Pub Date : 2019-05-01DOI: 10.1109/WOCC.2019.8770605
Peitong Yang, Lixin Li, Wei Liang, Huisheng Zhang, Z. Ding
Both non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) have been recognized as important techniques in future wireless networks, and the combination of them has received attention recently. It has been demonstrated that in a dual-user scenario, the use of the NOMA can effectively reduce the latency and energy consumption of MEC offloading. However, the scenario of multiple users needs to be considered further, which is more practical. In this paper, we consider a NOMA-MEC system with multiple users and single MEC server, and investigate the problem of minimizing offloading latency. Through using the Reinforcement learning (RL) algorithm Deep Q-network (DQN) to select the users who offload at the same time without knowing the actions of other users in advance, we will obtain the optimal user combination state and minimize system offloading latency. Simulation results show that the proposed method can significantly reduce the system offloading latency in the multi-user scenario of applying NOMA to MEC.
{"title":"Latency Optimization for Multi-user NOMA-MEC Offloading Using Reinforcement Learning","authors":"Peitong Yang, Lixin Li, Wei Liang, Huisheng Zhang, Z. Ding","doi":"10.1109/WOCC.2019.8770605","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770605","url":null,"abstract":"Both non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) have been recognized as important techniques in future wireless networks, and the combination of them has received attention recently. It has been demonstrated that in a dual-user scenario, the use of the NOMA can effectively reduce the latency and energy consumption of MEC offloading. However, the scenario of multiple users needs to be considered further, which is more practical. In this paper, we consider a NOMA-MEC system with multiple users and single MEC server, and investigate the problem of minimizing offloading latency. Through using the Reinforcement learning (RL) algorithm Deep Q-network (DQN) to select the users who offload at the same time without knowing the actions of other users in advance, we will obtain the optimal user combination state and minimize system offloading latency. Simulation results show that the proposed method can significantly reduce the system offloading latency in the multi-user scenario of applying NOMA to MEC.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121307558","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770618
M. Jha, Navin Kumar, Y. Lakshmi
In this paper, we analyzed the generalized spatial modulation (generalized SM) transmission technique for multi user indoor visible light communication (VLC) system. In generalized SM, number of bits conveyed per transmitter includes modulation symbol bits and active transmitter indices bits. Block diagonalization (BD) precoding technique is used to avoid multi user interference (MUI) in the transmitter without interference between photodiodes of the same user resulting in the noise reduction. A comparison is performed between the generalized SM with conventional Multiple Input Multiple Output (MIMO), spatial multiplexing (SMP) MIMO and spatial modulation MIMO transmission technique for multi user VLC system with regard to bit error rate (BER) performance using simulation. Simulation results show that generalized SM MIMO technique offers better signal to noise ratio (SNR) than SM MIMO by 2 dB, SMP MIMO by 5 dB and conventional MIMO technique by 8.5 dB to achieve the same BER of 10−6. We also analyzed the influence of field of view (FOV) at an optical receiver on SNR performance with respect to single light emitting diode (LED) power.
{"title":"Generalized Spatial Modulation for Multi-User in Visible Light Communication","authors":"M. Jha, Navin Kumar, Y. Lakshmi","doi":"10.1109/WOCC.2019.8770618","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770618","url":null,"abstract":"In this paper, we analyzed the generalized spatial modulation (generalized SM) transmission technique for multi user indoor visible light communication (VLC) system. In generalized SM, number of bits conveyed per transmitter includes modulation symbol bits and active transmitter indices bits. Block diagonalization (BD) precoding technique is used to avoid multi user interference (MUI) in the transmitter without interference between photodiodes of the same user resulting in the noise reduction. A comparison is performed between the generalized SM with conventional Multiple Input Multiple Output (MIMO), spatial multiplexing (SMP) MIMO and spatial modulation MIMO transmission technique for multi user VLC system with regard to bit error rate (BER) performance using simulation. Simulation results show that generalized SM MIMO technique offers better signal to noise ratio (SNR) than SM MIMO by 2 dB, SMP MIMO by 5 dB and conventional MIMO technique by 8.5 dB to achieve the same BER of 10−6. We also analyzed the influence of field of view (FOV) at an optical receiver on SNR performance with respect to single light emitting diode (LED) power.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115785274","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770656
Shihong Duan, Yuanyuan Li, Cheng Xu, Jiawang Wan, Jie He
Position is one of the essential attributes of an object. With the development of wireless communication and ranging technology, localization algorithms should also been investigated to improve its accuracy. Ultra Wideband (UWB) has the potentials of low cost and high precision. However, its accuracy is susceptible to environment, such as non-line-of-sight conditions. There is a pressing need for a suitable algorithm to reduce the impact of ranging errors, and ensure the performance of the positioning systems when the ranging error varies.
