Home / Journals / CMC / Vol.60, No.2, 2019
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  • Open AccessOpen Access

    ARTICLE

    Design and Performance Comparison of Rotated Y-Shaped Antenna Using Different Metamaterial Surfaces for 5G Mobile Devices

    Jalal Khan1, Daniyal Ali Sehrai1, Mushtaq Ahmad Khan1, Haseeb Ahmad Khan2, Salman Ahmad3, Arslan Ali4, Arslan Arif5, Anwer Ahmad Memon6, Sahib Khan1,4,*
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 409-420, 2019, DOI:10.32604/cmc.2019.06883
    Abstract In this paper, a rotated Y-shaped antenna is designed and compared in terms of performance using a conventional and EBG ground planes for future Fifth Generation (5G) cellular communication system. The rotated Y-shaped antenna is designed to transmit at 38 GHz which is one of the most prominent candidate bands for future 5G communication systems. In the design of conventional antenna and metamaterial surfaces (mushroom, slotted), Rogers-5880 substrate having relative permittivity, thickness and loss tangent of 2.2, 0.254 mm, and 0.0009 respectively have been used. The conventional rotated Y-shaped antenna offers a satisfactory wider bandwidth (0.87 GHz) at 38.06 GHz… More >

  • Open AccessOpen Access

    ARTICLE

    A Comparative Study of Machine Learning Methods for Genre Identification of Classical Arabic Text

    Maha Al-Yahya1, *
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 421-433, 2019, DOI:10.32604/cmc.2019.06209
    Abstract The purpose of this study is to evaluate the performance of five supervised machine learning methods for the task of automated genre identification of classical Arabic texts using text most frequent words as features. We design an experiment for comparing five machine-learning methods for the genre identification task for classical Arabic text. We set the data and the stylometric features and vary the classification method to evaluate the performance of each method. Of the five machine learning methods tested, we can conclude that Support Vector Machine (SVM) are generally the most effective. The contribution of this work lies in the… More >

  • Open AccessOpen Access

    ARTICLE

    Improved Enhanced Dbtma with Contention-Aware Admission Control to Improve the Network Performance in Manets

    M. Sivaram1,*, D. Yuvaraj2, Amin Salih Mohammed3, V. Manikandan4, V. Porkodi4, N. Yuvaraj5
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 435-454, 2019, DOI:10.32604/cmc.2019.06295
    Abstract DBTMA relies entirely on RTS/CTS dialogue for un-collided transmission of data. The purpose is to improve the QoS at MAC layer by developing it over 802.11e standard. However, DBTMA does not guarantee real-time constraints without efficient method for controlling the network loads. The main challenges in MANETs include prediction of the available bandwidth, establishing communication with neighboring nodes and predicting the consumption of bandwidth flow. These challenges are provided with solutions using Contention-Aware Admission Control (CACP) protocol. In this paper, the EDBTMA protocol is combined with CACP protocol that introduces bandwidth calculation using admission control strategy. The calculation includes certain… More >

  • Open AccessOpen Access

    ARTICLE

    Analysis of Bus Ride Comfort Using Smartphone Sensor Data

    Hoong-Chor Chin1, Xingting Pang1, Zhaoxia Wang2,3,*
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 455-463, 2019, DOI:10.32604/cmc.2019.05664
    Abstract Passenger comfort is an important indicator that is often used to measure the quality of public transport services. It may also be a crucial factor in the passenger’s choice of transport mode. The typical method of assessing passenger comfort is through a passenger interview survey which can be tedious. This study aims to investigate the relationship between bus ride comfort based on ride smoothness and the vehicle’s motion detected by the smartphone sensors. An experiment was carried out on a bus fixed route within the University campus where comfort levels were rated on a 3-point scale and recorded at 5-second… More >

  • Open AccessOpen Access

    ARTICLE

    Heterogeneous Memristive Models Design and Its Application in Information Security

