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第二届材料科学应用与能源材料国际研讨会

作者： Feiyue Wang Hui Zhi Ziju Huang Key Lab of Computing Intelligent and Signal Processing(Ministry of Education) Anhui University

In order to improve the uplink channel estimation performance and reduce pilot contamination(PC),this paper proposes a pilot allocation method of jointing cell grouping and alliance game(JCG-AG) for massive multiple-input multiple-output(MIMO) cellular *** can be divided into two ***,by properly dividing all cells into different cell-groups,the users in different cell-groups are allocated different orthogonal pilot ***,the users in the same cell-group are further divided into several mutually disjoint *** belonging to different sub-alliances are allocated different pilots,and users belonging to the same sub-alliance reuse the same *** the second step,the alliance formation algorithm is used to suppress *** JCG-AG method takes practical application as the starting point,focuses on the random distribution of users,and uses the idea of alliance *** these make it more flexible and *** demonstrated in the simulation results,the JCG-AG method can greatly mitigate the PC and reduce the average mean square error(MSE) for all channel estimations in the uplink.

关键词： MSE red A Pilot Allocation Method of Jointing Cell Grouping and Alliance Game in Massive MIMO System

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Design of reconfigurable monopole antenna with switchable dual band-notches for UWB applications

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Progress In Electromagnetics Research C 2019年 96卷 97-107页

作者： Li, Ji Sun, Yufa Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China

A reconfigurable antenna with on-demand single-band or dual-band rejection capability for ultra-wideband (UWB) applications is presented. A modified monopole structure is integrated with a U-shaped slot and an open-ended slot to realize band-rejection. The antenna operates in four modes: A full UWB (3.1–10.6 GHz) coverage antenna, a UWB antenna with a single-band WiMax or wide local area network (WLAN) rejection, and a UWB antenna with dual-band WiMax/WLAN rejection. On-demand single and dual-band rejections are implemented by controlling two slots using two PIN diodes. Thus, the adopted control technique is quite easy and requires low operating power. Details of the design process and reconfiguration mechanism are presented. The band-rejection performance is explained by return loss and surface current distribution at single-band mode. A prototype is built on a Rogers substrate and tested to validate the performances. The antenna exhibits stable radiation characteristics and almost flat gain responses across the whole band, while significantly gain reduction is achieved at the rejected bands. Therefore, this antenna is suitable for high-performance UWB systems in WiMax/WLAN dense environments with the aim to improve signal quality, system capacity, and communication efficiency. © 2019, Electromagnetics Academy. All rights reserved.

关键词： Monopole antennas

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The Downlink Performance of Massive MIMO Systems under Different Uplink Pilot Allocation Schemes

The Downlink Performance of Massive MIMO Systems under Diffe...

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第二届材料科学应用与能源材料国际研讨会

作者： Ziju Huang Hui Zhi Feiyue Wang Key Lab of Computing Intelligent and Signal Processing(Ministry of Education) Anhui University

In the scenario of time division duplexing(TDD) massive multiple-input multiple-output(MIMO) system,when there is pilot contamination(PC) in the uplink,different pilot allocation schemes will affect the results of the uplink channel *** the channel estimation results are used for downlink transmission precoding,which will further affects the downlink *** paper analyses the impact of different pilot allocation(PA) schemes on downlink *** theoretical analysis,the system downlink signal to interference plus noise ratio(SINR) and spectral efficiency expressions of different pilot allocation schemes are obtained *** simulation results show that the pilot allocation schemes with cell grouping is better than the schemes without cell *** SINR increases as the number of cell grouping increases,and the spectrum efficiency increases first and then decreases as the number of cell grouping increases.

关键词： TDD The Downlink Performance of Massive MIMO Systems under Different Uplink Pilot Allocation Schemes

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A New Vision-Aided Beam Prediction Scheme for mmWave Wireless Communications

A New Vision-Aided Beam Prediction Scheme for mmWave Wireles...

