2017 IEEE/CIC International Conference on Communications in China (ICCC)最新文献_第5页

Predicting inquiry and purchase intention of users on automobile websites 预测用户对汽车网站的查询和购买意愿

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330471

Jie Gu, Fang Wei, K. Yu, Rui Cao, Yazhou Shi

{"title":"Predicting inquiry and purchase intention of users on automobile websites","authors":"Jie Gu, Fang Wei, K. Yu, Rui Cao, Yazhou Shi","doi":"10.1109/ICCChina.2017.8330471","DOIUrl":"https://doi.org/10.1109/ICCChina.2017.8330471","url":null,"abstract":"With the rapid development of Internet and Internet penetration into the automobile industry, more and more people search and browse automobile related information on the Internet before making a decision of purchase. This has formed a fertile ground to study automobile purchase intention by using user online activity data. In this paper, we focus on the task of predicting whether a user has the intention to purchase a particular make of automobile mainly based on the Deep Packet Inspection data from ISPs. We extracted 3-month user activity data from DPI data and collected automobile related information by the Web crawler on 5 leading automobile websites in China. The prediction problem was formulated as a typical classification problem in practice. And we paid a great deal of attention to the feature engineering. We proposed a feature engineering method by combining vector representation for user visiting sequence and statistical features related to users as well as automobiles. We trained various classification models with the combined features by traditional statistical methods and our method. The experimental results show that the features generated by our method perform better than the features only by statistical methods.","PeriodicalId":418396,"journal":{"name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132958783","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

Analysis and modeling of ride-sharing service user behavior in urban area 城市拼车服务用户行为分析与建模

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330473

Fan Duo, Yuanyuan Qiao, Jie Yang

{"title":"Analysis and modeling of ride-sharing service user behavior in urban area","authors":"Fan Duo, Yuanyuan Qiao, Jie Yang","doi":"10.1109/ICCChina.2017.8330473","DOIUrl":"https://doi.org/10.1109/ICCChina.2017.8330473","url":null,"abstract":"In recent years, with the advent of ride-sharing, it has brought big influence to people's daily life. It makes calling a taxi easier with the help of Internet and application in smart phones. However, what quantitative and qualitative characteristics the ride-sharing has and whether some differences exist among the ride-sharing services of each Transportation Network Company (TNC) is unknown. To address these questions, this article tries to analyze the ride-sharing services of three TNCs from three quantitative perspectives: its temporal characteristic, spatial characteristic and distribution characteristic. From the temporal characteristic, we know how the number of users and passengers on each platform change with time in a week. From the spatial characteristic, we find the locations where people often use ride-sharing and how these locations change in different periods of a day. From the distribution characteristic, we draw time interval's distribution of ride-sharing usage behavior on each TNC and calculate its relevant indicators. These results help us understand the usage and condition of ride-sharing in China and help to improve the quality of TNC services and provide useful advises to urban planning.","PeriodicalId":418396,"journal":{"name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125442546","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

Two new MODE-based algorithms for 2D DOA estimation in large scale antenna array systems 大型天线阵系统中两种新的基于模型的二维DOA估计算法

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330456

Yuxiao Jiang, Bobin Yao, Qisheng Wu

引用次数: 0

Oracle approximating shrinkage estimator based cooperative spectrum sensing for dense cognitive small cell network 基于Oracle近似收缩估计的密集认知小蜂窝网络协同频谱感知

