Pub Date : 2024-01-21DOI: 10.2174/0122103279272325231130112108
AD Meriem, Khelil Abdellatif
Non-orthogonal multiple access (NOMA) is a promising technique for improving wireless communication performance in the future. In addition to NOMA, cognitive radio (CR) is another technology that can address the issue of limited spectrum availability and meet the increasing demands for wireless connectivity. This paper focuses on investigating underlay CR-NOMA-based D2D communications. The study assumes a decode-and-forward (DF) mode used in the system, where nearby users (D1, D2) act as helper users to assist distant users (D3, D4). The paper derives the closed-form expressions for outage probability (OP) and throughput at the far users in three scenarios: (1) Perfect successive interference cancellation (SIC) and perfect channel state information (CSI), (2) Imperfect CSI, and (3) Imperfect SIC. In CR-NOMA mode, the results indicate that the performance of user D4 was better than user D3. Additionally, the OP performance of distant users employing CR-NOMA mode surpasses that of users using CR-OMA mode. The optimal power allocation (PA) values are investigated. The presence of imperfect CSI and SIC has an unfavorable influence on the outage performance. Monte Carlo simulations are used to validate the derived analytical expressions.
{"title":"Outage Performance of Underlay CR-NOMA-based D2D Communications\u0000under Imperfect CSI and SIC","authors":"AD Meriem, Khelil Abdellatif","doi":"10.2174/0122103279272325231130112108","DOIUrl":"https://doi.org/10.2174/0122103279272325231130112108","url":null,"abstract":"\u0000\u0000Non-orthogonal multiple access (NOMA) is a promising technique for improving\u0000wireless communication performance in the future. In addition to NOMA, cognitive radio\u0000(CR) is another technology that can address the issue of limited spectrum availability and meet the\u0000increasing demands for wireless connectivity.\u0000\u0000\u0000\u0000This paper focuses on investigating underlay CR-NOMA-based D2D communications.\u0000The study assumes a decode-and-forward (DF) mode used in the system, where nearby users (D1,\u0000D2) act as helper users to assist distant users (D3, D4). The paper derives the closed-form expressions\u0000for outage probability (OP) and throughput at the far users in three scenarios: (1) Perfect successive\u0000interference cancellation (SIC) and perfect channel state information (CSI), (2) Imperfect CSI, and\u0000(3) Imperfect SIC.\u0000\u0000\u0000\u0000In CR-NOMA mode, the results indicate that the performance of user D4 was better than\u0000user D3. Additionally, the OP performance of distant users employing CR-NOMA mode surpasses\u0000that of users using CR-OMA mode. The optimal power allocation (PA) values are investigated.\u0000\u0000\u0000\u0000The presence of imperfect CSI and SIC has an unfavorable influence on the outage performance.\u0000Monte Carlo simulations are used to validate the derived analytical expressions.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"16 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139609838","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 : 2024-01-19DOI: 10.2174/0122103279273609231213075003
A. D. Sree, Kapil Sharma
The topology and communication links of vehicular adhoc networks, or VANETs, are always changing due to the transient nature of automobiles. VANETs are a subset of MANETs that have applications in the transportation sector, specifically in Intelligent Transportation Systems (ITS). Routing in these networks is challenging due to frequent link detachments, rapid topological changes, and high vehicle mobility. As a result, there are many obstacles and constraints in the way of creating an effective routing protocol that satisfies latency restrictions with minimal overhead. Malicious vehicle detection is also a crucial role in VANETs. Unmanned-Aerial-Vehicles(UAVs) can be useful for overcoming these constraints. This study examines the utilize of UAVs operating in an adhoc form and cooperating via cars VANETs to aid in the routing and detection of hostile vehicles. VANET is a routing protocol. The proposed UAV-assisted routing protocol (VRU) incorporates two separate protocols for routing data: (1) a protocol called VRU_vu for delivering data packets amid vehicles with the assist of UAVs, and (2) a protocol called VRU_u for routing data packets amid UAVs. To estimate the efficacy of VRU routing objects in a metropolitan setting, we run the NS-2.35 simulator under Linux Ubuntu 12.04. Vehicle and UAV motions can also be generated with the help of the mobility generator VanetMobiSim and the mobility simulation software MobiSim. According to the results of the performance analysis, the VRU-protocol is able to outperform the other evaluated routing protocols in terms of packet-delivery-ratio (by 17 percent) &detection-ratio (9 percent). The VRU protocol cuts overhead near 41% and reduces end-to-enddelay in mean of 15%.
