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2018 IEEE 18th International Conference on Communication Technology (ICCT)最新文献

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Resource Allocation Based on Dynamic User Priority for Indoor Visible Light Communication Ultra-Dense Networks 基于动态用户优先级的室内可见光通信超密集网络资源分配
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8599884
Xiangwei Bai, Qing Li, Siyu Tao
{"title":"Resource Allocation Based on Dynamic User Priority for Indoor Visible Light Communication Ultra-Dense Networks","authors":"Xiangwei Bai, Qing Li, Siyu Tao","doi":"10.1109/ICCT.2018.8599884","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8599884","url":null,"abstract":"Focusing on the problem of high user density in visible light communication ultra-dense networks (VLC-UDNs), this paper proposes a resource allocation method based on dynamic user priority. Firstly, this paper establishes a dynamic user priority measurement model, which realizes a multidimensional measurement for the differences among users. In the first stage, multi-dimensional features are selected dynamically with the change of network environment. In the second stage, the user priority calculation process is achieved through fuzzy logic (FL). Secondly, a throughput-maximizing resource allocation method with user priority guarantee is proposed. Simulation results show that the proposed multidimensional user priority model performs better than the conventional one-dimensional user priority model. In addition, the proposed throughput-maximizing allocation method outperforms the conventional proportion allocation method. The proposed resource allocation method based on dynamic user priority improves the system throughput against the conventional required data rate proportion allocation (RPA) method by 4%. Meanwhile, when the average blocking probability is higher than 0.45, it improves the proportion of satisfied users by up to 17.5%.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127495448","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: 5
A Method Based on Frequent Pattern Mining to Predict Spectral Availability of HF 基于频繁模式挖掘的高频频谱可用性预测方法
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8600045
Chujie Wu, Yunpeng Cheng, Yuping Gong, Guoru Ding, Ling Yu, Zhe Zhang
{"title":"A Method Based on Frequent Pattern Mining to Predict Spectral Availability of HF","authors":"Chujie Wu, Yunpeng Cheng, Yuping Gong, Guoru Ding, Ling Yu, Zhe Zhang","doi":"10.1109/ICCT.2018.8600045","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8600045","url":null,"abstract":"The HF radio communication has long been a big problem in channel selection since the spectrum environment is dynamic. To verify the feasibility of detecting idle channels by spectrum prediction, the data in this paper are based on realworld measurements collected by USRP in different time periods. The received signal power is converted to continuous sequences through a new channel state model reflecting spectrum availability. We then develop a prediction algorithm using simplified frequent pattern mining which can predict channel availability based on past channel states with considerable accuracy. The experimental results show that the measured data are more fluctuant in the afternoon which increase the predicted difficulty, nevertheless, the proposed algorithm is superior to neural network and Markov model in this situation, and the larger samples the better prediction performance.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132896014","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
Prediction of Human Body Motion from Video Sequences 基于视频序列的人体运动预测
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8600154
Zhuoheng Huang, Yue Yu, Xiangru Chen, Wei Wei
{"title":"Prediction of Human Body Motion from Video Sequences","authors":"Zhuoheng Huang, Yue Yu, Xiangru Chen, Wei Wei","doi":"10.1109/ICCT.2018.8600154","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8600154","url":null,"abstract":"Learning to predict human body motion has emerged as a meaningful research in computer vision and artificial intelligence. This paper presents the study on predicting human body motion from video sequences. We propose a human body motion prediction network integrating the recent advanced 2D feature extraction and video sequences prediction. Based on the temporal characteristics extracted from video sequences, our network realizes the prediction of the human motion. We train the network using the video based human pose datasets and demonstrate good performance of our network on 2D human body motion prediction through quantitative and qualitative results. Experimental results prove the feasibility of our method.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132208141","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
Power Amplifier Behavioral Model Dimension Pruning Using Sparse Principal Component Analysis 基于稀疏主成分分析的功放行为模型维数修剪