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330356

Meng Zhao, Caili Guo, Chunyan Feng, Shuo Chen

{"title":"Oracle approximating shrinkage estimator based cooperative spectrum sensing for dense cognitive small cell network","authors":"Meng Zhao, Caili Guo, Chunyan Feng, Shuo Chen","doi":"10.1109/ICCChina.2017.8330356","DOIUrl":"https://doi.org/10.1109/ICCChina.2017.8330356","url":null,"abstract":"In this paper, we study the problem that dense cognitive small cells cooperate to sense primary signals of a macro cell. In consideration of the dense deployment of small cells, the number of small cells (sample dimension) is comparable to the number of sample (sample size), in which case sample covariance matrix is ill-conditioned estimator of high-dimensional statistical covariance matrix. The poor estimated performance of sample covariance matrix leads to degradation of sensing performance. Therefore, based on Neyman-Pearson theorem, we propose two oracle approximating shrinkage estimator based cooperative spectrum sensing (OAS-CSS) algorithms by utilizing oracle approximating shrinkage (OAS) estimator which is more accurate compared with sample covariance matrix. First method is proposed in case of ideal noise and we derive the theoretical expressions of probability of false and threshold. In the latter method, non-ideal noise is considered whose variances are imbalanced. Simulations show that our proposed OAS-CSS detectors exhibit better performance than traditional detectors and existing high-dimensional detectors. Also, theoretical sensing performance results with respect to ideal noise show an excellent agreement with simulation results when sample dimension and sample size are large.","PeriodicalId":418396,"journal":{"name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126269760","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

Blind recognition of signals in LTE-U and Wi-Fi heterogeneous cognitive network LTE-U和Wi-Fi异构认知网络中信号的盲识别

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330417

Zhong-wan Liu, Caili Guo, Shuo Chen

{"title":"Blind recognition of signals in LTE-U and Wi-Fi heterogeneous cognitive network","authors":"Zhong-wan Liu, Caili Guo, Shuo Chen","doi":"10.1109/ICCChina.2017.8330417","DOIUrl":"https://doi.org/10.1109/ICCChina.2017.8330417","url":null,"abstract":"In order to reduce the pressure of licensed spectrum and improve the cellular network capacity, Long Term Evolution (LTE) in unlicensed spectrum (LTE-U) has attracted wide attention. However, there are many challenges to the heterogeneous network which is mainly formed by LTE-U and Wireless Fidelity (Wi-Fi) in the 5GHz unlicensed band. For improving the utilization of the unlicensed band, spectrum sharing of cognitive radio (CR) is an effective solution. For CR users (CRs) which have no information about primary users (PUs), the detected signal may be LTE or Wi-Fi signal, and how to accurately recognize both will be a challenge. In this paper, a blind recognition method of signals is proposed in LTE-U and Wi-Fi heterogeneous cognitive networks, and the signal model based on third Generation Partnership Project (3GPP) LTE and 802.11 Wi-Fi is considered. Without any prior information, the proposed method is based on the signal characteristic parameters which include the Fast Fourier Transformation (FFT) size, oversampling ratio and the number of effective subcarriers and these parameters are estimated based on autocorrelation and high order spectrum (HOS) properties of the signal. The blind recognition performance of the LTE and Wi-Fi signals is simulated versus different signal-to-noise ratio(SNR). Furthermore, simulation results show that the proposed method not only has better recognition performance, but also has lower complexity than the method based on eighth order statics and neural network classifier (EOS-NN).","PeriodicalId":418396,"journal":{"name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"37 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120902504","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

Location information aided beam allocation algorithm in mmWave massive MIMO systems 毫米波大规模MIMO系统中位置信息辅助波束分配算法

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330410

Anjie Pan, Tiankui Zhang, Xiao Han

{"title":"Location information aided beam allocation algorithm in mmWave massive MIMO systems","authors":"Anjie Pan, Tiankui Zhang, Xiao Han","doi":"10.1109/ICCChina.2017.8330410","DOIUrl":"https://doi.org/10.1109/ICCChina.2017.8330410","url":null,"abstract":"Millimeter wave (mmWave) band exhibits large bandwidth availability and meets the demands for high data rate of the fifth generation cellular networks (5G). However, mmWave signals suffer from severe path loss. Beamforming technology provides high array gain to overcome this limitation. Before data connection procedure, mmWave base stations (BSs) need to search for the suitable serving beams aiming at user equipments (UEs). This searching process is typically completed in the initial access procedure and causes fatal delays. Therefore, a reasonable beam allocation algorithm (BAA) is essential to speed up initial access procedure. In this paper, a support vector machine based beam allocation algorithm (SVM-BAA) is proposed, which utilizes location information and absorbs the thought of supervised learning. It constructs a SVM multi-classifier by using location information as features and serving beams as classes. When new UEs attempt to get access to mmWave BSs, their serving beams are allocated according to the decision results of SVM multi-classifier. Simulation results show that the proposed SVM-BAA can reduce the initial access delay compared with existing methods when there's enough previous location information.","PeriodicalId":418396,"journal":{"name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121711433","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

