2019 28th Wireless and Optical Communications Conference (WOCC)最新文献

Low Complexity Signal Detection Based on WL Decomposition for MIMO Systems 基于WL分解的MIMO系统低复杂度信号检测

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770538

Jing Lian, Zhenyu Zhang, Xiyuan Wang, Xiaofei Liu, Xiaoming Dai

引用次数: 0

Performance Evaluation of LTE-R System with Mobile Relay for Differentiated Services 面向差异化业务的移动中继LTE-R系统性能评价

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770564

Jingjing Yan, Dapeng Li, Youyun Xu, Jianping Chen

引用次数: 1

Research Framework for the Future Development of IoT Information Service Technology 物联网信息服务技术未来发展研究框架

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770591

Zhanzhong Tang, Xianwu Zeng, Zhiliang Wang

{"title":"Research Framework for the Future Development of IoT Information Service Technology","authors":"Zhanzhong Tang, Xianwu Zeng, Zhiliang Wang","doi":"10.1109/WOCC.2019.8770591","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770591","url":null,"abstract":"The Internet of Things information service system is a natural evolution of existing information systems. The source of information is multi-source. The storage and processing of information in a cloud environment may be distributed in entities in different regions, or may be concentrated in an information service center. The functional services provided by the information service system can be centralized or distributed. This study proposes a research framework for IoT information services, and gives a general description of the system structure and information services. The structure of the entire IoT system consists of three parts: information service interface, information service interface engine and information flow engine. The Internet of Things information service has the following development trends: (1) The environment of big data processing has expanded to the entire Internet of Things; (2) The development of services that meet the requirements of clear users to meet the needs of fuzzy users; (3) The calculation of cloud computing The organization further deepens and expands; (4) The post-evaluation of service quality develops to advance prediction; (5) The intelligentialize and automation of decision-making. This research framework can be used as a reference for future research on IoT information services.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129535590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resource Allocation for Threat Defense in Cyber-security IoT system 网络安全物联网系统中威胁防御的资源分配

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770615

Manxi Wang, Bingjie Liu, Haitao Xu

引用次数: 2

Error Analysis of Single-Satellite Interference Source Positioning Based on Different Number of Co-Frequency Beams 基于不同同频波束数的单星干扰源定位误差分析

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770599

Fan Zhao, Laiding Zhao, Gengxin Zhang, Jidong Xie

引用次数: 1

Rogue Base Station Detection Using A Machine Learning Approach 利用机器学习方法检测流氓基站

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770554

Jian Jin, ChangLiang Lian, Ming Xu

引用次数: 8

A Constellation Design and Optimization for Simultaneously Transmitting Information and Synchronization Sequence * 一种同时传输信息和同步序列的星座设计与优化*

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770549

Rugui Yao, Qihong Wu, Xiaoya Zuo, Y. Zhang, Hailong Liu

引用次数: 1

Hybrid Precoding Based on MMSE-EDS for Multi-user Multi-stream Massive MIMO Systems 基于MMSE-EDS的多用户多流大规模MIMO系统混合预编码

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770543

Zhan Liu, Yueyun Chen, Meijie Yang, Rongling Jian

引用次数: 4

Asymmetrical Emission Beams based Visible Light Communication Access Points Design 基于非对称发射光束的可见光通信接入点设计

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770572

Jupeng Ding, I. Chih-Lin, Xifeng Chen, Huicheng Lai

引用次数: 7

Active Learning with Spatial Distribution based Semi-Supervised Extreme Learning Machine for Multiclass Classification 基于空间分布主动学习的半监督极限学习机多类分类

2019 28th Wireless and Optical Communications Conference (WOCC) Pub Date : 2019-05-09 DOI: 10.1109/WOCC.2019.8770569

Yuefan Xu, Li Ma, Wendong Xiao

{"title":"Active Learning with Spatial Distribution based Semi-Supervised Extreme Learning Machine for Multiclass Classification","authors":"Yuefan Xu, Li Ma, Wendong Xiao","doi":"10.1109/WOCC.2019.8770569","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770569","url":null,"abstract":"Unlabeled samples are often readily available in our daily lives. However, valuable information contained in a large number of unlabeled samples tends to be ignored by general supervised learning models. To make full use of unlabeled samples, we propose a novel framework that combines active learning with semi-supervised learning. On one hand, we expect to label as few samples as possible while achieving guaranteed classification performance, hence it's of vital importance to design a specific active learning strategy to select only the most valuable batch of samples for expert labeling. On the other hand, the introduction of distribution information in unlabeled sample pool will bring great benefits to the model. Both labeled samples and unlabeled samples can be used for training semi-supervised classification model. In this paper, uncertainty-based active learning and manifold-based semi-supervised learning are integrated into our framework. Extreme learning machine (ELM) is adopted as our base classifier. Moreover, a novel uncertainty criterion, called Bell-Function-based uncertainty, is proposed for active learning selection for the first time. Empirical results on six public benchmark datasets show that our algorithm produces better performance in comparison with other approaches.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129789462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0