{"title":"TOA based Target Tracking using Optimal Estimation Methods","authors":"Shihong Duan, Yuanyuan Li, Cheng Xu, Jiawang Wan, Jie He","doi":"10.1109/WOCC.2019.8770656","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770656","url":null,"abstract":"Position is one of the essential attributes of an object. With the development of wireless communication and ranging technology, localization algorithms should also been investigated to improve its accuracy. Ultra Wideband (UWB) has the potentials of low cost and high precision. However, its accuracy is susceptible to environment, such as non-line-of-sight conditions. There is a pressing need for a suitable algorithm to reduce the impact of ranging errors, and ensure the performance of the positioning systems when the ranging error varies.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128387136","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770669
Shuang Tang, Chensheng Li, Xiaowei Qin, Guo Wei
Traditional traffic classification methods generally sort the Internet traffic for video streaming to the same category. However, video streaming should be treated differently according to different streaming techniques for the task of QoE evaluation. Meanwhile, end-to-end encryption and different encrypted forms make traffic classification even more challenging because of insufficient distinguishable characteristics. In this work, we propose a novel Dynamic Warping Network (DWN) model that allows us to differentiate different streaming techniques based on traffic patterns. We compute soft Dynamic Time Warping (DTW) distances between the download speed series and a set of warping series, which are further fed to Multi-Layer Perceptions (MLP) for traffic classification. We also show how to train the MLP and warping series jointly using back-propagation algorithm. The proposed model outperforms the start-of-the-art MaMPF model for distinguishing Internet traffic between different streaming techniques, where the accuracy for Video on Demand (VoD) using HTTP Adaptive Streaming (HAS) and live broadcasting (LB) reaches 90.51% and 88.84% respectively.
{"title":"Traffic Classification for Mobile Video Streaming Using Dynamic Warping Network","authors":"Shuang Tang, Chensheng Li, Xiaowei Qin, Guo Wei","doi":"10.1109/WOCC.2019.8770669","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770669","url":null,"abstract":"Traditional traffic classification methods generally sort the Internet traffic for video streaming to the same category. However, video streaming should be treated differently according to different streaming techniques for the task of QoE evaluation. Meanwhile, end-to-end encryption and different encrypted forms make traffic classification even more challenging because of insufficient distinguishable characteristics. In this work, we propose a novel Dynamic Warping Network (DWN) model that allows us to differentiate different streaming techniques based on traffic patterns. We compute soft Dynamic Time Warping (DTW) distances between the download speed series and a set of warping series, which are further fed to Multi-Layer Perceptions (MLP) for traffic classification. We also show how to train the MLP and warping series jointly using back-propagation algorithm. The proposed model outperforms the start-of-the-art MaMPF model for distinguishing Internet traffic between different streaming techniques, where the accuracy for Video on Demand (VoD) using HTTP Adaptive Streaming (HAS) and live broadcasting (LB) reaches 90.51% and 88.84% respectively.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114560472","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770682
Shu Gui, Runhe Qiu
This Cooperative relay technology has been widely studied, but the energy efficiency (EE) of relay transmission system is not always higher than that of direct transmission system. In this paper, the EEs of the direct transmission (DT) mode, the One - way relay transmission (OWRT) mode and the two-way relay transmission (TWRT) mode in different channel fading conditions are studied, and the expressions of EE are obtained. Comparing to the EEs of the three transmission modes under different channel fading, the system adaptively selects the transmission mode with higher EE according to the actual data transmission rate. Simulation results show that, compared to the traditional transmission mode, the proposed energy-efficient relay adaptive transmission strategy greatly improves the EE of the relay transmission system.
{"title":"High energy efficient relay adaptive transmission strategy","authors":"Shu Gui, Runhe Qiu","doi":"10.1109/WOCC.2019.8770682","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770682","url":null,"abstract":"This Cooperative relay technology has been widely studied, but the energy efficiency (EE) of relay transmission system is not always higher than that of direct transmission system. In this paper, the EEs of the direct transmission (DT) mode, the One - way relay transmission (OWRT) mode and the two-way relay transmission (TWRT) mode in different channel fading conditions are studied, and the expressions of EE are obtained. Comparing to the EEs of the three transmission modes under different channel fading, the system adaptively selects the transmission mode with higher EE according to the actual data transmission rate. Simulation results show that, compared to the traditional transmission mode, the proposed energy-efficient relay adaptive transmission strategy greatly improves the EE of the relay transmission system.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124390689","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770621
Na Li, Dongmei Zhang, Wei Xie, Meng Wang, Kui Xu, Jianhui Xu, Qingsong Zhang
In this paper, we consider the beam-domain time-switching (TS) simultaneous wireless information and power transfer (SWIPT) protocol design in half-duplex (HD) massive multiple-input multiple-output (MIMO) system, where the sensors are uniformly distributed in its coverage area. In order to reduce the computational complexity, we propose spatial basis expansion model (SBEM) with rotation angle to improve the performance of SWIPT technology. In the proposed scheme, the transmit time interval is decomposed to three subintervals, the duration of each subinterval is optimized to maximize the system spectrum efficiency.
