Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555717
Yuechao Chen, S. Du, H. Quan
The analysis and optimization for underwater target radiated noise recognition are addressed. The t-SNE (t-distributed stochastic neighbor embedding) algorithm is taken for dimension reduction of the underwater target radiated noise spectrum bands segmented by frequency and the visual results can be obtained. The average distance between classes and coincidence rate are constructed as indicators of the visualization results. By analyzing the separability of each frequency band, the optimal features can be obtained. Then the optimal features are recognized by three classification algorithms which are Random Forest, SVM (Support Vector Machine) and AdaBoost. The processing results of experimental signal spectrum with two types of target are as follows. The separability of the target signal spectrum decreases with the increase of frequency. The spectrum band of 10-150Hz has the best separability. SVM is sensitive to the increase of the data dimension with non optimal separability. Random Forests and AdaBoost can apply separability components in wider frequency bands and have greater tolerance. The overall recognition accuracy of AdaBoost is the highest, but the computation efficiency is the lowest. These analysis results shows that the t-SNE algorithm can be used to optimize the underwater target radiated noise spectrum features for the purpose of improving the accuracy and efficiency of the classification algorithm.
{"title":"Feature Analysis and Optimization of Underwater Target Radiated Noise Based on t-SNE","authors":"Yuechao Chen, S. Du, H. Quan","doi":"10.1109/WCSP.2018.8555717","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555717","url":null,"abstract":"The analysis and optimization for underwater target radiated noise recognition are addressed. The t-SNE (t-distributed stochastic neighbor embedding) algorithm is taken for dimension reduction of the underwater target radiated noise spectrum bands segmented by frequency and the visual results can be obtained. The average distance between classes and coincidence rate are constructed as indicators of the visualization results. By analyzing the separability of each frequency band, the optimal features can be obtained. Then the optimal features are recognized by three classification algorithms which are Random Forest, SVM (Support Vector Machine) and AdaBoost. The processing results of experimental signal spectrum with two types of target are as follows. The separability of the target signal spectrum decreases with the increase of frequency. The spectrum band of 10-150Hz has the best separability. SVM is sensitive to the increase of the data dimension with non optimal separability. Random Forests and AdaBoost can apply separability components in wider frequency bands and have greater tolerance. The overall recognition accuracy of AdaBoost is the highest, but the computation efficiency is the lowest. These analysis results shows that the t-SNE algorithm can be used to optimize the underwater target radiated noise spectrum features for the purpose of improving the accuracy and efficiency of the classification algorithm.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"39 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":"115150036","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555699
Chengcheng Shi, Peng Yuan, Zhihua Yang
In a satellite network, random traffic challenges the routing design due to the indeterminate data volume, time-varying topology and limited resource onboard. In this paper, therefore, an ON/OFF traffic model is demonstrated to describe the probabilistic arrival of traffic events with equal amounts of data, in a well-designed space-time graph. In particular, a space-time graph based minimum cost routing algorithm (MCRT) is proposed to find a feasible set of paths, where the contact capacity is probabilistically available for the such randomly arriving traffic data. Utilizing these paths, current traffic data could be transferred successfully to the destination during the ON period time slots, with a minimum cost in a tolerable delay requirement. Compared with a minimum cost routing algorithm for deterministic traffic, the simulation results show the excellent performance for the proposed MCRT algorithm.