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International Conference on Computer and Communications (ICCC)

作者： Ziqiang Ying Haojun Yang Jia Gao Kan Zheng Ministry of Education Intelligent Computing and Communications (IC2) Lab Wireless Signal Processing and Networks (WSPN) Lab Key Laboratory of Universal Wireless Communications Beijing University of Posts and Telecommunications (BUPT) Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

Beamforming is one of the most critical technologies for millimeter wave (mmWave) wireless communications. However, the classical beam selection methods generally require the large system overhead, such as frequent channel estimation. To this end, this paper proposes a new vision-aided beam prediction scheme based on object detection for mmWave wireless communications. In this scheme, the optimal beams are directly predicted based on the RGB images captured by cameras. Specifically, we first adopt the object detection model to locate the positions of all targeted users in the RGB images. Then, based on multilayer perceptron, an angle prediction model is used to estimate the angles between the users and the cameras. In addition, we select the optimal beam indexes from a pre-defined beam codebook according to the information of angle and codebook. Finally, the experimental results reveal that our proposed scheme has the lower overhead, higher accuracy and better scalability.

关键词： Wireless communication Scalability Object detection Predictive models Cameras Indexes Task analysis

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A Second-order C-bandpass Frequency Selective Surface

A Second-order C-bandpass Frequency Selective Surface

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Shenbing Wu Mingsheng Chen Meng Kong Liang Zhang Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University School of Electronic Engineering Huainan Normal University AnHui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University

ISBN: (数字)9781728157337

ISBN: (纸本)9781728157344

A novel C-bandpass frequency selective surface(FSS) exhibiting miniaturized periodic parts is developed in this study. Such FSS acts as a bandpass filter at 4.03--7.87GHz. The proposed FSS exhibits miniaturization characteristics with the unit-cell dimension 0.12λ*0.12λ and the total thickness less than λ/28. Meantime, the simulation results reveal that the second-order FSS exhibits better stability under a variety of incident directions and polarization modes.

关键词： Frequency selective surfaces Microwave technology Surface waves Simulation Millimeter wave technology Stability analysis Periodic structures

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Embedding dynamic attributed networks by modeling the evolution processes

arXiv

引用

arXiv 2020年

作者： Xu, Zenan Ou, Zijing Su, Qinliang Yu, Jianxing Quan, Xiaojun Lin, Zhenkun School of Data and Computer Science Sun Yat-sen University China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Key Lab. of Machine Intelligence and Advanced Computing Ministry of Education China

Network embedding has recently emerged as a promising technique to embed nodes of a network into low-dimensional vectors. While fairly successful, most existing works focus on the embedding techniques for static networks. But in practice, there are many networks that are evolving over time and hence are dynamic, e.g., the social networks. To address this issue, a high-order spatio-temporal embedding model is developed to track the evolutions of dynamic networks. Specifically, an activeness-aware neighborhood embedding method is first proposed to extract the high-order neighborhood information at each given timestamp. Then, an embedding prediction framework is further developed to capture the temporal correlations, in which the attention mechanism is employed instead of recurrent neural networks (RNNs) for its efficiency in computing and flexibility in modeling. Extensive experiments are conducted on four real-world datasets from three different areas. It is shown that the proposed method outperforms all the baselines by a substantial margin for the tasks of dynamic link prediction and node classification, which demonstrates the effectiveness of the proposed methods on tracking the evolutions of dynamic networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Recurrent neural networks

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GoSum: Extractive Summarization of Long Documents by Reinforcement Learning and Graph Organized discourse state

arXiv

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arXiv 2022年

作者： Bian, Junyi Huang, Xiaodi Zhou, Hong Zhu, Shanfeng School of Computer Science Fudan University Shanghai200433 China School of Computing and Mathematics Charles Sturt University AlburyNSW2640 Australia Atypon Systems LLC United Kingdom Institute of Science and Technology for Brain-Inspired Intelligence Fudan University China Ministry of Education Shanghai200433 China MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Shanghai200433 China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai200433 China

Extracting summaries from long documents can be regarded as sentence classification using the structural information of the documents. How to use such structural information to summarize a document is challenging. In this paper, we propose GoSum, a novel graph and reinforcement learning based extractive model for long-paper summarization. In particular, GoSum encodes sentence states in reinforcement learning by building a heterogeneous graph for each input document at different discourse levels. An edge in the graph reflects the discourse hierarchy of a document for restraining the semantic drifts across section boundaries. We evaluate GoSum on two datasets of scientific articles summarization: PubMed and arXiv. The experimental results have demonstrated that GoSum achieve state-of-the-art results compared with strong baselines of both extractive and abstractive models. The ablation studies further validate that the performance of our GoSum benefits from the use of discourse information. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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3R: Word and Phoneme Edition based Data Augmentation for Lexical Punctuation Prediction

3R: Word and Phoneme Edition based Data Augmentation for Lex...

