Pub Date : 2024-06-24DOI: 10.1109/OJVT.2024.3418201
Safa Hamdare;David J. Brown;Yue Cao;Mohammad Aljaidi;Omprakash Kaiwartya;Rahul Yadav;Pratik Vyas;Manish Jugran
The widespread adoption of Electric Vehicles (EV) has emphasized the urgent need for efficient and secure charging infrastructure. While existing research in EV charging infrastructure has primarily concentrated on minimizing charging time at charging stations (CSs), neglecting security-centric charging optimization, particularly with scaled charging infrastructure considering multiple CSs. To address this gap, this paper presents an enhanced Hybrid-Electric Vehicle Charging Management and Security (H-EVCMS) framework. The H-EVCMS framework is meticulously designed to optimize charging price, manage load balancing, and provide security across multiple CS by leveraging the Open Charge Point Protocol (OCPP). The proposed framework's performance is evaluated by examining various charging scenarios and analyzing the booking and power consumption patterns of each CS. The results demonstrate the advantages of the hybrid approach used by the proposed H-EVCMS over traditional charging infrastructure management, showcasing its potential to address the challenges of scaling EV charging infrastructure while ensuring security and efficiency.
{"title":"EV Charging Management and Security for Multi-Charging Stations Environment","authors":"Safa Hamdare;David J. Brown;Yue Cao;Mohammad Aljaidi;Omprakash Kaiwartya;Rahul Yadav;Pratik Vyas;Manish Jugran","doi":"10.1109/OJVT.2024.3418201","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3418201","url":null,"abstract":"The widespread adoption of Electric Vehicles (EV) has emphasized the urgent need for efficient and secure charging infrastructure. While existing research in EV charging infrastructure has primarily concentrated on minimizing charging time at charging stations (CSs), neglecting security-centric charging optimization, particularly with scaled charging infrastructure considering multiple CSs. To address this gap, this paper presents an enhanced Hybrid-Electric Vehicle Charging Management and Security (H-EVCMS) framework. The H-EVCMS framework is meticulously designed to optimize charging price, manage load balancing, and provide security across multiple CS by leveraging the Open Charge Point Protocol (OCPP). The proposed framework's performance is evaluated by examining various charging scenarios and analyzing the booking and power consumption patterns of each CS. The results demonstrate the advantages of the hybrid approach used by the proposed H-EVCMS over traditional charging infrastructure management, showcasing its potential to address the challenges of scaling EV charging infrastructure while ensuring security and efficiency.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"807-824"},"PeriodicalIF":5.3,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10569090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141583486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1109/OJVT.2024.3410834
Toluwaleke Olutayo;Benoit Champagne
This article addresses the problem of symbol detection in time-varying Massive Multiple-Input Multiple-Output (M-MIMO) systems. While conventional detection techniques either exhibit subpar performance or impose excessive computational burdens in such systems, learning-based methods which have shown great potential in stationary scenarios, struggle to adapt to non-stationary conditions. To address these challenges, we introduce innovative extensions to the Learned Conjugate Gradient Network (LcgNet) M-MIMO detector. Firstly, we expound Preconditioned LcgNet (PrLcgNet), which incorporates a preconditioner during training to enhance the uplink M-MIMO detector's filter matrix. This modification enables the detector to achieve faster convergence with fewer layers compared to the original approach. Secondly, we introduce an adaptation of PrLcgNet referred to as Dynamic Conjugate Gradient Network (DyCoGNet), specifically designed for time-varying environments. DyCoGNet leverages self-supervised learning with Forward Error Correction (FEC), enabling autonomous adaptation without the need for explicit labeled data. It also employs meta-learning, facilitating rapid adaptation to unforeseen channel conditions. Our simulation results demonstrate that in stationary scenarios, PrLcgNet achieves faster convergence than LCgNet, which can be leveraged to reduce system complexity or improve Symbol Error Rate (SER) performance. Furthermore, in non-stationary scenarios, DyCoGNet exhibits rapid and efficient adaptation, achieving significant SER performance gains compared to baseline cases without meta-learning and a recent benchmark using self-supervised learning.