{"title":"Machine Learning Based Secure Routing Protocol with Uav-Assisted for\u0000Autonomous Vehicles","authors":"A. D. Sree, Kapil Sharma","doi":"10.2174/0122103279273609231213075003","DOIUrl":"https://doi.org/10.2174/0122103279273609231213075003","url":null,"abstract":"\u0000\u0000The topology and communication links of vehicular adhoc\u0000networks, or VANETs, are always changing due to the transient nature of automobiles. VANETs\u0000are a subset of MANETs that have applications in the transportation sector, specifically in Intelligent\u0000Transportation Systems (ITS). Routing in these networks is challenging due to frequent\u0000link detachments, rapid topological changes, and high vehicle mobility.\u0000\u0000\u0000\u0000As a result, there are many obstacles and constraints in the way of creating an effective\u0000routing protocol that satisfies latency restrictions with minimal overhead. Malicious vehicle detection\u0000is also a crucial role in VANETs. Unmanned-Aerial-Vehicles(UAVs) can be useful for\u0000overcoming these constraints. This study examines the utilize of UAVs operating in an adhoc\u0000form and cooperating via cars VANETs to aid in the routing and detection of hostile vehicles.\u0000VANET is a routing protocol. The proposed UAV-assisted routing protocol (VRU) incorporates\u0000two separate protocols for routing data: (1) a protocol called VRU_vu for delivering data packets\u0000amid vehicles with the assist of UAVs, and (2) a protocol called VRU_u for routing data packets\u0000amid UAVs.\u0000\u0000\u0000\u0000To estimate the efficacy of VRU routing objects in a metropolitan setting, we run the\u0000NS-2.35 simulator under Linux Ubuntu 12.04. Vehicle and UAV motions can also be generated\u0000with the help of the mobility generator VanetMobiSim and the mobility simulation software MobiSim.\u0000\u0000\u0000\u0000According to the results of the performance analysis, the VRU-protocol is able to\u0000outperform the other evaluated routing protocols in terms of packet-delivery-ratio (by 17 percent)\u0000&detection-ratio (9 percent). The VRU protocol cuts overhead near 41% and reduces end-to-enddelay\u0000in mean of 15%.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"495 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502490","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 : 2024-01-19DOI: 10.2174/0122103279275330231217072855
Hemalatha K, Amanullah M
Wireless Sensor Networks (WSNs) have emerged as a crucial technology for various applications, but they face a lot of challenges relevant to limited energy resources, delayed communications, and complex data aggregation. To address these issues, this study proposes novel approaches called GAN-based Clustering and LSTM-based Data Aggregation (GCLD) that aim to enhance the performance of WSNs. The proposed GCLD method enhances the Quality of Service (QoS) of WSN by leveraging the capabilities of Generative Adversarial Networks (GANs) and the Long Short-Term Memory (LSTM) method. GANs are employed for clustering, where the generator assigns cluster assignments or centroids, and the discriminator distinguishes between real and generated cluster assignments. This adversarial learning process refines the clustering results. Subsequently, LSTM networks are used for data aggregation, capturing temporal dependencies and enabling accurate predictions. The evaluation results demonstrate the superior performance of GCLD in terms of delay, PDR, energy consumption, and accuracy than the existing methods. Overall, the significance of GCLD in advancing WSNs highlights its potential impact on various applications.
