2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)最新文献_第8页

Performance analysis of cooperative quickest interference detection for GNSS GNSS协同最快干扰检测性能分析

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974595

Jaehoon Lee, Junhyuk Kim, Hyowon Kim, Chansik Park, M. Lee, Sunwoo Kim

引用次数: 0

Research of public opinion hotspot detection model based on Web big data 基于Web大数据的舆情热点检测模型研究

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974538

C. Fan, Yuexin Wu, Jun Zhang, Tianlin Zhao

引用次数: 7

Understanding online shopping and offline mobility behavior in urban area from the view of multilayer networks 从多层网络的角度理解城市线上购物和线下移动行为

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974608

Yuanyuan Qiao, Yanting Zhang, Anders Lindgren, Jie Yang

引用次数: 1

A self-organizing resource allocation strategy based on Q-learning approach in ultra-dense networks 超密集网络中基于q -学习的自组织资源分配策略

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974555

Ming Chen, Y. Hua, Xinyu Gu, Shiwen Nie, Zhiqiang Fan

{"title":"A self-organizing resource allocation strategy based on Q-learning approach in ultra-dense networks","authors":"Ming Chen, Y. Hua, Xinyu Gu, Shiwen Nie, Zhiqiang Fan","doi":"10.1109/ICNIDC.2016.7974555","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974555","url":null,"abstract":"In ultra-dense heterogeneous cellular networks, with the density of low power base stations (BSs) increasing, the inter-cell interference (ICI) can be extremely strong when all BSs reuse the same time-frequency resources. In this paper, after proving that allocating orthogonal (frequency) sub-bands to adjacent cells can perform better on throughput than reusing the whole bandwidth, we propose a multi-agent Q-learning based resources allocation (QLRA) approach as an enhanced solution to maximize the system performance. For the QLRA, we operate two learning paradigms: the distributed Q-learning (DQL) algorithm and the centralized Q-learning (CQL) algorithm. In the DQL scenario, all small cells learn independently without sharing any information. While in the CQL scenario, interaction between different agents is taken into consideration and resources are scheduled in a centralized way. Simulation results show that both QLRA scenarios can study an ideal resource allocation strategy automatically and achieve better performance on system throughput. Moreover, by scheduling resources in a centralized way, the CQL scenario can improve the system throughput furtherly.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121066105","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: 7

Unequal block for low bandwidth adaption in wireless video broadcast 无线视频广播中低带宽适应的不等块

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974602

Zhexin Li, Yu Liu, Yumei Wang

{"title":"Unequal block for low bandwidth adaption in wireless video broadcast","authors":"Zhexin Li, Yu Liu, Yumei Wang","doi":"10.1109/ICNIDC.2016.7974602","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974602","url":null,"abstract":"With the development of information technology, people's demand for wireless video is improved. Recently, an uncoded video transmission scheme called SoftCast was proposed for wireless video communication which provided graceful transition quality. However, when channel bandwidth is low, we need to discard some packets before transmitting to meet the requirement of bandwidth. This will cause a sharp decline on receiver video quality. This paper proposed an unequal block method (UBCAST) based on the frequency of image. UBCAST divides the lowest frequency into the biggest block to protect low frequency information, and divides the highest frequency into the smallest block which can protect low frequency packets from being discarded. What's more we can increase high frequency block proportion to improve transmission quality. And we can also increase low frequency block proportion to increase discarding packets proportion to meet the bandwidth requirement of channel. The experimental results show that when transmitting video information completely, we can improve the performance of the original SoftCast using 8∗8 block up to 2dB. When the SNR of channel is 20dB, discarding packets, we can even get a 10dB gain.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131990835","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: 2

Compressed sensing for frequency hopping communication signals via analog to information converter 基于模拟信息转换器的跳频通信信号压缩感知

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974591

Lei Chen, Hui Peng, Mengyue Liu, Yu Liu

引用次数: 2

A fast and scalable supervised topic model using stochastic variational inference and MapReduce 基于随机变分推理和MapReduce的快速可扩展监督主题模型

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974542

Wenzhuo Song, Bo Yang, Xuehua Zhao, Fei Li

{"title":"A fast and scalable supervised topic model using stochastic variational inference and MapReduce","authors":"Wenzhuo Song, Bo Yang, Xuehua Zhao, Fei Li","doi":"10.1109/ICNIDC.2016.7974542","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974542","url":null,"abstract":"An important and widespread topic in cloud computing is text analyzing. People often use topic model which is a popular and effective technology to deal with related tasks. Among all the topic models, sLDA is acknowledged as a popular supervised topic model, which adds a response variable or category label with each document, so that the model can uncover the latent structure of a text dataset as well as retains the predictive power for supervised tasks. However, sLDA needs to process all the documents at each iteration in the training period. When the size of dataset increases to the volume that one node cannot deal with, sLDA will no longer be competitive. In this paper we propose a novel model named Mr.sLDA which extends sLDA with stochastic variational inference (SVI) and MapReduce. SVI can reduce the computational burden of sLDA and MapReduce extends the algorithm with parallelization. Mr.sLDA makes the training become more efficient and the training method can be easily implemented in a large computer cluster or cloud computing. Empirical results show that our approach has an efficient training process, and similar accuracy with sLDA.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133737464","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: 2

Topology discovery algorithm for ethernet networks with incomplete information based on VLAN 基于VLAN的不完全信息以太网拓扑发现算法

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974604

Jie Zhou, Yan Ma

引用次数: 5

Secure transmission based on cooperative jamming relay in heterogeneous massive MIMO system 异构海量MIMO系统中基于协同干扰中继的安全传输

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974578

Chang Li, Xinran Zhang, Wei Lin, Songlin Sun

引用次数: 1

An experimental study: The sufficient respiration rate detection technique via continuous wave Doppler radar 实验研究:连续波多普勒雷达充分呼吸频率检测技术

2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) Pub Date : 2016-09-01 DOI: 10.1109/ICNIDC.2016.7974619

Ku-young Chung, Bong-Ki Lee, Kwangsub Song, Kangsoo Shin, Seok-Hyun Cho, Joon‐Hyuk Chang

引用次数: 1