{"title":"Dynamic Conjugate Gradient Unfolding for Symbol Detection in Time-Varying Massive MIMO","authors":"Toluwaleke Olutayo;Benoit Champagne","doi":"10.1109/OJVT.2024.3410834","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3410834","url":null,"abstract":"This article addresses the problem of symbol detection in time-varying Massive Multiple-Input Multiple-Output (M-MIMO) systems. While conventional detection techniques either exhibit subpar performance or impose excessive computational burdens in such systems, learning-based methods which have shown great potential in stationary scenarios, struggle to adapt to non-stationary conditions. To address these challenges, we introduce innovative extensions to the Learned Conjugate Gradient Network (LcgNet) M-MIMO detector. Firstly, we expound Preconditioned LcgNet (PrLcgNet), which incorporates a preconditioner during training to enhance the uplink M-MIMO detector's filter matrix. This modification enables the detector to achieve faster convergence with fewer layers compared to the original approach. Secondly, we introduce an adaptation of PrLcgNet referred to as Dynamic Conjugate Gradient Network (DyCoGNet), specifically designed for time-varying environments. DyCoGNet leverages self-supervised learning with Forward Error Correction (FEC), enabling autonomous adaptation without the need for explicit labeled data. It also employs meta-learning, facilitating rapid adaptation to unforeseen channel conditions. Our simulation results demonstrate that in stationary scenarios, PrLcgNet achieves faster convergence than LCgNet, which can be leveraged to reduce system complexity or improve Symbol Error Rate (SER) performance. Furthermore, in non-stationary scenarios, DyCoGNet exhibits rapid and efficient adaptation, achieving significant SER performance gains compared to baseline cases without meta-learning and a recent benchmark using self-supervised learning.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"792-806"},"PeriodicalIF":5.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10551475","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141439460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sixth generation (6G) networks must guarantee radio-resource availability for coexisting users and machines. Here, non-orthogonal multiple access (NOMA) can address resource limitations by serving multiple devices on the same spectral and temporal resources. Meanwhile, cooperative relays can mitigate the impact with excessive large- and small-scale fading and interference. Still, to unlock the full potential of NOMA in 6G deployments, its performance must be analyzed under interference-limited scenarios with NOMA communications occuring across multiple cells. In this paper, the detrimental effect of co-channel interference (CCI) from nearby NOMA transmissions on a relay-aided NOMA network is examined. More specifically, randomly deployed CCI terminals communicate using NOMA and degrade the uplink communication. Network performance is thoroughly analyzed for various metrics, considering independent and identically distributed non-orthogonal CCI. Furthermore, for improved performance, transmit power, power allocation, and relay location optimization is presented. This scenario can correspond to Industry 4.0 settings, relying on private networks that can adjust the transmit power of interferers within the network. Our analytical findings are verified through Monte-Carlo simulations, revealing that non-orthogonal CCI degrades the system performance, causing system coding gain losses. Nonetheless, the proposed optimization framework can mitigate the impact of non-orthogonal CCI and ensure improved uplink performance.