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8600017
Yao Yao, Songbai He, Mingyu Li, Mingdong Zhu
{"title":"Power Amplifier Behavioral Model Dimension Pruning Using Sparse Principal Component Analysis","authors":"Yao Yao, Songbai He, Mingyu Li, Mingdong Zhu","doi":"10.1109/ICCT.2018.8600017","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8600017","url":null,"abstract":"In this paper, an efficient data dimension reduction method which uses sparse principal component analysis (SPCA) is presented for reducing the dimensions of power amplifier (PA) behavioral models. Unlike other model pruning techniques, the SPCA method reduces the data dimension by projecting the variables to a new low dimensional coordinate system while minimizing the model information loss. Meanwhile, the norm L2 and L1 are used as constraint and penalty factor to acquire sparse loadings, which can overcome the non-zero loadings disadvantage of ordinary PCA method and reduce the computational complexity in extracting principal components. Experiment results show that the coefficients of the sparse model can be decreased dramatically using the SPCA method, but almost have the same model performance with the full model.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884438","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: 1
Simulation and Experiment Study on Underwater Nonlinear Photoacoustic Effect 水下非线性光声效应的仿真与实验研究
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8600047
Lihua Lei, Ju Zhou, Guixing Cao, Cong Li
{"title":"Simulation and Experiment Study on Underwater Nonlinear Photoacoustic Effect","authors":"Lihua Lei, Ju Zhou, Guixing Cao, Cong Li","doi":"10.1109/ICCT.2018.8600047","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8600047","url":null,"abstract":"Nonlinear photoacoustic effect in water mainly includes two contributions, plasma expansion and bubble blasting. The Cavitation bubble collapses process and Plasma length of breakdown in dielectric breakdown mechanism are studied by simulation as well as the characteristic analysis of photoacoustic signals from experiment results. Unique advantages of nonlinear photoacoustic source and potential application of photoacoustic signals are depicted in detail, and according to the actual application prospect, the transmission characteristics of photoacoustic signals in water is simulated and analyzed.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126669050","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
Detection Algorithm of Maneuvering Target Based on Matched Fourier Transform 基于匹配傅里叶变换的机动目标检测算法
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8600102
B. Guo, Huixian Sun, Wenhua Hu, Ning Han, Huiyan Zeng, Guanjun Chen
{"title":"Detection Algorithm of Maneuvering Target Based on Matched Fourier Transform","authors":"B. Guo, Huixian Sun, Wenhua Hu, Ning Han, Huiyan Zeng, Guanjun Chen","doi":"10.1109/ICCT.2018.8600102","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8600102","url":null,"abstract":"When the radar detects the maneuvering target, there is a high-order term in the echo phase. When the coherent integration is carried out, the phenomenon of migration through Doppler cells occurs, which affects the target detection performance. Aiming at the detection problem of maneuvering target, a detection algorithm based on Matched Fourier Transform (MFT) is proposed. By constructing a basis function that is consistent with the target echo phase, the algorithm eliminated the problem of Doppler migration and can effectively estimate the motion parameters such as speed and acceleration of the target. Simulation experiments verified the effectiveness of the proposed algorithm.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114145064","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
Survey of Cycle Slip Detection & Correction Techniques for Single Frequency Receivers 单频接收机周跳检测与校正技术综述
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8599879
S. Z. Farooq, Dongkai Yang, T. Jin, Echoda Ngbede Joshua Ada
{"title":"Survey of Cycle Slip Detection & Correction Techniques for Single Frequency Receivers","authors":"S. Z. Farooq, Dongkai Yang, T. Jin, Echoda Ngbede Joshua Ada","doi":"10.1109/ICCT.2018.8599879","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8599879","url":null,"abstract":"This paper surveys the status of cycle slip detection and correction techniques for single frequency GNSS receivers. Generally, it is more difficult to determine cycle slips in single frequency observations than dual frequency ones especially for receivers in dynamic situations. However, recently the area has begun to receive attention because of the various emerging mass-market applications of commercial single-frequency GNSS receivers. This paper presents a review of the relevent work, including techniques for both point positioning and differential positioning, that has been carried out so far. A summary is provided with regards to the applicability of the proposed schemes for dynamic single frequency receivers in real-time. It is concluded that no technique is optimum and there is scope of improvement in this particular area.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"33 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120992623","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: 3