Multi-tap analog self-interference cancellation for full-duplex communications 多抽头模拟自干扰消除全双工通信

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330406

Xudong Li, Donglin Liu, Yaxin Liu, Chuan Huang

引用次数: 1

A stream-wise blind selected mapping technique for low-PAPR multi-user MIMO transmission 一种低papr多用户MIMO传输的流式盲选映射技术

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330507

Amnart Boonkajay, F. Adachi

{"title":"A stream-wise blind selected mapping technique for low-PAPR multi-user MIMO transmission","authors":"Amnart Boonkajay, F. Adachi","doi":"10.1109/ICCChina.2017.8330507","DOIUrl":"https://doi.org/10.1109/ICCChina.2017.8330507","url":null,"abstract":"Peak-to-average power ratio (PAPR) of transmit waveform becomes higher when transmit filtering and/or pre-coding are employed. In this paper, we introduce a PAPR reduction scheme called selected mapping without side information transmission (called blind SLM) for both orthogonal frequency division multiplexing (OFDM) and single-carrier (SC) signals. Firstly, we review the proposed blind SLM techniques, considering both single-input single output (SISO) and space-time block coded transmit diversity (STBC-TD). Then, a blind SLM technique for multi-user multiple-input multiple-output (MU-MIMO) transmission with minimum mean-square error (MMSE) filtering and singular value decomposition (SVD), called MMSE-SVD, is introduced. To realize a simple data detection without side-information in MU-MIMO, we recommend that the phase rotation sequence multiplication should be applied to transmit data streams before applying the transmit filtering (called stream-wise SLM). At the receiver, the phase rotation sequence estimation is done for each users data streams after applying the receive filtering. Simulation results confirm that the stream-wise blind SLM for MMSE-SVD can reduce the PAPR of transmit waveforms without degrading bit-error rate (BER).","PeriodicalId":418396,"journal":{"name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131512412","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

Comparison of music, unitary ESPRIT, and SAGE algorithms for estimating 3D angles in wireless channels 比较音乐，统一ESPRIT，和SAGE算法估计三维角度在无线信道

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330333

Rui Feng, Yu Liu, Jie Huang, Jian Sun, Chengxiang Wang

{"title":"Comparison of music, unitary ESPRIT, and SAGE algorithms for estimating 3D angles in wireless channels","authors":"Rui Feng, Yu Liu, Jie Huang, Jian Sun, Chengxiang Wang","doi":"10.1109/ICCChina.2017.8330333","DOIUrl":"https://doi.org/10.1109/ICCChina.2017.8330333","url":null,"abstract":"Joint estimation of azimuth and elevation angles is of great importance in source localization and channel characterization. Firstly, some basic knowledge of three typical parametric estimation algorithms are introduced in this paper, i.e., multiple signal classification (MUSIC), Unitary estimation of signal parameter via rotational invariance technique (ESPRIT), and space-alternating generalized expectation-maximization (SAGE) algorithms. Each algorithm is capable of extracting both azimuth angle of arrival (AAoA) and elevation angle of arrival (EAoA) of multi-paths jointly. It is pointed out that the SAGE and MUSIC algorithms have higher complexity than the Unitary ESPRIT algorithm due to the iteration/angle searching procedure. Secondly, impacts of antenna number, closely spaced paths, and signal-to-noise ratio (SNR) on estimation performance of three algorithms are analyzed. Results show that the Unitary ESPRIT algorithm has lower accuracy in comparison with the MUSIC and SAGE algorithms when antenna number and SNR are large. Finally, three algorithms are applied to estimate multipath parameters in 16 GHz massive MIMO channel measurements. It is shown that the Unitary ESPRIT algorithm performs less satisfactory in MPCs extraction, while MUSIC can provide comparable results with the SAGE algorithm.","PeriodicalId":418396,"journal":{"name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127805663","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

SOUP: Advanced SDR platform for 5G communication SOUP:先进的5G通信SDR平台

2017 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2017-10-01 DOI: 10.1109/ICCChina.2017.8330392

Hubin Feng, Jun Wu, Xiaonian Gong

引用次数: 2