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A Spectral Efficient Hybrid Precoding Algorithm for MmWave MIMO Systems

Procedia Computer Science 2020年 174卷 584-590页

作者： Tingting Li Feng Zhao Key Laboratory of Cognitive Radio and Information Processing Guilin University of Electronic Technology Guilin 541004 China Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Yulin China

Millimeter-wave MIMO will use hybrid precoding to improve the spectral efficiency. In this paper, we propose a spectral efficient hybrid precoding algorithm. In order to maximize the projection of hybrid precoding matrix on the optimal precoding matrix, we design the analog precoding matrix by selecting an optimal combination from the candidate matrix. Then, we regard the channel matrix and the obtained analog precoding matrix as an equivalent channel matrix, and use regularized zero-forcing to acquire the digital precoding matrix. Finally, we present simulation results of the proposed hybrid precoding algorithm and show that the algorithm approaches the optimal precoding.

关键词： Millimeter wave MIMO spectral efficiency hybrid precoding candidate matrix equivalent channel matrix

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Parallel implementation of w-projection wide-field imaging

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Science Bulletin 2019年第9期64卷 586-594页

作者： Baoqiang Lao Tao An Ang Yu Wenhui Zhang Junyi Wang Quan Guo Shaoguang Guo Xiaocong Wu Shanghai Astronomical Observatory Key Laboratory of Radio AstronomyChinese Academy of Sciences Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology

w-Projection is a wide-field imaging technique that is widely used in radio synthesis arrays. processing the wide-field big data generated by the future Square Kilometre Array(SKA) will require significant updates to current methods to significantly reduce the time consumed on data processing. data loading and gridding are found to be two major time-consuming tasks in w-projection. In this paper, we investigate two parallel methods of accelerating w-projection processing on multiple nodes: the hybrid Message Passing Interface(MPI) and Open Multi-processing(OpenMP) method based on multicore Central processing Units(CPUs) and the hybrid MPI and Compute Unified Device Architecture(CUDA)method based on Graphics processing Units(GPUs). Both methods are successfully employed and operated in various computational environments, confirming their robustness. The experimental results show that the total runtime of both MPI + OpenMP and MPI + CUDA methods is significantly shorter than that of single-thread processing. MPI + CUDA generally shows faster performance when running on multiple nodes than MPI + OpenMP, especially on large numbers of nodes. The single-precision GPU-based processing yields faster computation than the double-precision processing; while the single-and doubleprecision CPU-based processing shows consistent computational performance. The gridding time remarkably increases when the support size of the convolution kernel is larger than 8 and the image size is larger than 2,048 pixels. The present research offers useful guidance for developing SKA imaging pipelines.

关键词： Radio synthesis arrays Square kilometre array Wide field imaging Parallelization w-Projection

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Wideband polarization reconfigurable antenna based on double C-shaped radiators

Wideband polarization reconfigurable antenna based on double...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Weilong Liang Long Li Zhao Wu Yanhu Huang Qingxiu Ma Jiajun Liang Nanjing Research Institute of Electronics Technology Nanjing P. R. China School of Physics and Telecommunication Engineering Yulin Normal University Yulin P. R. China Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data Processing Yulin Normal University Yulin P. R. China

An enhancing bandwidth tri-polarization reconfigurable antenna based on double C-shaped radiators is proposed. The antenna consists of a modified ground plane, double C-shaped radiators, and a feedline with a simple parasitic stub. The modified ground plane and the parasitic stub can improve the impedance matching, meanwhile, adjust the axial ratio performance. Two PIN diodes are embedded between the C-shaped radiator and the feedline. Three polarization reconfigurable modes can be achieved caused by switching two PIN diodes state, linear polarization (LP), left-hand circular polarization (LHCP), and right-hand circular polarization (RHCP). As the simulated results show, the −10-dB impedance bandwidth reaches 126.6% (1.76-7.83 GHz) in LP mode and 78.4% (2.96-6.78 GHz) in CP modes. And the proposed antenna has a 3-dB axial ratio (AR) bandwidth of 84% (2.6-6.4 GHz) in two CP modes. Therefore, the proposed antenna can meet the requirement of the modern wireless and satellite communication system.