{"title":"Effective Hybrid Deep Learning Models of GAN and LSTM for Clustering\u0000and Data Aggregation in Wireless Sensor Networks","authors":"Hemalatha K, Amanullah M","doi":"10.2174/0122103279275330231217072855","DOIUrl":"https://doi.org/10.2174/0122103279275330231217072855","url":null,"abstract":"\u0000\u0000Wireless Sensor Networks (WSNs) have emerged as a crucial technology for\u0000various applications, but they face a lot of challenges relevant to limited energy resources, delayed\u0000communications, and complex data aggregation. To address these issues, this study proposes novel\u0000approaches called GAN-based Clustering and LSTM-based Data Aggregation (GCLD) that aim to enhance the performance of WSNs.\u0000\u0000\u0000\u0000The proposed GCLD method enhances the Quality of Service (QoS) of WSN by leveraging\u0000the capabilities of Generative Adversarial Networks (GANs) and the Long Short-Term Memory\u0000(LSTM) method. GANs are employed for clustering, where the generator assigns cluster assignments\u0000or centroids, and the discriminator distinguishes between real and generated cluster assignments. This\u0000adversarial learning process refines the clustering results. Subsequently, LSTM networks are used for\u0000data aggregation, capturing temporal dependencies and enabling accurate predictions.\u0000\u0000\u0000\u0000The evaluation results demonstrate the superior performance of GCLD in terms of delay,\u0000PDR, energy consumption, and accuracy than the existing methods.\u0000\u0000\u0000\u0000Overall, the significance of GCLD in advancing WSNs highlights its potential impact on\u0000various applications.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"82 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139613099","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 : 2024-01-19DOI: 10.2174/0122103279273418231212053836
K. Kumar, Amanpreet Kaur, Bishwajeet Pandey
This paper will focus on promoting the ideas of green communication Pulse Width Modulation (PWM) generator is used to control the power transfer in any communication model. It is one of the most crucial parts of an electrical circuit. Our main focus in this research work is to develop an energy and power-efficient PWM generator by using Field Programmable Gate Array (FPGA) logic to elevate green communication. Our main focus in this research work is to develop an energy and power-efficient PWM generator by using Field Programmable Gate Array (FPGA) logic to elevate green communication. In order to make the PWM suitable for GC, we have implemented the design on VIVADO ISE from Xilinx. The power analysis as well as resource utilization are targeted on three different FPGAs. Different IO standards of Stub Series Terminated Logic (SSTL) family are explored at different FPGA’s. Power analysis is deployed on the 7 series FPGAs of 3 different categories i.e., Spartan 7 (channel length = 28 nm), Kintex 7 (channel length = 20 nm) and ultra scale Zynq 7 (channel length = 16 nm). It can be concluded from power analysis that SPARTAN-7 device is the most powerefficient and ZYNQ Ultra scale+utilizes the highest amount of power. However, KINTEX-7 Ultrascale device lies in the middle of both these devices as far as power consumption is concerned. There is a reduction of 43.07 % TP consumption for SPARTAN-7 device with SSTL135 IO when equated with ZYNQ Ultra scale+ with SSTL18_I IO. Also, it can be observed from sections 5.1, 5.2 and 5.3 that there is more contribution of DP in TP consumption than SP. Hence the device utilizes additional power when it is in active state than static state. Since PWM generator is an integral part of data and wireless communication, it should require less power for proficient transmission and wellorganized green computing and communication
{"title":"Design of a Power Efficient Model of PWM Generator for Green Communication using High Performance FPGAs","authors":"K. Kumar, Amanpreet Kaur, Bishwajeet Pandey","doi":"10.2174/0122103279273418231212053836","DOIUrl":"https://doi.org/10.2174/0122103279273418231212053836","url":null,"abstract":"\u0000\u0000This paper will focus on promoting the ideas of green communication\u0000\u0000\u0000\u0000Pulse Width Modulation (PWM) generator is used to control the power transfer in any\u0000communication model. It is one of the most crucial parts of an electrical circuit. Our main focus in\u0000this research work is to develop an energy and power-efficient PWM generator by using Field Programmable Gate Array (FPGA) logic to elevate green communication.