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International Conference on Computational intelligence and Security

作者： Aihua Zheng Naipeng Ye Xiao Wang Xiao Song Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Hefei China Peking University Shenzhen Institute Shenzhen China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei China

Existing Lexical Punctuation Prediction methods are mainly trained on the standard clean data while losing the generalization in practical automatic speech recognition (ASR) system with ubiquitous transcription errors. To bridge the gap between clean training data and noisy testing data, we propose three random (3R) data augmentation strategies: random word deletion (RWD), random word substitution (RWS), and random phoneme edition (RPE) in both word and phoneme levels on the training dataset. Specifically, we contribute an acoustically similar vocabulary with phoneme level editions for acoustically similar word substitution. In addition, we first introduce the RoBERTa-large model into a punctuation prediction task to capture the semantics and the long-distance dependencies in language. Extensive experiments on the English dataset IWSLT2011 yield to a new state-of-the-art comparing to the prevalent punctuation prediction methods.

关键词： Training Vocabulary Semantics Training data Predictive models Noise measurement Security

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Let's play music: Audio-driven performance video generation

arXiv

引用

arXiv 2020年

作者： Zhu, Hao Li, Yi Zhu, Feixia Zheng, Aihua He, Ran Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China CASIA Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology CAS Beijing China

We propose a new task named Audio-driven Performance Video Generation (APVG), which aims to synthesize the video of a person playing a certain instrument guided by a given music audio clip. It is a challenging task to generate the high-dimensional temporal consistent videos from low-dimensional audio modality. In this paper, we propose a multistaged framework to achieve this new task to generate realistic and synchronized performance video from given music. Firstly, we provide both global appearance and local spatial information by generating the coarse videos and keypoints of body and hands from a given music respectively. Then, we propose to transform the generated keypoints to heatmap via a differentiable space transformer, since the heatmap offers more spatial information but is harder to generate directly from audio. Finally, we propose a Structured Temporal UNet (STU) to extract both intra-frame structured information and inter-frame temporal consistency. They are obtained via graph-based structure module, and CNN-GRU based high-level temporal module respectively for final video generation. Comprehensive experiments validate the effectiveness of our proposed framework. Copyright © 2020, The Authors. All rights reserved.

关键词： Music

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Hybrid graph-based radiology report generation

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Expert Systems with Applications 2025年 289卷

作者： Dengdi Sun Chaofan Mu Xuyang Fan Jin Tang Zegeng Li Jie Zhu Zhuanlian Ding Key Laboratory of Intelligent Computing & Signal Processing (ICSP) Ministry of Education School of Artificial Intelligence Anhui University Hefei 230601 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei 230601 China First Affiliated Hospital of Anhui University of Chinese Medicine Hefei 230031 China College of Integrated Chinese and Western Medicine Anhui University of Chinese Medicine Hefei 230012 China School of Internet Anhui University Hefei 230039 China

Automatic report generation plays a crucial role in clinical practice by alleviating the heavy workload on doctors and helping to prevent misdiagnoses or missed diagnoses. In the context of radiology report generation, knowledge injection is essential, particularly with the encoder-decoder framework commonly used in image captioning tasks. However, existing studies predominantly rely on expert knowledge, which is both challenging to collect and lacks universality. Additionally, this expert knowledge typically influences single-mode information and overlooks the importance of bridging the visual-to-textual gap. To address these challenges, we propose a hybrid graph-based approach for radiology report generation. Our method integrates two key components: the semantic homogeneous graph (SHG) and the cross-modal heterogeneous graph (CHG). Specifically, the SHG is constructed by mining semantic relationships between keywords across the entire corpus to generate universal knowledge. The CHG, conversely, is built from visual features, textual features, and corresponding knowledge embeddings, enabling knowledge injection during modal interaction. By leveraging graph convolutional networks to enhance graph embeddings, our model improves the quality of generated reports. Experimental results on two widely used benchmark datasets, IU-Xray and MIMIC-CXR, demonstrate the effectiveness of our approach. Notably, our method achieves a BLEU-4 score of 0.185 on the IU-Xray dataset and an F1 score of 0.418 on the MIMIC-CXR dataset, significantly outperforming existing methods.

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