{"title":"Simultaneously Power and Information Transmission for Half-duplex Massive MIMO with Spatial Basis Expansion Model","authors":"Na Li, Dongmei Zhang, Wei Xie, Meng Wang, Kui Xu, Jianhui Xu, Qingsong Zhang","doi":"10.1109/WOCC.2019.8770621","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770621","url":null,"abstract":"In this paper, we consider the beam-domain time-switching (TS) simultaneous wireless information and power transfer (SWIPT) protocol design in half-duplex (HD) massive multiple-input multiple-output (MIMO) system, where the sensors are uniformly distributed in its coverage area. In order to reduce the computational complexity, we propose spatial basis expansion model (SBEM) with rotation angle to improve the performance of SWIPT technology. In the proposed scheme, the transmit time interval is decomposed to three subintervals, the duration of each subinterval is optimized to maximize the system spectrum efficiency.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132161827","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770631
I. A. Khoso, T. Javed, Shanshan Tu, Yuanyuan Dong, Hua Li, Xiyuan Wang, Xiaoming Dai
Minimum mean squared error (MMSE) detector achieves near-optimal error rate performance for massive multiple-input multiple-output (M-MIMO) systems but involves large-scale matrix inversion operations with high complexity. Therefore, several approximated matrix inversion algorithms have been proposed. However, their convergence turns out to be very slow. In this paper, a new approach based on joint Jacobi and Richardson method is proposed. We show that the proposed method accelerate the convergence rate at low-complexity for different base station (BS)-to-user-antenna ratio (BUAR). Moreover, a promising initial estimate is utilized to achieve closer-to-optimal initialization for the proposed method. To further accelerate the convergence rate, we introduce a new approximated-eigenvalue based relaxation parameter. The convergence proof of the proposed algorithm is also provided in this work. We analyze the computational complexity of different methods and demonstrate the performance differences with numerical simulations.
{"title":"A Fast-Convergent Detector Based on Joint Jacobi and Richardson Method for Uplink Massive MIMO Systems","authors":"I. A. Khoso, T. Javed, Shanshan Tu, Yuanyuan Dong, Hua Li, Xiyuan Wang, Xiaoming Dai","doi":"10.1109/WOCC.2019.8770631","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770631","url":null,"abstract":"Minimum mean squared error (MMSE) detector achieves near-optimal error rate performance for massive multiple-input multiple-output (M-MIMO) systems but involves large-scale matrix inversion operations with high complexity. Therefore, several approximated matrix inversion algorithms have been proposed. However, their convergence turns out to be very slow. In this paper, a new approach based on joint Jacobi and Richardson method is proposed. We show that the proposed method accelerate the convergence rate at low-complexity for different base station (BS)-to-user-antenna ratio (BUAR). Moreover, a promising initial estimate is utilized to achieve closer-to-optimal initialization for the proposed method. To further accelerate the convergence rate, we introduce a new approximated-eigenvalue based relaxation parameter. The convergence proof of the proposed algorithm is also provided in this work. We analyze the computational complexity of different methods and demonstrate the performance differences with numerical simulations.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133745152","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770611
Xiaojuan Xie, Yanqin Ni, Shengliang Peng, Yu-dong Yao
Automatic modulation classification (AMC) is a crucial task for various communications applications. Deep learning (DL) based classifier is emerging as a prevalent choice for AMC. Previous research on DL based AMC usually assumes an environment of fixed signal to noise ratio (SNR). This paper considers DL based AMC for varying SNR environment. Two algorithms, including M2M4-aided algorithm and multi-label DL based algorithm, are proposed to combat the varying SNR. The former utilizes an M2M4 estimator to estimate SNR, according to which a proper trained DL model can be selected for AMC. The latter exploits multi-label DL to train a model, with which SNR scenario and modulation type can be inferred simultaneously. Experiment results show that the performance of both algorithms is fairly close to that of DL based AMC under fixed SNR environment.
