International Journal of Sensors, Wireless Communications and Control最新文献_第4页

Examining the Effects of Exteroceptive Sensors of Autonomous Vehicles (AV) on CAN Bus 自动驾驶汽车外感传感器对CAN总线的影响研究

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-08-24 DOI: 10.2174/2210327913666230824145823

Zeina Ali, Qutaiba Ibrahim Ali

引用次数: 0

Optimizing Performance of Worst Case User in Ultra-Dense Networks utilizing Deep Q-learning 利用深度q学习优化超密集网络中最坏情况用户的性能

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-08-23 DOI: 10.2174/2210327913666230823094503

S. Lam, Duc-Tan Tran

{"title":"Optimizing Performance of Worst Case User in Ultra-Dense Networks utilizing Deep Q-learning","authors":"S. Lam, Duc-Tan Tran","doi":"10.2174/2210327913666230823094503","DOIUrl":"https://doi.org/10.2174/2210327913666230823094503","url":null,"abstract":"\u0000\u0000In Ultra-Dense Networks (UDNs), where the Base Stations are distributed with a very high density, the users are possibly near the cells’ intersection. These users are called the Worst-Case Users (WCU) and usually experience very low performance\u0000\u0000\u0000\u0000Thus, improving the WCU performance is an urgent problem to secure the service requirement of future cellular networks.\u0000\u0000\u0000\u0000In this paper, the performance of the WCU is analyzed in UDNs with a maximum power algorithm and under the wireless environment with Stretched Path Loss model and Rayleigh fading. To improve the WCU data rate, the Deep Q Networks with and without Multi-Input-Multi-output (MIMO) are utilized in this paper.\u0000\u0000\u0000\u0000The simulation results show that a system–based Deep Q Learning can dramatically improve the WCU performance compared to the system with the maximum power algorithm. In addition, the deployment of the MIMO technique in a system–based Deep Q-learning only has benefits in bad channel conditions.\u0000\u0000\u0000\u0000In any channel condition, utilization of Deep Q Learning is a suitable solution to improve the WCU performance. Furthermore, if the user experiences a good channel condition, the MIMO technique can be used with Deep Q Learning to obtain further performance improvement.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74036207","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

Elimination of herbicides after the classification of weeds using Deep Learning 杂草分类后使用深度学习消除除草剂

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-08-16 DOI: 10.2174/2210327913666230816091012

Indu Malik, Anurag Singh Baghel

{"title":"Elimination of herbicides after the classification of weeds using Deep Learning","authors":"Indu Malik, Anurag Singh Baghel","doi":"10.2174/2210327913666230816091012","DOIUrl":"https://doi.org/10.2174/2210327913666230816091012","url":null,"abstract":"\u0000\u0000Herbicides are chemicals that are used to destroy weeds. It is commonly used in agriculture to kill undesired plants and increase crop yield, even though it has negative effects on humans and the environment. Pesticides sprayed on crops must be decreased in the real world to protect humans, animals, and birds from dangerous diseases such as cancer, eyes, and skin infection. Pesticides are classified as herbicides. Deep learning is being used in this research to minimize chemical compounds. Scientists seek to limit the amount of pesticide sprayed on crops to protect humans and the environment from toxic exposure.\u0000\u0000\u0000\u0000In this research, A neural network classifier is built using Convolutional Neural Network (CNN), dropout, rectified linear activation unit (ReLU), the Root Mean Squared Propagation (RMSprop) optimization technique, and stochastic gradient descent (SGD). The algorithms based on CNN outperformed the others. This study uses generated dataset (unique dataset and processes it row-wise through the Neural network) to train a categorized neural network, and the dataset was created with the assistance of the agriculture professor.\u0000\u0000\u0000\u0000This study offers a method for classifying weed images and spraying herbicides solely on weeds/unwanted plants rather than crops. The model should first be trained using the training dataset before being tested using the testing datasets.\u0000\u0000\u0000\u0000This model's training accuracy is 96%, while testing accuracy is 89%.\u0000\u0000\u0000\u0000This model reduced herbicide (it is a type of pesticide/chemical) spray over the crop (foods, vegetables, sugarcane) to protect humans, animals, birds, and the environment from harmful chemicals.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84797611","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

