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Titlebook: Communications and Networking; 16th EAI Internation Honghao Gao,Jun Wun,Jun Yu Conference proceedings 2022 ICST Institute for Computer Scie

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书目名称Communications and Networking
副标题16th EAI Internation
编辑Honghao Gao,Jun Wun,Jun Yu
视频videohttp://file.papertrans.cn/231/230526/230526.mp4
丛书名称Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
图书封面Titlebook: Communications and Networking; 16th EAI Internation Honghao Gao,Jun Wun,Jun Yu Conference proceedings 2022 ICST Institute for Computer Scie
描述This proceedings constitutes the refereed proceedings of the 16.th. International Conference on Communications and Networking, ChinaCom 2021, held in November 2021. Due to COVID-19 pandemic the conference was held virtually.. The 47 full papers and 5 workshop papers presented were carefully selected from 130 submissions. The papers are organized in topical sections on Scheduling and Transmission Optimization in Edge Computing; Complex System Optimization in Edge Computing; Network Communication Enhancement; Signal Processing and Communication Optimization; Deep Learning and Vehicular Communication; Edge Computing and Deep Learning; Finite Blocklength and Distributed Machine Learning; Deep Learning and Network Performance Optimization; Edge Computing and Reinforcement Learning..
出版日期Conference proceedings 2022
关键词bandwidth; communication; communication channels (information theory); communication systems; computer h
版次1
doihttps://doi.org/10.1007/978-3-030-99200-2
isbn_softcover978-3-030-99199-9
isbn_ebook978-3-030-99200-2Series ISSN 1867-8211 Series E-ISSN 1867-822X
issn_series 1867-8211
copyrightICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2022
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Millimeter Wave Hybrid Precoding Based on Deep Learninggorithm based on deep learning was proposed for millimeter wave massive MIMO system. Firstly, the hybrid precoding design problem was transformed into an exhaustive search problem for the analog precoder/combiner using the equivalent channel matrix. Then, a deep learning model was constructed to lea
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Open-Set Recognition Algorithm of Signal Modulation Based on Siamese Neural Network Firstly, the convolutional neural network (CNN) is employed to extract the features of the original signal to obtain the multi-dimensional feature vector, thereby constructing the feature data set. Then, a double-threshold method basedon average valuesis designed to distinguish signals with known m
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Accurate Frequency Estimator of Real Sinusoid Based on Maximum Sidelobe Decay Windowsl sinusoid interact with each other in the frequency spectrum. This leads to estimation bias. In this paper, we proposed an algorithm which is based on maximum sidelobe decay (MSD) windows. Firstly, the coarse frequency estimate is obtained by using Discrete Fourier Transform (DFT) and MSD windows.
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Transfer Learning Based Algorithm for Service Deployment Under Microservice Architectureh as Broad Coverage and High Latency Communication (BCHLC) will be introduced into the network, further increasing the complexity of network management. Furthermore, the development of edge computing and microservice architectures enables services to be deployed in a container on the edge clouds clo
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Joint Opportunistic Satellite Scheduling and Beamforming for Secure Transmission in Cognitive LEO Saoth the satellite and terristrial users under limited power budgets, we propose a joint opportunistic satellite scheduling and beamforming (BF) scheme for the CLSTN. Specifically, we formulate an optimization problem to maximize the secrecy energy efficiency (SEE) of the satellite user under the sec
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