第六代（6G）网络必须保证共存用户和机器的无线电资源可用性。在这方面，非正交多址接入（NOMA）可以通过在相同的频谱和时间资源上为多个设备提供服务来解决资源限制问题。同时，合作中继可减轻大、小范围过度衰落和干扰的影响。不过，要在 6G 部署中释放 NOMA 的全部潜力，必须分析其在干扰受限场景下的性能，即 NOMA 通信跨越多个小区。本文研究了来自附近 NOMA 传输的同信道干扰（CCI）对中继辅助 NOMA 网络的不利影响。更具体地说，随机部署的 CCI 终端使用 NOMA 进行通信，会降低上行链路通信性能。考虑到独立且同分布的非正交 CCI，针对各种指标对网络性能进行了全面分析。此外，为了提高性能，还介绍了发射功率、功率分配和中继位置优化。这种情况可以对应工业 4.0 的设置，依赖于可以调整网络内干扰者发射功率的专用网络。通过蒙特卡洛模拟验证了我们的分析结果，发现非正交 CCI 会降低系统性能，造成系统编码增益损失。然而，所提出的优化框架可以减轻非正交 CCI 的影响，确保改善上行链路性能。
{"title":"Relay-Aided Uplink NOMA Under Non-Orthogonal CCI and Imperfect SIC in 6G Networks","authors":"Volkan Özduran;Nikolaos Nomikos;Ehsan Soleimani-Nasab;Imran Shafique Ansari;Panagiotis Trakadas","doi":"10.1109/OJVT.2024.3392951","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3392951","url":null,"abstract":"Sixth generation (6G) networks must guarantee radio-resource availability for coexisting users and machines. Here, non-orthogonal multiple access (NOMA) can address resource limitations by serving multiple devices on the same spectral and temporal resources. Meanwhile, cooperative relays can mitigate the impact with excessive large- and small-scale fading and interference. Still, to unlock the full potential of NOMA in 6G deployments, its performance must be analyzed under interference-limited scenarios with NOMA communications occuring across multiple cells. In this paper, the detrimental effect of co-channel interference (CCI) from nearby NOMA transmissions on a relay-aided NOMA network is examined. More specifically, randomly deployed CCI terminals communicate using NOMA and degrade the uplink communication. Network performance is thoroughly analyzed for various metrics, considering independent and identically distributed non-orthogonal CCI. Furthermore, for improved performance, transmit power, power allocation, and relay location optimization is presented. This scenario can correspond to Industry 4.0 settings, relying on private networks that can adjust the transmit power of interferers within the network. Our analytical findings are verified through Monte-Carlo simulations, revealing that non-orthogonal CCI degrades the system performance, causing system coding gain losses. Nonetheless, the proposed optimization framework can mitigate the impact of non-orthogonal CCI and ensure improved uplink performance.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"658-680"},"PeriodicalIF":6.4,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10508052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140950957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-19DOI: 10.1109/OJVT.2024.3391380
Muhammad Haris;Dost Muhammad Saqib Bhatti;Haewoon Nam
Particle Swarm Optimization (PSO) stands as a cornerstone among population-based swarm intelligence algorithms, serving as a versatile tool to tackle diverse scientific and engineering optimization challenges due to its straightforward implementation and promising optimization capabilities. Nonetheless, PSO has its limitations, notably its propensity for slow convergence. Traditionally, PSO operates by guiding swarms through positions determined by their initial velocities and acceleration components, encompassing cognitive and social information. In pursuit of expedited convergence, we introduce a novel approach: the Cognitive and Social Information-Based Hyperbolic Tangent Particle Swarm Optimization (HT-PSO) algorithm. This innovation draws inspiration from the activation functions employed in neural networks, with the singular aim of accelerating convergence. To combat the issue of slow convergence, we reengineer the cognitive and social acceleration coefficients of the PSO algorithm, leveraging the power of the hyperbolic tangent function. This strategic adjustment fosters a dynamic balance between exploration and exploitation, unleashing PSO's full potential. Our experimental trials encompass thirteen benchmark functions spanning unimodal and multimodal landscapes. Besides that, the proposed algorithm is also applied to different UAV path planning scenarios, underscoring its real-world relevance. The outcomes underscore the prowess of HT-PSO, showcasing significantly better convergence rates compared to the state-of-the-art.