{"title":"A Space-Time Graph based Minimum Cost Routing Algorithm for the Random Traffic in the Satellite Network","authors":"Chengcheng Shi, Peng Yuan, Zhihua Yang","doi":"10.1109/WCSP.2018.8555699","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555699","url":null,"abstract":"In a satellite network, random traffic challenges the routing design due to the indeterminate data volume, time-varying topology and limited resource onboard. In this paper, therefore, an ON/OFF traffic model is demonstrated to describe the probabilistic arrival of traffic events with equal amounts of data, in a well-designed space-time graph. In particular, a space-time graph based minimum cost routing algorithm (MCRT) is proposed to find a feasible set of paths, where the contact capacity is probabilistically available for the such randomly arriving traffic data. Utilizing these paths, current traffic data could be transferred successfully to the destination during the ON period time slots, with a minimum cost in a tolerable delay requirement. Compared with a minimum cost routing algorithm for deterministic traffic, the simulation results show the excellent performance for the proposed MCRT algorithm.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"13 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":"115344842","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555706
Xi Yang, Xiao Li, Shengli Zhang, Shi Jin
This paper investigates the high signal-to-noise ratio (SNR) ergodic capacity of point-to-point millimeter wave systems under finite-dimensional channel model. We first derive a closed-form expression for the high-SNR ergodic channel capacity under arbitrary antenna configurations and arbitrary number of paths when the transmitter and receiver spatial correlation matrices are non-singular. Then, novel closed-form tight upper bounds and approximations for the high-SNR ergodic capacity are obtained by means of Jensen’s inequality and order statistics. The results show that the high-SNR ergodic capacity increases logarithmically with the eigenvalues of spatial correlation matrices and the transmit SNR per antenna. Moreover, it is interesting that the upper bounds and approximations derived from the combination of Jensen’s inequality and order statistics exhibit better performance than the other with only Jensen’s inequality. Monte-Carlo simulations are performed to validate our analytical results.
{"title":"High-SNR Capacity Analysis of mmWave Systems under Finite-Dimensional Channel Model","authors":"Xi Yang, Xiao Li, Shengli Zhang, Shi Jin","doi":"10.1109/WCSP.2018.8555706","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555706","url":null,"abstract":"This paper investigates the high signal-to-noise ratio (SNR) ergodic capacity of point-to-point millimeter wave systems under finite-dimensional channel model. We first derive a closed-form expression for the high-SNR ergodic channel capacity under arbitrary antenna configurations and arbitrary number of paths when the transmitter and receiver spatial correlation matrices are non-singular. Then, novel closed-form tight upper bounds and approximations for the high-SNR ergodic capacity are obtained by means of Jensen’s inequality and order statistics. The results show that the high-SNR ergodic capacity increases logarithmically with the eigenvalues of spatial correlation matrices and the transmit SNR per antenna. Moreover, it is interesting that the upper bounds and approximations derived from the combination of Jensen’s inequality and order statistics exhibit better performance than the other with only Jensen’s inequality. Monte-Carlo simulations are performed to validate our analytical results.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"111 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":"115452138","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555917
Zhimin Li, Haifeng Zheng, Xinxin Feng
The problem of data missing is a common issue in practical traffic data collection for an Intelligent Transportation System. However, how to efficiently impute the missing entries of the traffic data is still a challenge. Previous works on missing traffic data imputation usually apply matrix or tensor completion based methods which are unable to fully exploit the spatio-temporal features of historical traffic data to achieve a satisfactory performance. In this paper, we propose a 3D convolutional generative adversarial networks to impute missing traffic data. We propose to use a fractionally strided 3D convolutional neural network to construct the generator network since it can upsample efficiently in a deep network and a 3D convolutional neural network to construct the discriminator network to fully capture spatio-temporal features of traffic data. We also present numerical results with real traffic flow dataset to show that the proposed model can significantly improve the performance in terms of recovery accuracy over the other existing tensor completion methods under various data missing patterns. We believe that the proposed approach provides a promising alternative for data imputation in ITS and other applications.