\u0000\u0000\u0000\u0000Our main focus in this research work is to develop an energy and power-efficient PWM\u0000generator by using Field Programmable Gate Array (FPGA) logic to elevate green communication.\u0000\u0000\u0000\u0000In order to make the PWM suitable for GC, we have implemented the design on VIVADO\u0000ISE from Xilinx. The power analysis as well as resource utilization are targeted on three different\u0000FPGAs.\u0000\u0000\u0000\u0000Different IO standards of Stub Series Terminated Logic (SSTL) family are explored at different FPGA’s. Power analysis is deployed on the 7 series FPGAs of 3 different categories i.e., Spartan 7 (channel length = 28 nm), Kintex 7 (channel length = 20 nm) and ultra scale Zynq 7 (channel\u0000length = 16 nm).\u0000\u0000\u0000\u0000It can be concluded from power analysis that SPARTAN-7 device is the most powerefficient and ZYNQ Ultra scale+utilizes the highest amount of power. However, KINTEX-7 Ultrascale device lies in the middle of both these devices as far as power consumption is concerned.\u0000There is a reduction of 43.07 % TP consumption for SPARTAN-7 device with SSTL135 IO when\u0000equated with ZYNQ Ultra scale+ with SSTL18_I IO. Also, it can be observed from sections 5.1, 5.2\u0000and 5.3 that there is more contribution of DP in TP consumption than SP. Hence the device utilizes\u0000additional power when it is in active state than static state. Since PWM generator is an integral part of\u0000data and wireless communication, it should require less power for proficient transmission and wellorganized green computing and communication\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"91 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139612761","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 : 2024-01-19DOI: 10.2174/0122103279275188231205094007
Monika Agrawal, Nageswara Rao Moparthi
As the e-commerce product reviews and social media posts are increasing enormously, the size of the database for polarity/ sentiment detection is a challenging task, and again, predicting polarities associated with respect to aspect terms end to end in a sentence is a havoc in real-time applications. Human behavior is influenced by the various opinions generated in society. Public opinion influences our decisions most often. Businesses and establishments always need to collect the opinion of the society, which they try to obtain using customer feedback forms and questionnaires or surveys, which help them to be aware of the shortcomings if any, and to use suggestions to improve quality. It works in the same way for customers as well and the opinions of other customers about a particular product can come in handy when deciding to buy a product. In this work, an efficient Aspect-based Sentiment Classification technique has been introduced with a hybrid, multiple-word embedding methods and implemented using the CNN framework on large databases. Most of the traditional models have a limitation on the dependency for one or more similar types of aspect words for sentiment classification problem. However, these conventional models such as TF-ID, Word 2Vec and Glove method consumes much more time for word embedding process and Aspect terms generation and further process of aspect level sentiment classification. Further, these models are facing problems of high true negative rate and misclassification rate on large aspect databases in sentiment classification. In this article, we have introduced an efficient Proposed ensemble word embedding model in the CNN network and defined Hybrid Word2 Vec method, Hybrid Glove word embedding method and Hybrid Random Forest model for sentiment classification. Experiments on a widely used benchmark prove that the proposed word embedding method-based classification technique results in to higher true positive rate with minimal misclassifications and also supports better runtime and accuracy than the traditional word embedding-based aspect level classification approaches. In this article, a hybrid ensemble feature ranking-based classification model is proposed on the large aspect databases. In this work, advanced multiple-word embedding methods are implemented to improve the essential feature extraction problem in the aspect level sentiment process. These multiple-word embedding methods are applied to the sentiment databases in the CNN framework.