    Shaojiang Zhong1, *
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 465-479, 2019, DOI:10.32604/cmc.2019.05853
    Abstract Based on the three-dimensional classic Chua circuit, a nonlinear circuit containing two flux-control memristors is designed. Due to the difference in the design of the characteristic equation of the two magnetron memristors, their position form a symmetrical structure with respect to the capacitor. The existence of chaotic properties is proved by analyzing the stability of the system, including Lyapunov exponent, equilibrium point, eigenvalue, Poincare map, power spectrum, bifurcation diagram et al. Theoretical analysis and numerical calculation show that this heterogeneous memristive model is a hyperchaotic five-dimensional nonlinear dynamical system and has a strong chaotic behavior. Then, the memristive system is… More >

  • Open AccessOpen Access

    ARTICLE

    Drug Side-Effect Prediction Using Heterogeneous Features and Bipartite Local Models

    Yi Zheng1,2, Wentao Zhao2,*, Chengcheng Sun2, Qian Li1
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 481-496, 2019, DOI:10.32604/cmc.2019.05536
    Abstract Drug side-effects impose massive costs on society, leading to almost one-third drug failure in the drug discovery process. Therefore, early identification of potential side-effects becomes vital to avoid risks and reduce costs. Existing computational methods employ few drug features and predict drug side-effects from either drug side or side-effect side separately. In this work, we explore to predict drug side-effects by combining heterogeneous drug features and employing the bipartite local models (BLMs) which fuse predictions from both the drug side and side-effect side. Specifically, we integrate drug chemical structures, drug interacted proteins and drug associated genes into a unified framework… More >

  • Open AccessOpen Access

    RETRACTION

    RETRACTED: Automatic Arrhythmia Detection Based on Convolutional Neural Networks

    Zhong Liu1,2, Xinan Wang1,*, Kuntao Lu1, David Su3
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 497-509, 2019, DOI:10.32604/cmc.2019.04882
    Abstract ECG signal is of great importance in the clinical diagnosis of various heart diseases. The abnormal origin or conduction of excitation is the electrophysiological mechanism leading to arrhythmia, but the type and frequency of arrhythmia is an important indicator reflecting the stability of cardiac electrical activity. In clinical practice, arrhythmic signals can be classified according to the origin of excitation, the frequency of excitation, or the transmission of excitation. Traditional heart disease diagnosis depends on doctors, and it is influenced by doctors' professional skills and the department's specialty. ECG signal has the characteristics of weak signal, low frequency, large variation,… More >

  • Open AccessOpen Access

    ARTICLE

    Rigid Medical Image Registration Using Learning-Based Interest Points and Features

    Maoyang Zou1,2, Jinrong Hu2, Huan Zhang2, Xi Wu2, Jia He2, Zhijie Xu3, Yong Zhong1,*
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 511-525, 2019, DOI:10.32604/cmc.2019.05912
    Abstract For image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy and interventional radiology, one of the important techniques is medical image registration. In our study, we propose a learning-based approach named “FIP-CNNF” for rigid registration of medical image. Firstly, the pixel-level interest points are computed by the full convolution network (FCN) with self-supervise. Secondly, feature detection, descriptor and matching are trained by convolution neural network (CNN). Thirdly, random sample consensus (Ransac) is used to filter outliers, and the transformation parameters are found with the most inliers by iteratively fitting transforms. In addition, we propose “TrFIP-CNNF” which uses transfer learning and fine-tuning… More >

  • Open AccessOpen Access

    ARTICLE

    Directional Antenna Intelligent Coverage Method Based on Traversal Optimization Algorithm

    Jialuan He1,2, Zirui Xing2, Rong Hu2, Jing Qiu3,*, Shen Su3,*, Yuhan Chai3, Yue Wu4
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 527-544, 2019, DOI:10.32604/cmc.2019.05586
    Abstract Wireless broadband communication is widely used in maneuver command communications systems in many fields, such as military operations, counter-terrorism and disaster relief. How to reasonably formulate the directional antenna coverage strategy according to the mobile terminal dynamic distribution and guide the directional antenna dynamic coverage becomes a practical research topic. In many applications, a temporary wireless boardband base station is required to support wireless signal communications between many terminals from nearby vehicles and staffs. It is therefore important to efficiently set directional antenna while ensuring large enough coverage over dynamically distributed terminals. The wireless broadband base station mostly uses two… More >