关键词： Wireless communication Polarization Satellite antennas PIN photodiodes Switches Antenna feeds Broadband antennas

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Small file read performance optimization based on redis cache in distributed storage system 13th

Small file read performance optimization based on redis cach...

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13th International Conference on Genetic and Evolutionary Computing, ICGEC 2019

作者： Wei, Bizhong Deng, Liqiang Fan, Ya Ye, Miao School of Computer Science and Information Security Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology GuilinGuangxi541004 China

ISBN: (纸本)9789811533075

At present, small files stored in most of the distributed storage systems account for a large proportion, how to improve the storage efficiency of small file has long been a hot issue in the academic community. In the existing methods, researchers usually integrate small files into content-related large files for association storage. The shortcoming is that if we read some small files in a large file, the entire large file must be read into the cache space, which greatly reduces the utilization of the cache space. To solve this defect, this paper designs a scheme based on the combination of cache replacement optimization algorithm and multi-level cache dynamic elimination mechanism. We compute the content heat value of the cache object by the cache replacement optimization algorithm, and then through the multi-level cache dynamic elimination mechanism we expel the object with low content heat value in the cache space to reserve enough space for the new arrived object. This proposed method not only improves the cache space utilization, but also increases the cache data search efficiency and hit rate. Series of experiments and their result show that the cache hit rate obtained by our proposed method is 14% higher than the LRU cache replacement algorithm and 52% higher than the LFU cache replacement algorithm, which can optimize the reading performance of small files based on Redis cache. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Dynamics

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Research on Star/Galaxy Classification Based on Stacking Ensemble Learning

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Chinese Astronomy and Astrophysics 2020年第3期44卷 345-355页

作者： Chao, L.I. Wen-hui, ZHANG Ran, L.I. Jun-yi, W.A.N.G. Ji-ming, L.I.N. College of Information and Communication Engineering Guilin University of Electronic Technology Guilin 541004 Key Laboratory of Education Ministry for Cognitive Radio and Information Processing Guilin University of Electronic Technology Guilin 541004 Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin 541004 Guangxi College and University Key Laboratory for Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin 541004 Guangxi Key Laboratory for Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology Guilin 541004 Guangxi College and University Key Laboratory for Satellite Navigation and Position Sensing Guilin 541004

Machine learning has achieved great success in many areas today, but the forecast effect of machine learning often depends on the specific problem. An ensemble learning forecasts results by combining multiple base classifiers. Therefore, its ability to adapt to various scenarios is strong, and the classification accuracy is high. In response to the low classification accuracy of the darkest source magnitude set of stars/galaxies in the Sloan Digital Sky Survey (SDSS), a star/galaxy classification algorithm based on the stacking ensemble learning is proposed in this paper. The complete photometric data set is obtained from the SDSS data Release (DR) 7, and divided into the bright source magnitude set, dark source magnitude set, and darkest source magnitude set according to the stellar magnitude. Firstly, the 10-fold nested cross-validation method is used for the darkest source magnitude set, then the Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms are used to establish the base-classifier model;the Gradient Boosting Decision Tree (GBDT) is used as the meta-classifier model. Finally, based on the classification accuracy of galaxies and other indicators, the classification results are analyzed and compared with the results obtained by the Function Tree (FT), SVM, RF, GBDT, Stacked Denoising Autoencoders (SDAE), Deep Belief Nets (DBN), and Deep Perception Decision Tree (DPDT) models. The experimental results show that the stacking ensemble learning model has improved the classification accuracy of galaxies in the darkest source magnitude set by nearly 10% compared to the function tree algorithm. Compared with other traditional machine learning algorithm, stronger lifting algorithm, and deep learning algorithm, the stacking ensemble learning model also has different degrees of improvement. © 2020