Introducing a New Method for DPMU in Detecting the Type and Location of the Fault 介绍了一种DPMU检测故障类型和定位的新方法

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-08-16 DOI: 10.2174/2210327913666230816090948

Mohammad Zand, Morteza Azimi Nasab, S. Padmanaban, Bassam Khan

{"title":"Introducing a New Method for DPMU in Detecting the Type and Location of the Fault","authors":"Mohammad Zand, Morteza Azimi Nasab, S. Padmanaban, Bassam Khan","doi":"10.2174/2210327913666230816090948","DOIUrl":"https://doi.org/10.2174/2210327913666230816090948","url":null,"abstract":"\u0000\u0000Nowadays, due to the increasing development of distribution networks, their safety and high-reliability performance are of particular importance. One of the most important problems that endanger the security and reliability of these networks is the creation of some faults in them. In case of a fault in the network, identifying its location and type can be of great help in repairing faulty equipment. Also, by detecting the disconnection of one of the equipment or lines, it is possible to prevent accidents in the network.\u0000\u0000\u0000\u0000Phasor Measurement Unit (PMU) has been widely and successfully used as Transmission-Phasor Measurement Unit (T-PMU). The reporting time of PMUs is much shorter than the old Supervisory Control and Data Acquisition (SCADA) systems. They can provide synchronized phasor measurements that can generate voltage phasors of different network nodes. This study aimed to investigate the various applications of phasor measurement units in distribution networks and present a new method for detecting and analyzing the location and type of fault and topology fault of the distribution network using the Internet of Things (IOT) analysis method.\u0000\u0000\u0000\u0000To implement this method, it is necessary to measure different parameters of the distribution network before and after the occurrence of a fault, which is used by the DPMU for measurement. The simulation results indicate that for both single-topology and multi-topology faults, the proposed method has higher accuracy and better detection than the remaining common methods and effectively detects single-topology and multi-topology faults in the distribution network.\u0000\u0000\u0000\u0000This method can provide a more accurate network topology to estimate the state of the distribution network, which improves the accuracy of the state estimation and is suitable for implementing various advanced functions of the distribution management system.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79615727","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

Fault Detection in Windmills Using Augmented Reality 基于增强现实技术的风车故障检测

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-08-15 DOI: 10.2174/2210327913666230815121221

Jayabala Pradeep, P. Arunagiri, M. Harikrishnan, L. Martin

引用次数: 0

Analysis of MMSE Multiuser Detector in a Low-density Parity Check Coded Large Scale MIMO OFDM 低密度奇偶校验编码大规模MIMO OFDM中MMSE多用户检测器的分析

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-07-27 DOI: 10.2174/2210327913666230727095458

Shefin Shoukath, P. Haris

{"title":"Analysis of MMSE Multiuser Detector in a Low-density Parity Check Coded Large Scale MIMO OFDM","authors":"Shefin Shoukath, P. Haris","doi":"10.2174/2210327913666230727095458","DOIUrl":"https://doi.org/10.2174/2210327913666230727095458","url":null,"abstract":"\u0000\u0000Large-scale MIMO OFDM technique satisfies the demands on performance\u0000and the service quality preferred in wireless communication systems. Since numerous antenna terminals have been incorporated in the base station, multiuser detection is crucial for retrieving the data\u0000appropriately. Thus, the complexities of the detectors increase rapidly in large-scale MIMO OFDM\u0000schemes.\u0000\u0000\u0000\u0000This work is a solution to achieve an extensively high rate of data transmission, which will\u0000help improve the capacity of the LS MIMO OFDM system.\u0000\u0000\u0000\u0000A unique detection approach of multiuser detection in LS MIMO OFDM model with channel coding, like low density parity check codes (LDPC), is suggested in this paper. The LDPC-coded\u0000large-scale MIMO OFDM system has also been analysed in the study with users of around ten at the\u0000transmitter and several antennas in the base station.\u0000\u0000\u0000\u0000BER of the LDPC-coded LS MIMO OFDM exhibited a waterfall region for SNR greater\u0000than 6dB as the study has been done with different decoding iterations. The BER performance\u0000worsened with the increase in modulation symbols. The study has shown how the BER performance\u0000has improved with respect to the increasing fading channels and subcarriers.\u0000\u0000\u0000\u0000The proposed system exhibited performance closer to the MIMO capacity with low\u0000complexity MMSE detection. The multiuser detector of LDPC-coded LS MIMO OFDM has been\u0000analysed by error rate in received bits (BER) with respect to different parameters, such as modulation\u0000orders, iteration values, receiving antennas, and OFDM subcarriers.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80891079","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