  • Open AccessOpen Access

    ARTICLE

    Binaural Sound Source Localization Based on Convolutional Neural Network

    Lin Zhou1,*, Kangyu Ma1, Lijie Wang1, Ying Chen1,2, Yibin Tang3
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 545-557, 2019, DOI:10.32604/cmc.2019.05969
    Abstract Binaural sound source localization (BSSL) in low signal-to-noise ratio (SNR) and high reverberation environment is still a challenging task. In this paper, a novel BSSL algorithm is proposed by introducing convolutional neural network (CNN). The proposed algorithm first extracts the spatial feature of each sub-band from binaural sound signal, and then combines the features of all sub-bands within one frame to assemble a two-dimensional feature matrix as a grey image. To fully exploit the advantage of the CNN in extracting high-level features from the grey image, the spatial feature matrix of each frame is used as input to train the… More >

  • Open AccessOpen Access

    ARTICLE

    An Application-Oriented Buffer Management Strategy in Opportunistic Networks

    Meihua Liu1, Xinchen Zhang2,*, Shuangkui Ge3, Xiaoli Chen1, Jianbin Wu2, Mao Tian1
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 559-574, 2019, DOI:10.32604/cmc.2019.04843
    Abstract In Opportunistic networks (ONs), buffer management is critical to improve the message exchanging efficiency due to the limited storage space and transmission bandwidth at the wireless edge. Current solutions make message scheduling and drop policy based on assumptions that messages can always been forwarded in a single contact, and all node pairs have the same contact rates. However, such ideal assumptions are invalid for realistic mobility traces of hand-held. Recent studies show that the single contact duration is limited and the mobility of nodes is heterogeneous in reality. In this paper, a buffer management strategy based on contact duration and… More >

  • Open AccessOpen Access

    ARTICLE

    A Review on Deep Learning Approaches to Image Classification and Object Segmentation

    Hao Wu1, Qi Liu2, 3, *, Xiaodong Liu4
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 575-597, 2019, DOI:10.32604/cmc.2019.03595
    Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed discussion of several typical networks… More >

  • Open AccessOpen Access

    ARTICLE

    Satellite Cloud-Derived Wind Inversion Algorithm Using GPU

    Lili He1,2, Hongtao Bai1,2, Dantong Ouyang1,2, Changshuai Wang1,2, Chong Wang1,2,3, Yu Jiang1,2,*
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 599-613, 2019, DOI:10.32604/cmc.2019.05928
    Abstract Cloud-derived wind refers to the wind field data product reversely derived through satellite remote sensing cloud images. Satellite cloud-derived wind inversion has the characteristics of large scale, computationally intensive and long time. The most widely used cloud-derived serial--tracer cloud tracking method is the maximum cross-correlation coefficient (MCC) method. In order to overcome the efficiency bottleneck of the cloud-derived serial MCC algorithm, we proposed a parallel cloud-derived wind inversion algorithm based on GPU framework in this paper, according to the characteristics of independence between each wind vector calculation. In this algorithm, each iteration is considered as a thread of GPU cores,… More >

  • Open AccessOpen Access

    ARTICLE

    An Improved Integration for Trimmed Geometries in Isogeometric Analysis

    Jinlan Xu1, Ningning Sun1, Laixin Shu1, Timon Rabczuk2, Gang Xu1,*
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 615-632, 2019, DOI:10.32604/cmc.2019.04464
    Abstract Trimming techniques are efficient ways to generate complex geometries in Computer-Aided Design (CAD). In this paper, an improved integration for trimmed geometries in isogeometric analysis (IGA) is proposed. The proposed method can improve the accuracy of the approximation and the condition number of the stiffness matrix. In addition, comparing to the traditional approaches, the trimming techniques can reduce the number of the integration elements with much fewer integration points, which improves the computational efficiency significantly. Several examples are illustrated to show the effectiveness of the proposed approach. More >