关键词： Galaxies: fundamental parameters methods: data analysis Stars: fundamental parameters techniques: photometric

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EXISTENCE AND CONTROLLABILITY FOR NONLINEAR FRACTIONAL CONTROL SYSTEMS WITH DAMPING IN HILBERT SPACES

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Acta Mathematica Scientia 2019年第1期39卷 229-242页

作者： Xiuwen LI Zhenhai LIU Jing LI Chris TISDELL School of Science Nanjing University of Sciences and Technology Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Hunan Province Key Laboratory of Mathematical Modelling and Analysis in Engineering Department of Mathematics and Statistics Changsha University of Science and Technology Faculty of Science The University of New South Wales UNSW

In this paper, we are concerned with the existence of mild solution and controllability for a class of nonlinear fractional control systems with damping in Hilbert *** first step is to give the representation of mild solution for this control system by utilizing the general method of Laplace transform and the theory of(α, γ)-regularized families of operators. Next, we study the solvability and controllability of nonlinear fractional control systems with damping under some suitable sufficient conditions. Finally, two examples are given to illustrate the theory.

关键词： existence controllability fractional control systems damping regularized resolvent family

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BLOWN: A Blockchain Protocol for Single-Hop Wireless Networks under Adversarial SINR

arXiv

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arXiv 2021年

作者： Xu, Minghui Zhao, Feng Zou, Yifei Liu, Chunchi Cheng, Xiuzhen Dressler, Falko The School of Computer Science and Technology Shandong University Qingdao266510 China The Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Yulin China Ernst & Young Shanghai200120 China The School of Electrical Engineering and Computer Science TU Berlin Berlin10587 Germany

Known as a distributed ledger technology (DLT), blockchain has attracted much attention due to its properties such as decentralization, security, immutability and transparency, and its potential of servicing as an infrastructure for various applications. Blockchain can empower wireless networks with identity management, data integrity, access control, and high-level security. However, previous studies on blockchain-enabled wireless networks mostly focus on proposing architectures or building systems with popular blockchain protocols. Nevertheless, such existing protocols have obvious shortcomings when adopted in wireless networks where nodes may have limited physical resources, may fall short of well-established reliable channels, or may suffer from variable bandwidths impacted by environments or jamming attacks. In this paper, we propose a novel consensus protocol named Proof-of-Channel (PoC) leveraging the natural properties of wireless communications, and develop a permissioned BLOWN protocol (BLOckchain protocol for Wireless Networks) for single-hop wireless networks under an adversarial SINR model. We formalize BLOWN with the universal composition framework and prove its security properties, namely persistence and liveness, as well as its strengths in countering against adversarial jamming, double-spending, and Sybil attacks, which are also demonstrated by extensive simulation studies. Copyright © 2021, The Authors. All rights reserved.

关键词： Blockchain

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wChain: A fast fault-tolerant blockchain protocol for multihop wireless networks

arXiv

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arXiv 2021年

作者： Xu, Minghui Liu, Chunchi Zou, Yifei Zhao, Feng Yu, Jiguo Cheng, Xiuzhen Department of Computer Science George Washington University WashingtonDC20052 United States School of Computer Science and Technology Shandong University Qingdao266510 China Guangxi Colleges Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Yulin China Jinan Shandong250353 China Jinan Shandong250014 China Shandong Laboratory of Computer Networks Jinan250014 China

This paper presents wChain, a blockchain protocol specifically designed for multihop wireless networks that deeply integrates wireless communication properties and blockchain technologies under the realistic SINR model. We adopt a hierarchical spanner as the communication backbone to address medium contention and achieve fast data aggregation within O(log N log Γ) slots where N is the network size and Γ refers to the ratio of the maximum distance to the minimum distance between any two nodes. Besides, wChain employs data aggregation and reaggregation, and node recovery mechanisms to ensure efficiency, fault tolerance, persistence, and liveness. The worst-case runtime of wChain is upper bounded by O(f log N log Γ), where f = bN2 c is the upper bound of the number of faulty nodes. To validate our design, we conduct both theoretical analysis and simulation studies, and the results only demonstrate the nice properties of wChain, but also point to a vast new space for the exploration of blockchain protocols in wireless networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal interference