SDR Implementation of Spectrum Sensing Using Deep Learning 基于深度学习的频谱感知SDR实现

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-07-19 DOI: 10.2174/2210327913666230719152400

Zeghdoud Sabrina, Teguig Djamal, Tanougast Camel, Mesloub Amar, Sadoudi Said, Nesraoui Okba

{"title":"SDR Implementation of Spectrum Sensing Using Deep Learning","authors":"Zeghdoud Sabrina, Teguig Djamal, Tanougast Camel, Mesloub Amar, Sadoudi Said, Nesraoui Okba","doi":"10.2174/2210327913666230719152400","DOIUrl":"https://doi.org/10.2174/2210327913666230719152400","url":null,"abstract":"\u0000\u0000Software Defined Radio (SDR) is a technology that offers a high level of reconfigurability to address the issue of spectrum sparsity in wireless communication systems. This technology is widely used in Cognitive radio (CR), and researchers aim to develop new spectrum sensing methods that ensure a high signal detection performance and a low signal-to-noise ratio (SNR). In this context, deep learning (DL) based models can be an appropriate solution for building spectrum detection methods.\u0000\u0000\u0000\u0000This paper proposes a spectrum sensing architecture combining a convolutional neural network and long short-term memory (CNN-LSTM). This architecture takes advantage of the spatial modelling of CNN and the temporal modelling of LSTM to produce more separable features for detection. The paper aims to propose an SDR implementation of the CNN-LSTM model for real-time detection by using the Universal Software Radio Peripheral (USRP) board and GNU radio platform.\u0000\u0000\u0000\u0000Results and Discussion: Numerical Simulation results reveal that the proposed CNN-LSTM outperforms the CNN, the LSTM, and the energy detector (ED) in terms of higher detection probability Pd and lower false alarm probability Pfa, even at low SNR. The SDR implementation results show the robustness of the CNN-LSTM method under several real-time detection scenarios: FM, GSM, and OFDM.\u0000\u0000\u0000\u0000The CNN-LSTM model used for spectrum sensing provides a high detection performance in a low SNR environment compared to LSTM, CNN, and the ED detector.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73159301","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

Asymmetric Successive Compute-and-Forward and the Capacity Gap for the Gaussian Two-Way Relay Channel 高斯双向中继信道的非对称连续计算转发和容量间隙

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-06-05 DOI: 10.2174/2210327913666230605120441

Leila Ghabeli

{"title":"Asymmetric Successive Compute-and-Forward and the Capacity Gap for the Gaussian Two-Way Relay Channel","authors":"Leila Ghabeli","doi":"10.2174/2210327913666230605120441","DOIUrl":"https://doi.org/10.2174/2210327913666230605120441","url":null,"abstract":"The compute-and-forward strategy is one of the outstanding methods which is used for interference management in wireless relay networks where decoding linear combinations of code words is required. Recently, many efforts have been made for decoding integer and non-integer combinations [1]-[7]. The difference between the methods is the manner of handling different conditions of networks, such as equal or unequal power constraints and equal or unequal channel gains.\u0000\u0000\u0000\u0000In this work, we present a modified n-step asymmetric successive compute-and-forward strategy for the communication network where we have both unequal power constraints and unequal channel gains conditions.\u0000\u0000\u0000\u0000In the proposed method, we scale channel gains and coefficients with the square root of power constraints. In this way, despite previous methods, without the need for scaling factors in our formulation, it is still able to solve the problem of general Gaussian relay networks with unequal power constraints and unequal channel gains. We also use scaling factors in our method in order to have the ability to divide the rates between users fairly.\u0000\u0000\u0000\u0000We evaluate the ability of the modified strategy for the uplink communication of the two-way relay channel, where one relay can help communication between the two users. At the relay, we decode the linear combinations of the messages of the two users and obtain 1/2 bit/sec/Hz per user capacity gap from the cut-set bound. Through some theoretical and simulation results, we show that by appropriately adjusting parameters, different points and areas of rate regions are achievable.","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90597620","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