{"title":"3D Convolutional Generative Adversarial Networks for Missing Traffic Data Completion","authors":"Zhimin Li, Haifeng Zheng, Xinxin Feng","doi":"10.1109/WCSP.2018.8555917","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555917","url":null,"abstract":"The problem of data missing is a common issue in practical traffic data collection for an Intelligent Transportation System. However, how to efficiently impute the missing entries of the traffic data is still a challenge. Previous works on missing traffic data imputation usually apply matrix or tensor completion based methods which are unable to fully exploit the spatio-temporal features of historical traffic data to achieve a satisfactory performance. In this paper, we propose a 3D convolutional generative adversarial networks to impute missing traffic data. We propose to use a fractionally strided 3D convolutional neural network to construct the generator network since it can upsample efficiently in a deep network and a 3D convolutional neural network to construct the discriminator network to fully capture spatio-temporal features of traffic data. We also present numerical results with real traffic flow dataset to show that the proposed model can significantly improve the performance in terms of recovery accuracy over the other existing tensor completion methods under various data missing patterns. We believe that the proposed approach provides a promising alternative for data imputation in ITS and other applications.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"1 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":"124391850","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555886
Yue Li, Qinyu Zhang, Peng Yuan, Zhihua Yang
In these years, hybrid low earth orbit (LEO) satellites and terrestrial networks are widely developed for a variety of content distribution services, such as internet of things, satellite sensor networks and tactical distribution networks, due to low deployment cost and broader coverage capability. However, an unreasonable distribution strategy in the integrated LEO satellite and terrestrial user network will incur prolonged content access latency and significant overheads for users, due to obviously time-varying topology and limited on-board resources. In this paper, therefore, we proposed a back-tracing partition directed on-path caching mechanism for the publisher/subscriber distribution over the hybrid LEO constellation and terrestrial network. In the proposed mechanism, a back-tracing algorithm instructed node selection strategy is well-designed as well as a cross-slot graph based Dijkstra routing algorithm. Through avoiding intermittent connectivity as much as possible, the proposed mechanism could efficiently reduce the redundant transmissions of data access for different users, by fetching objective file mainly from a limited group of intermediate caching nodes, instead of directly from the source node. The simulation results verified the proposed method can obviously degrade the overall overheads and access delay of all users compared with the minimum spanning tree (MST) algorithm.
{"title":"A Back-tracing Partition based On-path Caching Distribution Strategy over integrated LEO Satellite and Terrestrial networks","authors":"Yue Li, Qinyu Zhang, Peng Yuan, Zhihua Yang","doi":"10.1109/WCSP.2018.8555886","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555886","url":null,"abstract":"In these years, hybrid low earth orbit (LEO) satellites and terrestrial networks are widely developed for a variety of content distribution services, such as internet of things, satellite sensor networks and tactical distribution networks, due to low deployment cost and broader coverage capability. However, an unreasonable distribution strategy in the integrated LEO satellite and terrestrial user network will incur prolonged content access latency and significant overheads for users, due to obviously time-varying topology and limited on-board resources. In this paper, therefore, we proposed a back-tracing partition directed on-path caching mechanism for the publisher/subscriber distribution over the hybrid LEO constellation and terrestrial network. In the proposed mechanism, a back-tracing algorithm instructed node selection strategy is well-designed as well as a cross-slot graph based Dijkstra routing algorithm. Through avoiding intermittent connectivity as much as possible, the proposed mechanism could efficiently reduce the redundant transmissions of data access for different users, by fetching objective file mainly from a limited group of intermediate caching nodes, instead of directly from the source node. The simulation results verified the proposed method can obviously degrade the overall overheads and access delay of all users compared with the minimum spanning tree (MST) algorithm.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"101 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":"116672069","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555698
Mengfan Zheng, Wen Chen, Cong Ling
In this paper, we consider the problem of polar coding for block fading channels without any instantaneous channel state information (CSI). We first decompose a block fading channel of $T_{c}$ symbols per coherent interval into $T_{c}$ binary-input sub-channels in a mutual-information-preserving way, and then design a multilevel (MLC) polar coding scheme for them. The proposed scheme achieves the ergodic mutual information of binary-input block fading channels with only channel distribution information (CDI). Simulations results are presented to compare the performance of the proposed MLC scheme and polar codes designed for i.i. d. fading channels with interleaving, which can provide some guidance for practical designs.