  • Open AccessOpen Access

    ARTICLE

    Locating Steganalysis of LSB Matching Based on Spatial and Wavelet Filter Fusion

    Chunfang Yang1,*, Jie Wang1, Chengliang Lin1, Huiqin Chen2, Wenjuan Wang1
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 633-644, 2019, DOI:10.32604/cmc.2019.06154
    Abstract For the case of that only a single stego image of LSB (Least Significant Bit) matching steganography is available, the existing steganalysis algorithms cannot effectively locate the modified pixels. Therefore, an algorithm is proposed to locate the modified pixels of LSB matching based on spatial and wavelet filter fusion. Firstly, the validity of using the residuals obtained by spatial and wavelet filtering to locate the modified pixels of LSB matching is analyzed. It is pointed out that both of these two kinds of residuals can be used to identify the modified pixels of LSB matching with success rate higher than… More >

  • Open AccessOpen Access

    ARTICLE

    Key Process Protection of High Dimensional Process Data in Complex Production

    He Shi1,2,3,4, Wenli Shang1,2,3,4,*, Chunyu Chen1,2,3,4, Jianming Zhao1,2,3,4, Long Yin1, 2, 3, 4
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 645-658, 2019, DOI:10.32604/cmc.2019.05648
    Abstract In order to solve the problem of locating and protecting key processes and detecting outliers efficiently in complex industrial processes. An anomaly detection system which is based on the two-layer model fusion frame is designed in this paper. The key process is located by using the random forest model firstly, then the process data feature selection, dimension reduction and noise reduction are processed. Finally, the validity of the model is verified by simulation experiments. It is shown that this method can effectively reduce the prediction accuracy variance and improve the generalization ability of the traditional anomaly detection model from the… More >

  • Open AccessOpen Access

    ARTICLE

    Collaborative Filtering Recommendation Algorithm Based on Multi-Relationship Social Network

    Sheng Bin1,*, Gengxin Sun1, Ning Cao2, Jinming Qiu2, Zhiyong Zheng3, Guohua Yang4, Hongyan Zhao5, Meng Jiang6, Lina Xu7
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 659-674, 2019, DOI:10.32604/cmc.2019.05858
    Abstract Recommendation system is one of the most common applications in the field of big data. The traditional collaborative filtering recommendation algorithm is directly based on user-item rating matrix. However, when there are huge amounts of user and commodities data, the efficiency of the algorithm will be significantly reduced. Aiming at the problem, a collaborative filtering recommendation algorithm based on multi-relational social networks is proposed. The algorithm divides the multi-relational social networks based on the multi-subnet complex network model into communities by using information dissemination method, which divides the users with similar degree into a community. Then the user-item rating matrix… More >

  • Open AccessOpen Access

    ARTICLE

    Enabling Comparable Search Over Encrypted Data for IoT with Privacy-Preserving

    Lei Xu1, Chungen Xu1,*, Zhongyi Liu1, Yunling Wang2,3, Jianfeng Wang2,3
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 675-690, 2019, DOI:10.32604/cmc.2019.05276
    Abstract With the rapid development of cloud computing and Internet of Things (IoT) technology, massive data raises and shuttles on the network every day. To ensure the confidentiality and utilization of these data, industries and companies users encrypt their data and store them in an outsourced party. However, simple adoption of encryption scheme makes the original lose its flexibility and utilization. To address these problems, the searchable encryption scheme is proposed. Different from traditional encrypted data search scheme, this paper focuses on providing a solution to search the data from one or more IoT device by comparing their underlying numerical values.… More >

  • Open AccessOpen Access

    ARTICLE

    MSICST: Multiple-Scenario Industrial Control System Testbed for Security Research

