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China Communications 2021年第5期18卷 I0003-I0007页

作者： Zhi Chen Chong Han Xianbin Yu Guangjian Wang Nan Yang Mugen Peng Key Laboratory of Terahertz Technology Ministry of Education the Terahertz Wireless Communications(TWC)Laboratory University of Michigan–Shanghai Jiao Tong University(UM-SJTU)Joint InstituteShanghai Jiao Tong UniversityChina the College of Information Science and Electronic Engineering at Zhejiang University Huawei Technologies Co. Ltd.2012 lab. the School of Engineering at the Australian National University BUPT the School of Information and Communication Engineering State Key Laboratory of Networking and Switching Technology

With Wireless communications in the 0.1-10TeraHertz(THz)band are envisioned as one of the key enablers towards ubiquitous wireless communications beyond 5G accommodating a massive number of connected devices and ultra-high user data rates in the order of *** THz band is located between the millimeter-wave(mmWave)and the far infrared(IR)band and still considered as one of the least investigated and exploited regions in the electromagnetic spectrum.

关键词： millimeter spectrum. Wireless

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KEAN: Knowledge Embedded and Attention-based Network for POI Recommendation

KEAN: Knowledge Embedded and Attention-based Network for POI...

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2020 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2020

作者： Zhang, Chengwen Li, Tang Gou, Yunqing Yang, Mo Beijing Key Lab of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications Beijing China International School Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781728170046

In recent years, with the rapid development of location-based social networks (LBSN) in the Internet, point of interest (POI) recommendation has become a hot spot. Most existing researches make use of contextual information to model users' interest preferences. However, the existing methods for extracting various auxiliary information still need to be improved, such as how to treat the users' social relations equally. In order to obtain users' actual preferences more accurately, in POI recommendation, we propose a deep learning framework KEAN (Knowledge Embedded and Attention Based Network) based on knowledge graph and attention model. The framework includes knowledge-graph embedding method, preference extraction network based on attention mechanism and recommendation network. Our study used knowledge-graph embedding method to get the embedding of each user and POI. In addition, an LSTM network based on attention mechanism was proposed, which uses LSTM network to learn the user's preferences according to the user's check-in sequence. Besides, the attention mechanism was used to extract friends' preferences and merge them with the user's preferences to generate end-user preferences. Finally, our model use fully-connected neural networks to realize recommendations. The effectiveness of the model was proved by the experimental results based on real LBSN datasets. © 2020 IEEE.

关键词： Knowledge graph

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A Comparative Study for Indoor Factory Environments at 4.9 and 28 GHz

A Comparative Study for Indoor Factory Environments at 4.9 a...

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European Conference on Antennas and Propagation, EuCAP

作者： Yicheng Guan Jianhua Zhang Lei Tian Pan Tang Tao Jiang State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Mailbox NO.92 Beijing China

ISBN: (数字)9788831299008

ISBN: (纸本)9781728137124

The industrial Internet of Things (IIoT) has benefited from the fifth-generation (5G) wireless network and is providing much-needed impetus to stimulate economic growth. Because of a very wide frequency range of 5G wireless network, the microwave and millimeter wavebands will constitute hybrid wireless communication systems, thus it is essential to have a thorough knowledge of the propagation characteristics in industrial scenarios at different frequencies. In this paper, we provide a comparative study of channel characteristics, i.e., the path loss and Ricean K-factor, at 4.9 and 28 GHz in indoor factory environments based on channel measurements. The analysis results consistently indicate that rich reflection paths occur in industrial scenarios, relative to indoor office environments. Also, severer attenuation and lower multipath richness occur at 28 GHz. Meanwhile, the impact of antenna height on the propagation channel is studied. These results are helpful for the frequency band selection and antenna height design of IIoT systems.

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Analysis Of Delay Characteristics At 4.9 Ghz And 28 Ghz In An Indoor Industrial Scenario

Analysis Of Delay Characteristics At 4.9 Ghz And 28 Ghz In A...