{"title":"An Efficient Aspect-based Sentiment Classification with Hybrid Word\u0000Embeddings and CNN Framework","authors":"Monika Agrawal, Nageswara Rao Moparthi","doi":"10.2174/0122103279275188231205094007","DOIUrl":"https://doi.org/10.2174/0122103279275188231205094007","url":null,"abstract":"\u0000\u0000As the e-commerce product reviews and social media posts are increasing\u0000enormously, the size of the database for polarity/ sentiment detection is a challenging task, and\u0000again, predicting polarities associated with respect to aspect terms end to end in a sentence is a havoc in real-time applications. Human behavior is influenced by the various opinions generated in society. Public opinion influences our decisions most often. Businesses and establishments always\u0000need to collect the opinion of the society, which they try to obtain using customer feedback forms\u0000and questionnaires or surveys, which help them to be aware of the shortcomings if any, and to use\u0000suggestions to improve quality. It works in the same way for customers as well and the opinions of\u0000other customers about a particular product can come in handy when deciding to buy a product.\u0000\u0000\u0000\u0000In this work, an efficient Aspect-based Sentiment Classification technique has been introduced with a hybrid, multiple-word embedding methods and implemented using the CNN\u0000framework on large databases.\u0000\u0000\u0000\u0000Most of the traditional models have a limitation on the dependency for one or more similar types of aspect words for sentiment classification problem. However, these conventional models\u0000such as TF-ID, Word 2Vec and Glove method consumes much more time for word embedding process and Aspect terms generation and further process of aspect level sentiment classification. Further, these models are facing problems of high true negative rate and misclassification rate on large\u0000aspect databases in sentiment classification. In this article, we have introduced an efficient Proposed\u0000ensemble word embedding model in the CNN network and defined Hybrid Word2 Vec method, Hybrid Glove word embedding method and Hybrid Random Forest model for sentiment classification.\u0000\u0000\u0000\u0000Experiments on a widely used benchmark prove that the proposed word embedding method-based classification technique results in to higher true positive rate with minimal misclassifications and also supports better runtime and accuracy than the traditional word embedding-based aspect level classification approaches.\u0000\u0000\u0000\u0000In this article, a hybrid ensemble feature ranking-based classification model is proposed on the large aspect databases. In this work, advanced multiple-word embedding methods are\u0000implemented to improve the essential feature extraction problem in the aspect level sentiment process. These multiple-word embedding methods are applied to the sentiment databases in the CNN\u0000framework.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"49 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139613525","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 : 2024-01-05DOI: 10.2174/0122103279260571231213053403
Sourav Maity, Karan Veer
Facial electromyography (fEMG) records muscular activities from the facial muscles, which provides details regarding facial muscle stimulation patterns in experimentation. The Principal Component Analysis (PCA) is mostly implemented, whereas the actual or unprocessed initial fEMG data are rendered into low-spatial units with minimizing the level of data repetition. Facial EMG signal was acquired by using the instrument BIOPAC MP150. Four electrodes were fixed on the face of each participant for capturing the four different emotions like happiness, anger, sad and fear. Two electrodes were placed on arm for grounding purposes. The aim of this research paper is to propagate the functioning of PCA in synchrony with the subjective fEMG analysis and to give a thorough apprehension of the advanced PCA in the areas of machine learning. It describes its arithmetical characteristics, while PCA is estimated by implying the covariance matrix. Datasets which are larger in size are progressively universal and their interpretation often becomes complex or tough. So, it is necessary to minimize the number of variables and elucidate linear compositions of the data to explicate it on a huge number of variables with a relevant approach. Therefore, Principal Component Analysis (PCA) is applied because it is an unsupervised training method that utilizes advanced statistical concept to minimize the dimensionality of huge datasets. This work is furthermore inclined toward the analysis of fEMG signals acquired for four different facial expressions using Analysis of Variance (ANOVA) to provide clarity on the variation of features.