    Wei Xu1,2, Yaodong Tao2,3, Chunfang Yang4,*, Huiqin Chen5
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 691-705, 2019, DOI:10.32604/cmc.2019.05678
    Abstract A security testbed is an important aspect of Industrial Control System (ICS) security research. However, existing testbeds still have many problems in that they cannot fully simulate enterprise networks and ICS attacks. This paper presents a Multiple-Scenario Industrial Control System Testbed (MSICST), a hardware-in-the-loop ICS testbed for security research. The testbed contains four typical process scenarios: thermal power plant, rail transit, smart grid, and intelligent manufacturing. We use a combination of actual physical equipment and software simulations to build the process scenario sand table and use real hardware and software to build the control systems, demilitarized zone, and enterprise zone… More >

  • Open AccessOpen Access

    ARTICLE

    Tibetan Sentiment Classification Method Based on Semi-Supervised Recursive Autoencoders

    Xiaodong Yan1,2, Wei Song1,2,*, Xiaobing Zhao1,2, Anti Wang3
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 707-719, 2019, DOI:10.32604/cmc.2019.05157
    Abstract We apply the semi-supervised recursive autoencoders (RAE) model for the sentiment classification task of Tibetan short text, and we obtain a better classification effect. The input of the semi-supervised RAE model is the word vector. We crawled a large amount of Tibetan text from the Internet, got Tibetan word vectors by using Word2vec, and verified its validity through simple experiments. The values of parameter α and word vector dimension are important to the model effect. The experiment results indicate that when α is 0.3 and the word vector dimension is 60, the model works best. Our experiment also shows the… More >

  • Open AccessOpen Access

    ARTICLE

    MalDetect: A Structure of Encrypted Malware Traffic Detection

    Jiyuan Liu1, Yingzhi Zeng2, Jiangyong Shi2, Yuexiang Yang2,∗, Rui Wang3, Liangzhong He4
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 721-739, 2019, DOI:10.32604/cmc.2019.05610
    Abstract Recently, TLS protocol has been widely used to secure the application data carried in network traffic. It becomes more difficult for attackers to decipher messages through capturing the traffic generated from communications of hosts. On the other hand, malwares adopt TLS protocol when accessing to internet, which makes most malware traffic detection methods, such as DPI (Deep Packet Inspection), ineffective. Some literatures use statistical method with extracting the observable data fields exposed in TLS connections to train machine learning classifiers so as to infer whether a traffic flow is malware or not. However, most of them adopt the features based… More >

  • Open AccessOpen Access

    ARTICLE

    Robust Re-Weighted Multi-View Feature Selection

    Yiming Xue1, Nan Wang2, Yan Niu1, Ping Zhong2, ∗, Shaozhang Niu3, Yuntao Song4
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 741-756, 2019, DOI:10.32604/cmc.2019.05611
    Abstract In practical application, many objects are described by multi-view features because multiple views can provide a more informative representation than the single view. When dealing with the multi-view data, the high dimensionality is often an obstacle as it can bring the expensive time consumption and an increased chance of over-fitting. So how to identify the relevant views and features is an important issue. The matrix-based multi-view feature selection that can integrate multiple views to select relevant feature subset has aroused widely concern in recent years. The existing supervised multi-view feature selection methods usually concatenate all views into the long vectors… More >

  • Open AccessOpen Access

    ARTICLE

    Ab Initio Molecular-Dynamics Simulation Liquid and Amorphous Al94-xNi6Lax (x=3-9) Alloys

    Lu Wang1,2, Cuihhong Yang2, Tong Liu3, Hongyan Wu2,*
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 757-765, 2019, DOI:10.32604/cmc.2019.04499
    Abstract Ab initio molecular-dynamics simulations have been used to investigate the liquid and amorphous Al94-xNi6Lax (x=3-9) alloys. Through calculating the pair distribution functions and partial coordination numbers, the structure and properties of these alloys are researched, which will help the design bulk metallic glass. The concentration of La atoms can affect the short-range order of Al94-xNi6Lax alloys, which is also studied in this calculation result. More >