{"title":"Polar Coding for Noncoherent Block Fading Channels","authors":"Mengfan Zheng, Wen Chen, Cong Ling","doi":"10.1109/WCSP.2018.8555698","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555698","url":null,"abstract":"In this paper, we consider the problem of polar coding for block fading channels without any instantaneous channel state information (CSI). We first decompose a block fading channel of $T_{c}$ symbols per coherent interval into $T_{c}$ binary-input sub-channels in a mutual-information-preserving way, and then design a multilevel (MLC) polar coding scheme for them. The proposed scheme achieves the ergodic mutual information of binary-input block fading channels with only channel distribution information (CDI). Simulations results are presented to compare the performance of the proposed MLC scheme and polar codes designed for i.i. d. fading channels with interleaving, which can provide some guidance for practical designs.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"35 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":"127255031","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555647
Yiwen Nie, Junhui Zhao, Jin Liu, Rong Ran
Potential lack of witness and monitoring equipments make timely accident rescue a challenge after vehicle collision happens. It is necessary to deploy onboard sensors to achieve the real-time detection for vehicle collisions. However, how to accurately detect collisions by filtering fluctuate data from sensors near vehicle engine remains a problem. In this paper, we take the first step to conduct an experiment and gather the labeled data of 2,700 collisions. Then, a vehicle collision detecting scheme based on linear discriminant analysis (VCD-LDA) in big data enabled vehicular network is proposed. The experimental results show that VCD-LDA scheme discern 99.34% collisions with higher accuracy, compared with other classic algorithm of machine learning.
{"title":"Big Data Enabled Vehicle Collision Detection Using Linear Discriminant Analysis","authors":"Yiwen Nie, Junhui Zhao, Jin Liu, Rong Ran","doi":"10.1109/WCSP.2018.8555647","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555647","url":null,"abstract":"Potential lack of witness and monitoring equipments make timely accident rescue a challenge after vehicle collision happens. It is necessary to deploy onboard sensors to achieve the real-time detection for vehicle collisions. However, how to accurately detect collisions by filtering fluctuate data from sensors near vehicle engine remains a problem. In this paper, we take the first step to conduct an experiment and gather the labeled data of 2,700 collisions. Then, a vehicle collision detecting scheme based on linear discriminant analysis (VCD-LDA) in big data enabled vehicular network is proposed. The experimental results show that VCD-LDA scheme discern 99.34% collisions with higher accuracy, compared with other classic algorithm of machine learning.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"19 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":"127495185","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555530
Xu Qin, Tao Wang, Baoxian Zhang
Broadcasting operation is an essential operation for wireless ad hoc and sensor networks. In this paper, we study how to achieve efficient broadcasting in wireless ad hoc and sensor networks with the assistance of location information. We accordingly design an efficient location based broadcasting algorithm. In the algorithm design, we do not assume any topological information. To reduce broadcast redundancy, our algorithm jointly uses distance based deferring and angle based deferring to encourage nodes with higher contributions to retransmit first. We further extend our algorithm for supporting continuous broadcast packet transmissions. Simulation results validate the effectiveness of our designed algorithm.
{"title":"An Efficient Location based Localized Broadcasting Algorithm for Wireless Ad Hoc and Sensor Networks","authors":"Xu Qin, Tao Wang, Baoxian Zhang","doi":"10.1109/WCSP.2018.8555530","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555530","url":null,"abstract":"Broadcasting operation is an essential operation for wireless ad hoc and sensor networks. In this paper, we study how to achieve efficient broadcasting in wireless ad hoc and sensor networks with the assistance of location information. We accordingly design an efficient location based broadcasting algorithm. In the algorithm design, we do not assume any topological information. To reduce broadcast redundancy, our algorithm jointly uses distance based deferring and angle based deferring to encourage nodes with higher contributions to retransmit first. We further extend our algorithm for supporting continuous broadcast packet transmissions. Simulation results validate the effectiveness of our designed algorithm.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"14 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":"124908856","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555684
Zhenjie Qin, Aijing Li, Chao Dong, Haipeng Dai, Ai Xu
Due to availability of off-the-shelf devices and low cost, unmanned aerial vehicles (UAVs) are widely used in reconnaissance missions. In this paper, we study the fair-energy trajectory plan of multi-UAV in reconnaissance scenario with motion, hovering and communication energy consumption in consideration. Most of current works only consider the motion energy, however, the hovering and communication energy can not be ignored. We model the fair-energy problem as the minmax tour cover problem, and verify that the problem is strongly NP-hard. We propose a heuristic algorithm which includes tour calculation and tour splitting. The effectiveness of the proposed algorithm is verified by extensive numerical results, showing that the maximum energy consumption is reduced by 27% at most compared with other algorithms.