{"title":"An Approach for Evaluation and Recognition of Facial Emotions Using\u0000EMG Signal","authors":"Sourav Maity, Karan Veer","doi":"10.2174/0122103279260571231213053403","DOIUrl":"https://doi.org/10.2174/0122103279260571231213053403","url":null,"abstract":"\u0000\u0000Facial electromyography (fEMG) records muscular activities from the facial\u0000muscles, which provides details regarding facial muscle stimulation patterns in experimentation.\u0000\u0000\u0000\u0000The Principal Component Analysis (PCA) is mostly implemented, whereas the actual or\u0000unprocessed initial fEMG data are rendered into low-spatial units with minimizing the level of data\u0000repetition.\u0000\u0000\u0000\u0000Facial EMG signal was acquired by using the instrument BIOPAC MP150. Four electrodes\u0000were fixed on the face of each participant for capturing the four different emotions like happiness,\u0000anger, sad and fear. Two electrodes were placed on arm for grounding purposes.\u0000\u0000\u0000\u0000The aim of this research paper is to propagate the functioning of PCA in synchrony with the\u0000subjective fEMG analysis and to give a thorough apprehension of the advanced PCA in the areas of\u0000machine learning. It describes its arithmetical characteristics, while PCA is estimated by implying the\u0000covariance matrix. Datasets which are larger in size are progressively universal and their interpretation often becomes complex or tough. So, it is necessary to minimize the number of variables and\u0000elucidate linear compositions of the data to explicate it on a huge number of variables with a relevant\u0000approach. Therefore, Principal Component Analysis (PCA) is applied because it is an unsupervised\u0000training method that utilizes advanced statistical concept to minimize the dimensionality of huge datasets.\u0000\u0000\u0000\u0000This work is furthermore inclined toward the analysis of fEMG signals acquired for four\u0000different facial expressions using Analysis of Variance (ANOVA) to provide clarity on the variation\u0000of features.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"30 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139449895","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 : 2024-01-03DOI: 10.2174/0122103279270847231205100550
B. Gumaida, Adamu Abubakar Ibrahim
Magnificent localization precision and low operating expenses are the main keys and essential issues to managing and operating outdoor wireless sensor networks. This work proposes a novel and rigorous efficiency localization algorithm utilizing a simplex optimization approach for node localization. This novel optimization method is a direct search approach, and is usually directed to solve nonlinear optimization problems that may not have wellknown derivatives, and it is called the Nelder-mead Method (NMM). It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. This paper emphasizes employing a ranging technique called Received Signal Strength Indicator (shortly RSSI) to calculate the length of distances among all the nodes of WSNs. Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other optimization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). This obviously appeared in several metrics of performance evaluation, such as accuracy of localization, node localization rate, and implementation time. The proposed algorithm that utilized NMM is more functional to enhance the precision of localization because of particular characteristics that are the flexible implementation of NMM and the free cost of using the RSSI technique.
