi-Channel Co-axial Quasi-Perfect Vortex Electromagnetic Waves with Equal Divergence Radii Based on Aperture-Shared Metasurface

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IEEE Transactions on Antennas and Propagation 2025年

作者： Deng, Li Yang, Kaiqiao Yin, Kaiyue Chen, Jiawei Qu, Meijun Feng, Botao Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing100876 China Southeast University Institute of Electromagnetic Space State Key Laboratory of Millimeter Wave Nanjing211189 China Communication University of China School of Information and Communication Engineering Beijing Beijing100024 China Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China

Vortex electromagnetic (EM) waves hold significant promise for next-generation wireless communication applications. However, their practical deployment is hindered by varying divergence characteristics across vortex modes with different mode numbers. To overcome this challenge and enable true spatial multiplexing of orbital angular momentum (OAM) waves, a dual-polarized shared-aperture metasurface is proposed. By leveraging both polarization and OAM multiplexing, quasi-perfect vortex (QPV) EM waves with co-axial beams and equal divergence radii are successfully generated at microwave frequencies. Initially, the properties of quasi-perfect vortex waves in the microwave band are analyzed, followed by the design of a dual-polarized metasurface unit. This unit integrates parasitic damping-coupled patches based on the traditional Jerusalem cross structure, providing polarization-independent control and approximately 360° phase-tuning capability. Furthermore, simulations validate the effectiveness of the dual-polarized single-mode metasurface design. Based on this, the concept is extended to a 4-channel multiplexing metasurface, operating at 15 GHz and capable of generating QPV waves. Finally, experimental results from the fabricated metasurface demonstrate the generation of QPV waves with OAM mode numbers 0, +2, +1, and -1, achieving simulated and measured OAM mode purities of 0.835 and 0.70, respectively. The experimental data closely aligns with simulations, confirming the effectiveness of the design. This study offers new insights into generating and applying perfect vortex EM waves, paving the way for high-capacity near-field wireless communication systems and advanced control of novel EM physical dimensions. © 1963-2012 IEEE.

关键词： Near field communication

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MIMO Radar Aided Beam Selection in Millimeter Wave V2I Communications

MIMO Radar Aided Beam Selection in Millimeter Wave V2I Commu...

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International Conference on Computer and Communications (ICCC)

作者： Dianang Li Xinxin He Jie Lv Tao Wang Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

The multiple-in-multiple-out (MIMO) radar is deployed to assist the millimeter wave (mmWave) communication with low beam training overhead in vehicle-to-infrastructure (V2I), which has attracted increasing attention. This paper proposes a structured weighted radar aided beam selection. To be specific, since the spatial information provided by radar involves inevitable inaccuracy due to the angle deviation, we calculate the probability distribution of the codewords based on the deviation angle and use it for designing the training codebook. Furthermore, beam selection is formulated as prior weighted sparse signal recovery problem, where the prior structured-weight for communication is determined by the spatial congruence with radar channel, and the difference between two frequency bands is derived to correct the weight. The resulting prior structured weight is further deployed to the orthogonal matching pursuit algorithm to enhance its performance. Simulation results demonstrate that the proposed method provides the efficient and reliable beam selection performance of the mobility mmWave channel with fewer training overhead.

关键词： Training MIMO radar Vehicle-to-infrastructure Simulation Matching pursuit algorithms Millimeter wave radar Radar tracking

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Work in Progress: Exploration of Research-study Dual Cycle Mode for Simulation Practice Teaching

Work in Progress: Exploration of Research-study Dual Cycle M...

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IEEE World Engineering Education Conference (EDUNINE)

作者： Hui Li Qiang Wu Zhiqun Gu Rentao Gu Yuefeng Ji Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Traditional information course simulation teaching is often based on specific simulation software to simulate and verify some theoretical models in the course knowledge points. Under the constraints of fixed topics and methods, the limited teaching content leads to the limitation of students' innovation ability and practical ability. In view of the above problems, the present paper undertakes the progress of the dual center teaching model, with the help of an extensible online simulation platform, to design the simulation problems of related artificial intelligence algorithms for the actual engineering problems in the communication network, forming a simulation teaching mode of research and learning double cycle through which students simulate cases and apply these algorithms to innovation and entrepreneurship practice.

关键词： Technological innovation Entrepreneurship Learning (artificial intelligence) Software Communication networks Engineering education

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Image Coding and Compression Method Based on Semantics of Pixels for Semantic Communication

Image Coding and Compression Method Based on Semantics of Pi...

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IEEE International Conference on Communications in China Workshops (ICCC)

作者： Qizheng Sun Caili Guo Rui Tang Chuanhong Liu Yufeng Zhang Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing China Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing China China Telecom Dict Application Capability Center Beijing University of Posts and Telecommunications

ISBN: (数字)9798350377675

ISBN: (纸本)9798350377682

Semantic image transmission is promising for both image reconstruction or downstream task execution. However, it is still challenging to simultaneously achieve pleasing visual clarity and superior downstream tasks. To tackle this issue, we propose a semantic-preserving image coding and compression method based on the semantics of pixels (SP). Specifically, we first project the semantic importance onto pixels, which is quantified by a gradient-based mechanism. Then, we design an SP-based loss function to train the image coding and compression network. This loss function not only preserves the semantic information to boost the performance of intelligent tasks but also preserves the pixel information to achieve pleasing visual effects. Experimental results confirm improvements in both aspects of performance. Especially for intelligent task performance, the proposed method achieves up to 22.22 % and 78.40 % performance gain ratio compared with the state of art deep learning-based and the traditional method, respectively.

关键词： Training Fading channels Image coding Image communication Semantics Performance gain Visual effects Generative adversarial networks Encoding Image reconstruction

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Two-Stream Convolutional Neural Network for Skeleton-Based Action Recognition 6

Two-Stream Convolutional Neural Network for Skeleton-Based A...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Shi, Yao Wu, Muqing Xu, Weiyao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186351

Skeleton-based action recognition has attracted much attention while the skeleton contains important information related to action. How to efficiently use the temporal and spatial information in skeleton data is still an open problem. We propose in this paper a two-stream convolutional neural network which combines joints information with bone information to recognize actions. More specifically, the input of one stream is the joints position information (point information) and the other is the bone vector information (direction and length information) which is more informative in local relative change. Every stream also integrates motion information which represent temporal difference of inputs. Besides, we enhance our network using asymmetric convolution blocks (ACBlock). ACBlock can capture features efficiently and reduce the negative effects of rotation and deformation which contributes to feature extraction. Experiments on NTU-RGB+D datasets demonstrate the advantage of the proposed model on effectiveness of the novel model to recognize the action. © 2020 IEEE.

关键词： Convolution

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