{"title":"A Fast-Convergent Hyperbolic Tangent PSO Algorithm for UAVs Path Planning","authors":"Muhammad Haris;Dost Muhammad Saqib Bhatti;Haewoon Nam","doi":"10.1109/OJVT.2024.3391380","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3391380","url":null,"abstract":"Particle Swarm Optimization (PSO) stands as a cornerstone among population-based swarm intelligence algorithms, serving as a versatile tool to tackle diverse scientific and engineering optimization challenges due to its straightforward implementation and promising optimization capabilities. Nonetheless, PSO has its limitations, notably its propensity for slow convergence. Traditionally, PSO operates by guiding swarms through positions determined by their initial velocities and acceleration components, encompassing cognitive and social information. In pursuit of expedited convergence, we introduce a novel approach: the Cognitive and Social Information-Based Hyperbolic Tangent Particle Swarm Optimization (HT-PSO) algorithm. This innovation draws inspiration from the activation functions employed in neural networks, with the singular aim of accelerating convergence. To combat the issue of slow convergence, we reengineer the cognitive and social acceleration coefficients of the PSO algorithm, leveraging the power of the hyperbolic tangent function. This strategic adjustment fosters a dynamic balance between exploration and exploitation, unleashing PSO's full potential. Our experimental trials encompass thirteen benchmark functions spanning unimodal and multimodal landscapes. Besides that, the proposed algorithm is also applied to different UAV path planning scenarios, underscoring its real-world relevance. The outcomes underscore the prowess of HT-PSO, showcasing significantly better convergence rates compared to the state-of-the-art.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"681-694"},"PeriodicalIF":6.4,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10505768","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141096361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.1109/OJVT.2024.3390833
Constantinos M. Mylonakis;Zaharias D. Zaharis
This article aims to constitute a noteworthy contribution to the domain of direction-of-arrival (DoA) estimation through the application of deep learning algorithms. We approach the DoA estimation challenge as a binary classification task, employing a novel grid in the output layer and a deep convolutional neural network (DCNN) as the classifier. The input of the DCNN is the correlation matrix of signals received by a $4 times 4$ uniformly spaced patch antenna array. The proposed model's performance is evaluated based on its capacity to predict angles of arrival from any direction in a three-dimensional space, encompassing azimuth angles within the interval $[0^circ, 360^circ)$ and polar angles within $[0^circ, 60^circ ]$ . We aim to optimize the utilization of spatial information and create a robust, precise, and efficient DoA estimator. To address this, we conduct comprehensive testing in diverse scenarios, encompassing the simultaneous reception of multiple signals across a wide range of signal-to-noise ratio values. Both mean absolute error and root mean squared error are calculated to assess the performance of the DCNN. Rigorous comparison with conventional and state-of-the-art endeavors emphasizes the proposed model's efficacy.
{"title":"A Novel Three-Dimensional Direction-of-Arrival Estimation Approach Using a Deep Convolutional Neural Network","authors":"Constantinos M. Mylonakis;Zaharias D. Zaharis","doi":"10.1109/OJVT.2024.3390833","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3390833","url":null,"abstract":"This article aims to constitute a noteworthy contribution to the domain of direction-of-arrival (DoA) estimation through the application of deep learning algorithms. We approach the DoA estimation challenge as a binary classification task, employing a novel grid in the output layer and a deep convolutional neural network (DCNN) as the classifier. The input of the DCNN is the correlation matrix of signals received by a \u0000<inline-formula><tex-math>$4 times 4$</tex-math></inline-formula>\u0000 uniformly spaced patch antenna array. The proposed model's performance is evaluated based on its capacity to predict angles of arrival from any direction in a three-dimensional space, encompassing azimuth angles within the interval \u0000<inline-formula><tex-math>$[0^circ, 360^circ)$</tex-math></inline-formula>\u0000 and polar angles within \u0000<inline-formula><tex-math>$[0^circ, 60^circ ]$</tex-math></inline-formula>\u0000. We aim to optimize the utilization of spatial information and create a robust, precise, and efficient DoA estimator. To address this, we conduct comprehensive testing in diverse scenarios, encompassing the simultaneous reception of multiple signals across a wide range of signal-to-noise ratio values. Both mean absolute error and root mean squared error are calculated to assess the performance of the DCNN. Rigorous comparison with conventional and state-of-the-art endeavors emphasizes the proposed model's efficacy.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"643-657"},"PeriodicalIF":6.4,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10504989","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140906933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-17DOI: 10.1109/OJVT.2024.3390204
João Madeira;Zahra Mokhtari;João Guerreiro;Rui Dinis
Is is widely known that the power consumption of Analog-to-Digital Converters (ADCs) is strongly related with the number of bits of resolution. Using smaller resolutions can greatly reduce the power consumption of the RX frontend. However, the use of low-resolution ADCs introduces significant nonlinear distortion, especially when Orthogonal Frequency Division Multiplexing (OFDM) signals are employed, which might severely degrade performance. In this work, we consider nonlinear effects at the receiver side, associated with quantization and saturation of low-resolution ADCs, and we propose a Generalized Approximate Message Passing (GAMP) receiver that is specially designed to cope with nonlinear effects at the OFDM receiver. We show that our receiver can significantly mitigate the distortion that arises from low-resolution ADCs, allowing larger M-ary Quadrature Amplitude Modulation (M-QAM) constellations to be employed. The proposed receiver is shown to be robust to strong channel fading effects, as well as errors during the channel estimation process.