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Anisotropic and Isotropic Implicit Obstacle Problems with Nonlocal Terms and Multivalued Boundary Conditions

SSRN

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SSRN 2022年

作者： Zeng, Shengda Gasinski, Leszek Radulescu, Vicentiu D. Winkert, Patrick Guangxi Colleges Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Guangxi Yulin537000 China Jagiellonian University in Krakow Faculty of Mathematics and Computer Science ul. Lojasiewicza 6 Krakow30-348 Poland Department of Mathematics Pedagogical University of Cracow Podchorazych 2 Cracow30-084 Poland Faculty of Applied Mathematics AGH University of Science and Technology Kraków30-059 Poland Department of Mathematics University of Craiova Craiova200585 Romania China-Romania Research Center in Applied Mathematics Romania Technische Universität Berlin Institut für Mathematik Straße des 17. Juni 136 Berlin10623 Germany

In this paper we study an anisotropic implicit obstacle problem driven by the $(p(\cdot),q(\cdot))$-Laplacian and an isotropic implicit obstacle problem involving a nonlinear convection term (a reaction term depending on the gradient) which contain several interesting and challenging untreated problems. These two implicit obstacle problems have both highly nonlinear and nonlocal functions and three multivalued terms where two of them are appearing on the boundary and the other one is formulated in the domain. Under very general assumptions on the data, we develop general frameworks to examine the nonemptiness and compactness of the set of weak solutions to the problems under consideration. The proofs of our main results use the theory of nonsmooth analysis, Tychonoff's fixed point theorem for multivalued operators, the theory of pseudomonotone operators and variational approach. © 2022, The Authors. All rights reserved.

关键词： Anisotropy

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Study of Star/Galaxy Classification Based on the XGBoost Algorithm

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Chinese Astronomy and Astrophysics 2019年第4期43卷 539-548页

作者： Chao, Li Wen-hui, Zhang Ji-ming, Lin College of Information and Communication Engineering Guilin University of Electronic Technology Guilin 541004 Key Laboratory of Cognitive Radio and Information Processing the Ministry of Education Guilin University of Electronic Technology Guilin 541004 Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin 541004 Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin 541004

Machine learning has achieved great success in many areas today. The lifting algorithm has a strong ability to adapt to various scenarios with a high accuracy, and has played a great role in many fields. But in astronomy, the application of lifting algorithms is still rare. In response to the low classification accuracy of the dark star/galaxy source set in the Sloan Digital Sky Survey (SDSS), a new research result of machine learning, eXtreme Gradient Boosting (XGBoost), has been introduced. The complete photometric data set is obtained from the SDSS-DR7, and divided into a bright source set and a dark source set according to the star magnitude. Firstly, the ten-fold cross-validation method is used for the bright source set and the dark source set respectively, and the XGBoost algorithm is used to establish the star/galaxy classification model. Then, the grid search and other methods are used to adjust the XGBoost parameters. Finally, based on the galaxy classification accuracy and other indicators, the classification results are analyzed, by comparing with the models of function tree (FT), Adaptive boosting (Adaboost), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Stacked Denoising AutoEncoders (SDAE), and Deep Belief Nets (DBN). The experimental results show that, the XGBoost improves the classification accuracy of galaxies in the dark source classification by nearly 10% as compared to the function tree algorithm, and improves the classification accuracy of sources with the darkest magnitudes in the dark source set by nearly 5% as compared to the function tree algorithm. Compared with other traditional machine learning algorithms and deep neural networks, the XGBoost also has different degrees of improvement. © 2019

关键词： Stars: fundamental parameters—galaxies: fundamental parameters—techniques: photometric—methods: data analysis

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