{"title":"Fair-Energy Trajectory Plan for Reconnaissance Mission Based on UAVs Cooperation","authors":"Zhenjie Qin, Aijing Li, Chao Dong, Haipeng Dai, Ai Xu","doi":"10.1109/WCSP.2018.8555684","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555684","url":null,"abstract":"Due to availability of off-the-shelf devices and low cost, unmanned aerial vehicles (UAVs) are widely used in reconnaissance missions. In this paper, we study the fair-energy trajectory plan of multi-UAV in reconnaissance scenario with motion, hovering and communication energy consumption in consideration. Most of current works only consider the motion energy, however, the hovering and communication energy can not be ignored. We model the fair-energy problem as the minmax tour cover problem, and verify that the problem is strongly NP-hard. We propose a heuristic algorithm which includes tour calculation and tour splitting. The effectiveness of the proposed algorithm is verified by extensive numerical results, showing that the maximum energy consumption is reduced by 27% at most compared with other algorithms.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"32 4 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":"126054674","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}
Pub Date : 2018-10-01DOI: 10.1109/WCSP.2018.8555723
Jie Wang, Xin Kang, Ying-Chang Liang, Sumei Sun
Internet of Things (IoT) is an emerging technology that will change our daily life. However, due to the size limitation, most of them cannot be equipped with a large battery to support the long serving time requirement. Thus, the energy harvesting (EH) technology, which can wirelessly provide energy for battery-constrained devices, has become a promising solution for IoT. In this paper, we propose an energy harvesting chain model for a wireless-powered IoT network with one information access point (AP), one radio frequency RF energy source and a set of IoT devices. The energy is transferred from the RF source to the first user, and the subsequent user harvests energy from the previous one while it transmits information to the AP. In this paper, we study two problems under the proposed energy harvesting chain model, which are total-time minimization (TTM) and sum-throughput maximization (STM). By applying convex optimization techniques, both problems can be solved in closed-form. Then, a suboptimal time allocation scheme is studied. It is shown by simulation results that the proposed chain model is useful and can be applied to specific practical application scenarios.
{"title":"An Energy Harvesting Chain Model for Wireless-Powered IoT Networks","authors":"Jie Wang, Xin Kang, Ying-Chang Liang, Sumei Sun","doi":"10.1109/WCSP.2018.8555723","DOIUrl":"https://doi.org/10.1109/WCSP.2018.8555723","url":null,"abstract":"Internet of Things (IoT) is an emerging technology that will change our daily life. However, due to the size limitation, most of them cannot be equipped with a large battery to support the long serving time requirement. Thus, the energy harvesting (EH) technology, which can wirelessly provide energy for battery-constrained devices, has become a promising solution for IoT. In this paper, we propose an energy harvesting chain model for a wireless-powered IoT network with one information access point (AP), one radio frequency RF energy source and a set of IoT devices. The energy is transferred from the RF source to the first user, and the subsequent user harvests energy from the previous one while it transmits information to the AP. In this paper, we study two problems under the proposed energy harvesting chain model, which are total-time minimization (TTM) and sum-throughput maximization (STM). By applying convex optimization techniques, both problems can be solved in closed-form. Then, a suboptimal time allocation scheme is studied. It is shown by simulation results that the proposed chain model is useful and can be applied to specific practical application scenarios.","PeriodicalId":423073,"journal":{"name":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"33 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":"125310502","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}
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