{"title":"Receiver Design for OFDM Schemes With Low-Resolution ADCs","authors":"João Madeira;Zahra Mokhtari;João Guerreiro;Rui Dinis","doi":"10.1109/OJVT.2024.3390204","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3390204","url":null,"abstract":"Is is widely known that the power consumption of Analog-to-Digital Converters (ADCs) is strongly related with the number of bits of resolution. Using smaller resolutions can greatly reduce the power consumption of the RX frontend. However, the use of low-resolution ADCs introduces significant nonlinear distortion, especially when Orthogonal Frequency Division Multiplexing (OFDM) signals are employed, which might severely degrade performance. In this work, we consider nonlinear effects at the receiver side, associated with quantization and saturation of low-resolution ADCs, and we propose a Generalized Approximate Message Passing (GAMP) receiver that is specially designed to cope with nonlinear effects at the OFDM receiver. We show that our receiver can significantly mitigate the distortion that arises from low-resolution ADCs, allowing larger M-ary Quadrature Amplitude Modulation (M-QAM) constellations to be employed. The proposed receiver is shown to be robust to strong channel fading effects, as well as errors during the channel estimation process.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"632-642"},"PeriodicalIF":6.4,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10504423","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140818773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-12DOI: 10.1109/OJVT.2024.3387414
Oumaima Barhoumi;Mohamed H. Zaki;Sofiéné Tahar
Traffic conflict techniques enable a comprehensive assessment of traffic safety analysis. Formal methods allow the identification of factors that contribute to traffic safety issues and provide evidence of potential safety degradation. As such, formal methods provide a novel way to model traffic rules and verify road users' compliance. The paper proposes formalizing a traffic safety rule in differential dynamic logic and using KeYmaera theorem prover for verification. This rule considers time-to-collision (TTC), space headway (SHW), and shockwave speed (SWV). To validate the effectiveness of this rule in realistic traffic scenarios, we conducted a study using calibrated microsimulation data from the SR528 highway in Orlando, Florida. Our analysis examined the TTC, SHW, and SWV values for vehicle platoons on the highway and demonstrated how smaller TTC and SHW values indicate shockwaves and subsequent conflicts. Furthermore, we observed that shockwave speed could contribute to traffic conflicts by enabling evasive actions such as sudden braking or lane changes as the risk of collisions increases. By highlighting these findings, we aim to provide valuable insights into the real-world applicability of formal methods for traffic safety and their potential in promoting safer driving practices that can help create reliable autonomous vehicle control systems.