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European Conference on Antennas and Propagation, EuCAP

作者： Zuolong Ying Tao Jiang Pan Tang Jianhua Zhang Lei Tian Key Lab of Universal Wireless Communications Ministry of Education State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9788831299008

ISBN: (纸本)9781728137124

The development of 5G promotes the interconnection of all things. And Industrial Internet of Things (IIoT) have attracted much attention because of its broad application value. In this paper, we present measurements that were conducted at 4.9 GHz and 28 GHz for comparing the channel delay spread in an indoor industrial scenario. Based on the measured data, the delay spread is compared at different frequencies. It can be found that the root mean square (RMS) delay spread (DS) is well fitted by a lognormal distribution. Besides, the mean RMS DS at 28 GHz is much smaller than that at 4.9 GHz. Compared with 3GPP standard, we find that the mean RMS DS in the indoor industrial scenario is much larger than that in the traditional indoor office scenario. At last, the effects of the TX-RX distance and antenna heights on RMS DS are investigated. By modeling DS as a function of the TX-RX distance, it is found that in the line-of-sight (LOS) scenario, RMS DS increases linearly with the TX-RX distance, both at 4.9 GHz and 28 GHz. By setting different antenna heights, it is found that in non-line-of-sight (NLOS), the mean RMS DS in the clutter-elevated scenario is 12 ns smaller than that in the clutter-embedded scenario. These results can provide insights into the design of IIoT systems.

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A Visualization System that Ensures the Localization of Private Geographic Information

A Visualization System that Ensures the Localization of Priv...

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International Conference on Universal Village (UV)

作者： Hongyan Cui Zhonghua Lv Yufan Guo Rui Zhang Lifeng Zhang State Key Lab of Networking and Switching Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Common geographic information visualization systems are based on online map tools to render geographic information. However, in an intranet environment where Internet access is not possible, online map tools cannot be used. Therefore, this paper designs a localized visualization system based on C/S architecture that can ensure private geographic information. The system can support Windows, Linux, MacOS. The system can ensure the confidentiality of private geographic information and realize the visualization of private geographic information. The test results show that the system has the localization and visualization of private geographic information, and the operation is stable and reliable.

关键词： Location awareness Visualization Linux Urban planning Layout Tools Windows

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Performance analysis and comparison of PoW,PoS and DAG based blockchains

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Digital Communications and Networks 2020年第4期6卷 480-485页

作者： Bin Cao Zhenghui Zhang Daquan Feng Shengli Zhang Lei Zhang Mugen Peng Yun Li The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China The State Key Laboratory of Integrated Services Networks(Xidian University) Xian710000China School of Communications and Information Engineering and Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and TelecommunicationsChongqing400065China The Guangdong Key Laboratory of Intelligent Information Processing College of Electronic and Information EngineeringShenzhen UniversityShenzhen518060China College of Information Engineering Shenzhen UniversityShenzhen518060China School of Engineering University of GlasgowGlasgowG128QQUK

In the blockchain,the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the *** blockchain consensus mechanisms have been ***,there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/*** this end,this work investigates three mainstream consensus mechanisms in the blockchain,namely,Proof of Work(PoW),Proof of Stake(PoS),and Direct Acyclic Graph(DAG),and identifies their performances in terms of the average time to generate a new block,the confirmation delay,the Transaction Per Second(TPS)and the confirmation failure *** results show that the consensus process is affected by both network resource(computation power/coin age,buffer size)and network load *** addition,it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.

关键词： Blockchain Proof of work Proof of stake Direct acyclic graph Performance comparison

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DQ-RM: Deep Reinforcement Learning-based Route Mutation Scheme for Multimedia Services 16

DQ-RM: Deep Reinforcement Learning-based Route Mutation Sche...

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16th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2020

作者： Zhang, Tao Xu, Changqiao Zhang, Bingchi Kuang, Xiaohui Wang, Yue Yang, Shujie Muntean, Gabriel-Miro State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of International Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Science and Technology on Information System Security Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Performance Engineering Lab. School of Electronic Engineering Dublin City University Dublin Ireland

ISBN: (纸本)9781728131290

Increasingly growing various multimedia services (e.g., interactive live video and so on) have brought tremendous pressure on existing static defense techniques. To cope with inherent drawback of static defense techniques, Network Moving Target Defense (NMTD) such as route mutation (RM) was proposed. What's more, applying reinforcement learning (RL) into RM has been proved feasible in our previous work. But two main problems still need to be considered in this combination of RL with RM: 1) It lacks the consideration of multiple flows situation. 2) With the state-action space grow larger, current solution can't handle efficiently. In this paper, we propose a deep Q-learning method for RM (DQ-RM) to solve above two problems. Firstly, benefited from the satisfiability module theory, we formalize RM space considering single flow and multiple flows concurrently. Then we further propose a deep reinforcement learning-based RM scheme based on our previous work, which is suitable for large-scale state-action space. Finally, extensive experimental results highlight the improvement of DQ-RM in defense performance and convergence speed compared to the representative solution. © 2020 IEEE.