{"title":"Deep Learning based Automatic Modulation Classification for Varying SNR Environment","authors":"Xiaojuan Xie, Yanqin Ni, Shengliang Peng, Yu-dong Yao","doi":"10.1109/WOCC.2019.8770611","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770611","url":null,"abstract":"Automatic modulation classification (AMC) is a crucial task for various communications applications. Deep learning (DL) based classifier is emerging as a prevalent choice for AMC. Previous research on DL based AMC usually assumes an environment of fixed signal to noise ratio (SNR). This paper considers DL based AMC for varying SNR environment. Two algorithms, including M2M4-aided algorithm and multi-label DL based algorithm, are proposed to combat the varying SNR. The former utilizes an M2M4 estimator to estimate SNR, according to which a proper trained DL model can be selected for AMC. The latter exploits multi-label DL to train a model, with which SNR scenario and modulation type can be inferred simultaneously. Experiment results show that the performance of both algorithms is fairly close to that of DL based AMC under fixed SNR environment.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116172576","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770661
Nan Wu, S. Haruyama
Sound detection with optical means is an appealing research topic. Laser speckle is one effective method to detect the sound due to its sensitivity to tiny motion. The traditional laser-speckle sound recovery methods require a high-speed camera to record fast-moving speckle images and then recover the original sound signals from the motion information of the captured speckle images. In this manuscript, a laser microphone system is proposed to detect and regenerate the sound signal in real time. In the proposed system, only a small part of the imaging sensor is used to ensure a high sampling rate with a common industrial camera and reduce the computation time consumption. Meanwhile, optical flow algorithm is employed to obtain the motion information of captured speckle images and regenerate the sound. These two points allow us to capture images from the camera and regenerate sound in real time without storing any data into the computer, which greatly increases the speed of the system and achieves a microphone-like functions. Experiments are conducted to show that the proposed system can detect and regenerate the sound signal in real-time with a high quality.
{"title":"Real-time Sound Detection and Regeneration Based on Optical Flow Algorithm of Laser Speckle Images","authors":"Nan Wu, S. Haruyama","doi":"10.1109/WOCC.2019.8770661","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770661","url":null,"abstract":"Sound detection with optical means is an appealing research topic. Laser speckle is one effective method to detect the sound due to its sensitivity to tiny motion. The traditional laser-speckle sound recovery methods require a high-speed camera to record fast-moving speckle images and then recover the original sound signals from the motion information of the captured speckle images. In this manuscript, a laser microphone system is proposed to detect and regenerate the sound signal in real time. In the proposed system, only a small part of the imaging sensor is used to ensure a high sampling rate with a common industrial camera and reduce the computation time consumption. Meanwhile, optical flow algorithm is employed to obtain the motion information of captured speckle images and regenerate the sound. These two points allow us to capture images from the camera and regenerate sound in real time without storing any data into the computer, which greatly increases the speed of the system and achieves a microphone-like functions. Experiments are conducted to show that the proposed system can detect and regenerate the sound signal in real-time with a high quality.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116485325","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 : 2019-05-01DOI: 10.1109/WOCC.2019.8770663
Jian Ming, Aibing Jin, Jinhai Sun, D. Hu, Yan Xia
Based on the theory and technology of Internet of Things(IOT) and digital mine, the Mine Internet of Things (perception Mine) is used to detect and control of the personnel, equipment and mine environment, which can improve the ability of perceiving the operation status of the personnel and the equipment and controlling risks in mining production. Field experiments of RSSI distance measurement were conducted on account of characteristics of the operational environment and engineering arrangements of the underground mine. In view of field experiments results, the RSSI-distance relation model was established. The trilateration positioning model and BP neural network positioning model were used to process and analyze the node positioning data. The mine cave-back monitoring method based on RSSI distance measurement is introduced.
{"title":"Study on the Detecting Technology of Mine Internet of Things Based on RSSI Technology","authors":"Jian Ming, Aibing Jin, Jinhai Sun, D. Hu, Yan Xia","doi":"10.1109/WOCC.2019.8770663","DOIUrl":"https://doi.org/10.1109/WOCC.2019.8770663","url":null,"abstract":"Based on the theory and technology of Internet of Things(IOT) and digital mine, the Mine Internet of Things (perception Mine) is used to detect and control of the personnel, equipment and mine environment, which can improve the ability of perceiving the operation status of the personnel and the equipment and controlling risks in mining production. Field experiments of RSSI distance measurement were conducted on account of characteristics of the operational environment and engineering arrangements of the underground mine. In view of field experiments results, the RSSI-distance relation model was established. The trilateration positioning model and BP neural network positioning model were used to process and analyze the node positioning data. The mine cave-back monitoring method based on RSSI distance measurement is introduced.","PeriodicalId":285172,"journal":{"name":"2019 28th Wireless and Optical Communications Conference (WOCC)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114187294","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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