{"title":"A Formal Approach to Road Safety Assessment Using Traffic Conflict Techniques","authors":"Oumaima Barhoumi;Mohamed H. Zaki;Sofiéné Tahar","doi":"10.1109/OJVT.2024.3387414","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3387414","url":null,"abstract":"Traffic conflict techniques enable a comprehensive assessment of traffic safety analysis. Formal methods allow the identification of factors that contribute to traffic safety issues and provide evidence of potential safety degradation. As such, formal methods provide a novel way to model traffic rules and verify road users' compliance. The paper proposes formalizing a traffic safety rule in differential dynamic logic and using KeYmaera theorem prover for verification. This rule considers time-to-collision (TTC), space headway (SHW), and shockwave speed (SWV). To validate the effectiveness of this rule in realistic traffic scenarios, we conducted a study using calibrated microsimulation data from the SR528 highway in Orlando, Florida. Our analysis examined the TTC, SHW, and SWV values for vehicle platoons on the highway and demonstrated how smaller TTC and SHW values indicate shockwaves and subsequent conflicts. Furthermore, we observed that shockwave speed could contribute to traffic conflicts by enabling evasive actions such as sudden braking or lane changes as the risk of collisions increases. By highlighting these findings, we aim to provide valuable insights into the real-world applicability of formal methods for traffic safety and their potential in promoting safer driving practices that can help create reliable autonomous vehicle control systems.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"606-619"},"PeriodicalIF":6.4,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496854","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-08DOI: 10.1109/OJVT.2024.3386064
Zhengying Lou;Ruibo Wang;Baha Eddine Youcef Belmekki;Mustafa A. Kishk;Mohamed-Slim Alouini
Terrain information is a crucial factor affecting the performance of unmanned aerial vehicle (UAV) networks. As a tutorial, this article provides a unique perspective on the completeness of terrain information, summarizing and enhancing the research on terrain-based UAV deployment. In the presence of complete terrain information, two highly discussed topics are UAV-aided map construction and dynamic trajectory design based on maps. We propose a case study illustrating the mutually reinforcing relationship between them. When terrain information is incomplete, and only terrain-related feature parameters are available, we discuss how existing models map terrain features to blockage probabilities. By introducing the application of this model with stochastic geometry, a case study is proposed to analyze the accuracy of the model. When no terrain information is available, UAVs gather terrain information during the real-time networking process and determine the next position by collected information. This real-time search method is currently limited to relay communication. In the case study, we extend it to a multi-user scenario and summarize three trade-offs of the method. Finally, we conduct a qualitative analysis to assess the impact of three factors that have been overlooked in terrain-based UAV deployment.
{"title":"Exploring UAV Networking From the Terrain Information Completeness Perspective: A Tutorial","authors":"Zhengying Lou;Ruibo Wang;Baha Eddine Youcef Belmekki;Mustafa A. Kishk;Mohamed-Slim Alouini","doi":"10.1109/OJVT.2024.3386064","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3386064","url":null,"abstract":"Terrain information is a crucial factor affecting the performance of unmanned aerial vehicle (UAV) networks. As a tutorial, this article provides a unique perspective on the completeness of terrain information, summarizing and enhancing the research on terrain-based UAV deployment. In the presence of complete terrain information, two highly discussed topics are UAV-aided map construction and dynamic trajectory design based on maps. We propose a case study illustrating the mutually reinforcing relationship between them. When terrain information is incomplete, and only terrain-related feature parameters are available, we discuss how existing models map terrain features to blockage probabilities. By introducing the application of this model with stochastic geometry, a case study is proposed to analyze the accuracy of the model. When no terrain information is available, UAVs gather terrain information during the real-time networking process and determine the next position by collected information. This real-time search method is currently limited to relay communication. In the case study, we extend it to a multi-user scenario and summarize three trade-offs of the method. Finally, we conduct a qualitative analysis to assess the impact of three factors that have been overlooked in terrain-based UAV deployment.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"620-631"},"PeriodicalIF":6.4,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10494362","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-02DOI: 10.1109/OJVT.2024.3384102
Ahmed M. Benaya;Mohamed S. Hassan;Mahmoud H. Ismail;Taha Landolsi
With the extensive deployment of Internet-of-Things (IoT) in next generation wireless systems, the problems of energy efficiency and battery life become exacerbated, highlighting the pressing need for innovative solutions. Symbiotic radio (SR) is considered one of the emerging technologies that aims at providing an energy-efficient solution for the ubiquitous IoT applications. In this paper, we propose an SR system that is assisted with a double-faced active intelligent reflecting surface (DFA-IRS). The proposed system consists of an active transmitter (AT), an active receiver (AR), a backscatter receiver (BR), a DFA-IRS, and an IoT device that is connected to the DFA-IRS. We formulated a BR spectral efficiency maximization problem via optimizing the active beamforming vector at the AT, the power amplification factors of the IRS active elements, and the IRS phase shift at each active element under the constraints of a maximum power budget and the AR spectral efficiency requirements. The formulated problem is non-convex due to the coupling between different variables. Hence, we divided the main problems into three sub-problems and utilized the successive convex approximation (SCA) and the semidefinite relaxation (SDR) techniques to obtain a convex equivalent problem that can be solved using conventional optimization tools such as CVX. Simulation results show that the proposed algorithm converges in few number of iterations. Moreover, the proposed scheme achieves better BR spectral efficiency when compared to the case where a single-faced active IRS or a simultaneously transmitting and reflecting IRS (STAR-IRS) counterpart is used.