关键词： Reinforcement learning

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TF-RNN: A Method of Rumor Detection on Social Media 5

TF-RNN: A Method of Rumor Detection on Social Media

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5th IEEE International Conference on Big Data Intelligence and Computing, DataCom 2019

作者： Xu, Peng Zhu, Yonghao Shuang, Kai Cao, Yulu Liu, Yiming Wang, Shu Beijing University of Posts and Telecommunications State Key Lab of Networking and Switching Technology Beijing China Science and Technology on Communication Networks Laboratory Shijiazhuang China

ISBN: (纸本)9781728141176

Rumor can cause great harm to individuals and society and identifying such misinformation on social media is a challenging task. Unlike previous studies which are only based on text information or propagation structures of rumors, we attempt to address the problem of indentifying rumors out of microblogs by combining both of them and user-based features. Thus we propose Triple-feature Recursive Neural Networks (TF-RNN). To begin with, we model the dissemination of microblogs as tree-structured RNN. We then adopt Wide and Deep model to extract features, including the content-based and user-based features, of each node in the propagation tree as input to the tree-structured RNN. The classification result on datasets of Sina Weibo and Twitter demonstrates that the model is 2% to 3% more accurate than the baseline model respectively. © 2019 IEEE.

关键词： Tweets

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Ray-tracing Based Channel Clustering and Analysis at 28 GHz in Conference Environment

Ray-tracing Based Channel Clustering and Analysis at 28 GHz ...

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European Conference on Antennas and Propagation, EuCAP

作者： He Ding Lei Tian Pan Tang Li Yu Wanpeng Zhang Tao Jiang Jianhua Zhang State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing P. O. Box 92 China

ISBN: (数字)9788831299008

ISBN: (纸本)9781728137124

The millimeter-wave (mm-wave) band is of great importance for the future wireless communication systems. Studies on millimeter-wave channels are of great importance to mmwave wireless technologies. In this paper, we investigate the 3-D clustering phenomenon of mm-wave propagation at 28 GHz in a conference room. The results including cluster propagation mechanisms, the relationship between the clusters and the physical environment, and intra-cluster statistics are presented. Results show that the cluster propagation mechanisms are influenced by the room geometry. The last hop of sub-paths in the same cluster may locate on different objects existing in the environment. Besides, cluster statistics including intra-cluster delay spread (DS), angle spread (AS), and sub-paths number are discussed. Their logarithms fit normal distributions well. These results could help extend and justify current research on mm-wave channels. Moreover, a ray-tracing (RT) tool is used to emulate the measurements and similarity results are presented and analyzed. Excellent agreements between the measurement and simulation verify the feasibility and accuracy of RT simulation for studying the cluster characteristics.

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Secure and Efficient Federated Learning Through Layering and Sharding Blockchain

arXiv

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arXiv 2021年

作者： Yuan, Shuo Cao, Bin Sun, Yao Wan, Zhiguo Peng, Mugen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom Zhejiang Lab Zhejiang Hangzhou311121 China

Introducing blockchain into Federated Learning (FL) to build a trusted edge computing environment for transmission and learning has attracted widespread attention as a new decentralized learning pattern. However, traditional consensus mechanisms and architectures of blockchain systems face significant challenges in handling large-scale FL tasks, especially on Internet of Things (IoT) devices, due to their substantial resource consumption, limited transaction throughput, and complex communication requirements. To address these challenges, this paper proposes ChainFL, a novel two-layer blockchain-driven FL system. It splits the IoT network into multiple shards within the subchain layer, effectively reducing the scale of information exchange, and employs a Direct Acyclic Graph (DAG)-based mainchain as the mainchain layer, enabling parallel and asynchronous cross-shard validation. Furthermore, the FL procedure is customized to integrate deeply with blockchain technology, and a modified DAG consensus mechanism is designed to mitigate distortion caused by abnormal models. To provide a proof-of-concept implementation and evaluation, multiple subchains based on Hyperledger Fabric and a self-developed DAG-based mainchain are deployed. Extensive experiments demonstrate that ChainFL significantly surpasses conventional FL systems, showing up to a 14% improvement in training efficiency and a threefold increase in robustness. Copyright © 2021, The Authors. All rights reserved.

关键词： Blockchain

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