  • Open AccessOpen Access

    ARTICLE

    Fuzzy C-Means Algorithm Automatically Determining Optimal Number of Clusters

    Ruikang Xing1,*, Chenghai Li1
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 767-780, 2019, DOI:10.32604/cmc.2019.04500
    Abstract In clustering analysis, the key to deciding clustering quality is to determine the optimal number of clusters. At present, most clustering algorithms need to give the number of clusters in advance for clustering analysis of the samples. How to gain the correct optimal number of clusters has been an important topic of clustering validation study. By studying and analyzing the FCM algorithm in this study, an accurate and efficient algorithm used to confirm the optimal number of clusters is proposed for the defects of traditional FCM algorithm. For time and clustering accuracy problems of FCM algorithm and relevant algorithms automatically… More >

  • Open AccessOpen Access

    ARTICLE

    A Novel Scene Text Recognition Method Based on Deep Learning

    Maosen Wang1, Shaozhang Niu1,*, Zhenguang Gao2
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 781-794, 2019, DOI:10.32604/cmc.2019.05595
    Abstract Scene text recognition is one of the most important techniques in pattern recognition and machine intelligence due to its numerous practical applications. Scene text recognition is also a sequence model task. Recurrent neural network (RNN) is commonly regarded as the default starting point for sequential models. Due to the non-parallel prediction and the gradient disappearance problem, the performance of the RNN is difficult to improve substantially. In this paper, a new TRDD network architecture which base on dilated convolution and residual block is proposed, using Convolutional Neural Networks (CNN) instead of RNN realizes the recognition task of sequence texts. Our… More >

  • Open AccessOpen Access

    ARTICLE

    Multi-Rate Polling: Improve the Performance of Energy Harvesting Backscatter Wireless Networks

    Yu Han1,*, Wenxian Zheng2, Guangjun Wen1, Chu Chu1, Jian Su3, Yibo Zhang4
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 795-812, 2019, DOI:10.32604/cmc.2019.05719
    Abstract In recent years, Researchers have proposed the concept of Energy Harvesting Backscatter Wireless Networks (EHBWN). EHBWN usually consists of one sink and several backscatter nodes. Backscatter nodes harvest energy from their environment and communicate with sink through backscattering the carrier wave transmitted by sink. Although a certain amount of access protocols for Energy Harvesting Wireless Networks have been present, they usually do not take the sink’s receiver sensitivity into account, which makes those protocols unsuitable in practice. In this paper, we first give an analysis of the backscatter channel link budget and the relationship between the effective communication range and… More >

  • Open AccessOpen Access

    ARTICLE

    A Multi-Objective Decision-Making Approach for the Optimal Location of Electric Vehicle Charging Facilities

    Weiwei Liu1, Yang Tang2, Fei Yang2, Yi Dou3, Jin Wang4,*
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 813-834, 2019, DOI:10.32604/cmc.2019.06754
    Abstract Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the… More >

  • Open AccessOpen Access

    ARTICLE

    A Capacity Improving Scheme in Multi-RSUs Deployed V2I

    Yueyun Chen1,*, Zhuo Zeng1, Taohua Chen1, Zushen Liu2, Alan Yang3
    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 835-853, 2019, DOI:10.32604/cmc.2019.07080
    Abstract The communication reliability and system capacity are two of the key performance indicators for Internet of Vehicles (IoV). Existing studies have proposed a variety of technologies to improve reliability and other performance, such as channel selection and power allocation in Vehicle-to-Infrastructure (V2I). However, these researches are mostly applied in a single roadside unit (RSU) scenario without considering inter-cell interference (ICI) of multi-RSUs. In this paper, considering the distribution characteristics of multi-RSUs deployment and corresponding ICI, we propose a reliable uplink transmission scheme to maximize the total capacity and decrease the interference of multi-RSUs (mRSU-DI) in condition of the uplink interruption… More >

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