A New Effective Strategy for User Association in Heterogeneous Networks 异构网络中一种新的有效用户关联策略

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-06-01 DOI: 10.2174/2210327913666230601153113

L.Aziz, A. Gourari, S.Achki

{"title":"A New Effective Strategy for User Association in Heterogeneous Networks","authors":"L.Aziz, A. Gourari, S.Achki","doi":"10.2174/2210327913666230601153113","DOIUrl":"https://doi.org/10.2174/2210327913666230601153113","url":null,"abstract":"\u0000\u0000Heterogeneous networks (HetNet) represent a promising technology that satisfies the needs of mobile users. However, several problems have influenced the performance of wireless communication, such as the maximization of energy efficiency and the problem of interferences due to the uncontrolled association of the user equipment (UE).\u0000\u0000\u0000\u0000Solving the problem of maximizing energy efficiency has captured the attention of several researchers. In this work, we propose an effective user association based on K-nearest Neighbors (KNN) approach considering a large dataset. The major novelty of this work is that the supervised learning perspective is applied to a dataset regrouped from an optimal user association, where the most valuable parameters are considered.\u0000\u0000\u0000\u0000Additionally, it allows for mitigating the problem of interferences using individual user association. Simulation results have proven the efficiency of the proposed methodology\u0000\u0000\u0000\u0000The suggested results have outperformed the two works in terms of accuracy, where the proposed method presents a better accuracy of 95%.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79283009","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

Trust Computational Model For Iot Using Machine Learning 使用机器学习的物联网信任计算模型

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-05-25 DOI: 10.2174/2210327913666230525141053

C. K. Marigowda, T. J, G. S, V. K. R., Muthyamala A

{"title":"Trust Computational Model For Iot Using Machine Learning","authors":"C. K. Marigowda, T. J, G. S, V. K. R., Muthyamala A","doi":"10.2174/2210327913666230525141053","DOIUrl":"https://doi.org/10.2174/2210327913666230525141053","url":null,"abstract":"\u0000\u0000The Internet of Things has evolved over the years to a greater extent, where objects communicate with each other over a network. Heterogenous communication between the nodes leads to a large amount of information sharing, and sensitive information could be shared over the network. It is important to maintain privacy and security during information sharing to protect devices from communicating with malicious nodes.\u0000\u0000\u0000\u0000The concept of trust was introduced to prevent nodes from communicating with malicious nodes. A trust computation model for the IoT based on machine learning concepts was designed, which evaluates trust based on the Trust Marks. There are three trust marks, out of which two are evaluated. The three trust marks are knowledge, experience, and reputation. Knowledge trust marks are evaluated separately based on their trust property mathematical formulations, and then based on these properties, machine learning-based algorithms are applied to train the model to classify the objects as trustworthy and untrustworthy.\u0000\u0000\u0000\u0000The effectiveness of the Knowledge Trust Mark is measured by a simulation and confusion matrix. The accuracy of the trained model is shown by the accuracy score. The trust computational model for IoT using machine learning shows higher accuracy in classifying the objects as trustworthy and untrustworthy.\u0000\u0000\u0000\u0000The experience trust mark is evaluated based on its properties, and the behaviour of the experience is shown over time graphically.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"239 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74901755","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