{"title":"A Novel Polytope Algorithm based On Nelder-mead Method for Localization in Wireless Sensor Network","authors":"B. Gumaida, Adamu Abubakar Ibrahim","doi":"10.2174/0122103279270847231205100550","DOIUrl":"https://doi.org/10.2174/0122103279270847231205100550","url":null,"abstract":"\u0000\u0000Magnificent localization precision and low operating expenses are the main keys and essential issues to managing and operating outdoor wireless sensor networks. This work proposes a novel and rigorous efficiency localization algorithm utilizing a simplex\u0000optimization approach for node localization. This novel optimization method is a direct search approach, and is usually directed to solve nonlinear optimization problems that may not have wellknown derivatives, and it is called the Nelder-mead Method (NMM).\u0000\u0000\u0000\u0000It is suggested that the objective function that will be optimized using NMM is the mean\u0000squared error of the range of all neighboring anchor nodes installed in the studied WSNs. This paper\u0000emphasizes employing a ranging technique called Received Signal Strength Indicator (shortly RSSI)\u0000to calculate the length of distances among all the nodes of WSNs.\u0000\u0000\u0000\u0000Simulation results perfectly showed that the suggested localization algorithm based on\u0000NMM can carry out a better performance than that of other localization algorithms utilizing other optimization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm\u0000(BA). This obviously appeared in several metrics of performance evaluation, such as accuracy of localization, node localization rate, and implementation time.\u0000\u0000\u0000\u0000The proposed algorithm that utilized NMM is more functional to enhance the precision\u0000of localization because of particular characteristics that are the flexible implementation of NMM and\u0000the free cost of using the RSSI technique.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"30 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139389177","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 : 2024-01-03DOI: 10.2174/0122103279287823231207072006
F. Lone, H. Verma, Krishna Pal Sharma
Intelligent Transportation Systems (ITS) have attracted the attention of developing nations because of their potential to enhance mobility and road safety, two issues that have become increasingly pressing in recent years. Information and Communication Technology (ICT) has accentuated every industry, and the automobile industry is no exception, allowing vehicles to communicate among themselves and the surrounding infrastructure for information exchange using Vehicle-to-Everything (V2X) communication. Vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-cloud (V2C) connections are made possible through the use of state-of-the-art networking technology. With EVehicles at the forefront, the vision of an ITS expands further. ITS is anticipated to offer wireless network-based services including vehicle occupant entertainment, traffic flow optimization, and accident prevention. Most nations have been trying to standardize the ITS architecture, and the European Union (EU) has been at the forefront by developing and standardizing the ETSI (European Telecommunications Standards Institute) architecture. As the most mature ITS architecture, this paper thoroughly explains the ETSI architecture in a single document for both the researcher's and newcomers' ease. Additionally, the challenges and issues pertinent to adopting and implementing the ITS ecosystem have also been discussed in detail
智能交通系统（ITS）因其在提高机动性和道路安全方面的潜力而备受发展中国家的关注。信息和通信技术（ICT）已在各行各业得到广泛应用，汽车行业也不例外，它允许车辆之间以及车辆与周围基础设施之间利用车对物（V2X）通信进行信息交换。通过使用最先进的网络技术，车对车（V2V）、车对基础设施（V2I）、车对行人（V2P）和车对云（V2C）连接成为可能。随着电动汽车的发展，智能交通系统的愿景将进一步扩大。预计智能交通系统将提供基于无线网络的服务，包括车内娱乐、交通流优化和事故预防。大多数国家一直在努力实现智能交通系统架构的标准化，而欧盟（EU）通过开发和标准化 ETSI（欧洲电信标准协会）架构走在了前列。作为最成熟的 ITS 体系结构，本文在一份文件中全面介绍了 ETSI 体系结构，以方便研究人员和新手使用。此外，本文还详细讨论了采用和实施 ITS 生态系统所面临的挑战和问题。
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Pub Date : 2024-01-03DOI: 10.2174/0122103279266100231210125510
J. R. Jeya Shiney, A. A. Clarence Asis
The channel sparsity is exploited by transforming the channel into an angular domain from the spatial domain at millimeter wave frequencies in Beamspace Multiple-Input Multiple-Output (B-MIMO) systems. Every beam in B-MIMO corresponds to an individual radio frequency (RF) chain, and thus, beam selection techniques can reduce the RF hardware complexity. RF chain limitation is needed for an ideal beamspace precoding scheme to attain good system performance across the entire bandwidth. New methods of beamspace channel estimation with a small amount of estimation error and low computational complexity are challenging in the beam domain due to the larger antenna arrays deployed. A novel beamspace processing technique to improve the direction of arrival estimation performance for different array configurations with improvement in system performance is desired in a 5G system. A detailed review of the B-MIMO system with its architecture and various beam selection techniques is presented in this paper. The scope of the work is elaborated by incorporating various existing beamspace precoding and channel estimation methods. The paper also presents various beamspace processing schemes for parameter estimation with a focus on the direction of arrival estimation performance.