Unsupervised Ego-Motion and Dense Depth Estimation with Monocular Video 单目视频的无监督自我运动和密集深度估计
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8600039
Yufan Xu, Yan Wang, Lei Guo
{"title":"Unsupervised Ego-Motion and Dense Depth Estimation with Monocular Video","authors":"Yufan Xu, Yan Wang, Lei Guo","doi":"10.1109/ICCT.2018.8600039","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8600039","url":null,"abstract":"In recent years, Deep Learning based method for 3-Dimension (3D) geometry perception tasks, like dense depth recovery, optical flow estimation and ego-motion estimation, is attracting significant attention. Inspired by recent advances in unsupervised strategies to learning from video datasets, we present a reasonable combination of constrains and a finer architecture, used for unsupervised ego-motion and depth estimation. Specifically, we introduce our effective neural networks Depth-Net (for monocular depth estimation) and Pose-Net (for ego-motion estimation), which are trained with monocular images. Depth-Net is proposed by us, improving the accuracy of estimation with as few parameters as possible. Finally, extensive experiments are implement on the KITTI driving dataset, proving our method outperforms some state-of-the-art results in unsupervised even supervised method.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122419867","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: 8
A Numerical Integral Algorithm Based on the CAPSO to Improve the Estimation for the Parameters of the Homodyned-K Distribution 一种基于CAPSO的改进纯差k分布参数估计的数值积分算法
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8599949
Yuqian Wang, Yufeng Zhang, Weijia Zhao, Hongxuan Zhu
{"title":"A Numerical Integral Algorithm Based on the CAPSO to Improve the Estimation for the Parameters of the Homodyned-K Distribution","authors":"Yuqian Wang, Yufeng Zhang, Weijia Zhao, Hongxuan Zhu","doi":"10.1109/ICCT.2018.8599949","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8599949","url":null,"abstract":"The homodyned-K (HK) distribution is a widely used statistical model, whose parameters have different physical-meanings for tissue characterization. In the present study, the maximum likelihood estimation (MLE) method based on the Newton-Raphson algorithm is proposed to estimate the HK parameters solely. For improving the accuracy and convergence of the MLE, the cloud adaptive particle swarm optimization (CAPSO) algorithm is proposed for the integral calculation of the probability density function (PDF) of the HK distribution. In the experiments, sets of samples satisfying the HK distribution are generated, and then the parameters are estimated by the proposed CAPSO-based MLE method. The statistics of estimation errors are calculated, and compared with the results based on the mean intensity and X- and U-statistics (XU) method, which is the latest one based on moment estimation. Experimental results show that the proposed method can solely estimate the HK parameters with a small error level, which means a further practical value in ultrasonic applications.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"1 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131464461","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
A GMM-UBM Based Multi-speaker Re-segmentation and Re-clustering Algorithm 基于GMM-UBM的多说话人再分割和再聚类算法
2018 IEEE 18th International Conference on Communication Technology (ICCT) Pub Date : 2018-10-01 DOI: 10.1109/ICCT.2018.8600111
Yahui Su, Xuanmin Lu
{"title":"A GMM-UBM Based Multi-speaker Re-segmentation and Re-clustering Algorithm","authors":"Yahui Su, Xuanmin Lu","doi":"10.1109/ICCT.2018.8600111","DOIUrl":"https://doi.org/10.1109/ICCT.2018.8600111","url":null,"abstract":"Aiming at the shortcomings of traditional speaker segmentation and clustering methods, this paper proposes a multilevel speaker re-segmentation and re-clustering algorithm based on GMM-UBM. The algorithm is based on the method of statistical modeling in the field of speaker recognition, and makes full use of the speaker information after segmenting and clustering in traditional methods to re-segment and re-cluster speech files, which improves the performance of the system effectively.","PeriodicalId":244952,"journal":{"name":"2018 IEEE 18th International Conference on Communication Technology (ICCT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131891522","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: 1
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