{"title":"A Survey on Beamspace Millimeter-wave Massive Mimo Systems: An\u0000Overview of Open Issues, Challenges, and Future Research Trends","authors":"J. R. Jeya Shiney, A. A. Clarence Asis","doi":"10.2174/0122103279266100231210125510","DOIUrl":"https://doi.org/10.2174/0122103279266100231210125510","url":null,"abstract":"\u0000\u0000The channel sparsity is exploited by transforming the channel into an angular domain from\u0000the spatial domain at millimeter wave frequencies in Beamspace Multiple-Input Multiple-Output\u0000(B-MIMO) systems. Every beam in B-MIMO corresponds to an individual radio frequency (RF)\u0000chain, and thus, beam selection techniques can reduce the RF hardware complexity. RF chain limitation is needed for an ideal beamspace precoding scheme to attain good system performance across\u0000the entire bandwidth. New methods of beamspace channel estimation with a small amount of estimation error and low computational complexity are challenging in the beam domain due to the larger\u0000antenna arrays deployed. A novel beamspace processing technique to improve the direction of arrival\u0000estimation performance for different array configurations with improvement in system performance\u0000is desired in a 5G system. A detailed review of the B-MIMO system with its architecture and various\u0000beam selection techniques is presented in this paper. The scope of the work is elaborated by incorporating various existing beamspace precoding and channel estimation methods. The paper also presents various beamspace processing schemes for parameter estimation with a focus on the direction\u0000of arrival estimation performance.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"107 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139387897","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 : 2023-12-14DOI: 10.2174/0122103279252457231018060854
Zahia Bensalah Azizou, Abdelmalek Boudries, M. Amad
The Internet of Things (IoT) has emerged as a significant technology in recent years, wherein each object is equipped with sensors and applications that provide functionality through services. Due to the increasing benefits of heterogeneous objects with constrained resources in high environments, traditional service discovery approaches become impractical for dynamic IoT networks. Therefore, service discovery poses a considerable challenge for the Internet of Things. This paper introduces a novel decentralized discovery algorithm based on the Grey Wolf Optimizer (GWO) for IoT services. GWO is a recent metaheuristic in swarm intelligence designed to solve combinatorial optimization problems. simulation results indicate that GWO achieves high discovery success with minimal steps required for service discovery. Our approach maintains its performance and exhibits good scalability as the number of objects increases in the decentralized approach for IoT.
{"title":"Grey Wolf Optimizer-Based Decentralized Service Discovery in the\u0000Internet of Things Applications","authors":"Zahia Bensalah Azizou, Abdelmalek Boudries, M. Amad","doi":"10.2174/0122103279252457231018060854","DOIUrl":"https://doi.org/10.2174/0122103279252457231018060854","url":null,"abstract":"\u0000\u0000The Internet of Things (IoT) has emerged as a significant technology in recent\u0000years, wherein each object is equipped with sensors and applications that provide functionality\u0000through services. Due to the increasing benefits of heterogeneous objects with constrained resources\u0000in high environments, traditional service discovery approaches become impractical for dynamic IoT\u0000networks. Therefore, service discovery poses a considerable challenge for the Internet of Things.\u0000\u0000\u0000\u0000This paper introduces a novel decentralized discovery algorithm based on the Grey Wolf\u0000Optimizer (GWO) for IoT services. GWO is a recent metaheuristic in swarm intelligence designed to\u0000solve combinatorial optimization problems.\u0000\u0000\u0000\u0000simulation results indicate that GWO achieves high discovery success with minimal steps\u0000required for service discovery.\u0000\u0000\u0000\u0000Our approach maintains its performance and exhibits good scalability as the number of\u0000objects increases in the decentralized approach for IoT.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"19 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139002997","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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