随着下一代无线系统中物联网（IoT）的广泛部署，能效和电池寿命问题变得更加严重，这凸显了对创新解决方案的迫切需求。共生无线电（SR）被认为是新兴技术之一，旨在为无处不在的物联网应用提供节能解决方案。在本文中，我们提出了一种由双面有源智能反射面（DFA-IRS）辅助的 SR 系统。该系统由主动发射器（AT）、主动接收器（AR）、反向散射接收器（BR）、DFA-IRS 和连接到 DFA-IRS 的物联网设备组成。我们通过优化 AT 的有源波束成形向量、IRS 有源元件的功率放大系数以及每个有源元件的 IRS 相移，在最大功率预算和 AR 频谱效率要求的约束下，提出了一个 BR 频谱效率最大化问题。由于不同变量之间的耦合，所提出的问题是非凸的。因此，我们将主要问题划分为三个子问题，并利用连续凸近似（SCA）和半定量松弛（SDR）技术获得凸等效问题，该问题可使用 CVX 等传统优化工具求解。仿真结果表明，所提出的算法在较少的迭代次数内就能收敛。此外，与使用单面有源 IRS 或同时发射和反射 IRS（STAR-IRS）的情况相比，拟议方案实现了更好的 BR 频谱效率。
{"title":"Double-Faced Active Intelligent Reflecting Surfaces-Assisted Symbiotic Radio Communications","authors":"Ahmed M. Benaya;Mohamed S. Hassan;Mahmoud H. Ismail;Taha Landolsi","doi":"10.1109/OJVT.2024.3384102","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3384102","url":null,"abstract":"With the extensive deployment of Internet-of-Things (IoT) in next generation wireless systems, the problems of energy efficiency and battery life become exacerbated, highlighting the pressing need for innovative solutions. Symbiotic radio (SR) is considered one of the emerging technologies that aims at providing an energy-efficient solution for the ubiquitous IoT applications. In this paper, we propose an SR system that is assisted with a double-faced active intelligent reflecting surface (DFA-IRS). The proposed system consists of an active transmitter (AT), an active receiver (AR), a backscatter receiver (BR), a DFA-IRS, and an IoT device that is connected to the DFA-IRS. We formulated a BR spectral efficiency maximization problem via optimizing the active beamforming vector at the AT, the power amplification factors of the IRS active elements, and the IRS phase shift at each active element under the constraints of a maximum power budget and the AR spectral efficiency requirements. The formulated problem is non-convex due to the coupling between different variables. Hence, we divided the main problems into three sub-problems and utilized the successive convex approximation (SCA) and the semidefinite relaxation (SDR) techniques to obtain a convex equivalent problem that can be solved using conventional optimization tools such as CVX. Simulation results show that the proposed algorithm converges in few number of iterations. Moreover, the proposed scheme achieves better BR spectral efficiency when compared to the case where a single-faced active IRS or a simultaneously transmitting and reflecting IRS (STAR-IRS) counterpart is used.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"577-591"},"PeriodicalIF":6.4,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10487865","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140633556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, a simplified type-2 (ST2) radial basis function (RBF) based neuroadaptive technique for controlling an automotive electric power steering (AEPS) system is designed. The dynamics of the AEPS are assumed to be unknown and the system is subjected to certain disturbances. A ST2-RBF system is proposed for approximating the unknown nonlinear functions. The ST2-RBF parameters are tuned online based on the adaptation laws obtained via Lyapunov stability analysis. A robust observer is also used in this process. The effects of uncertainties as well as approximation and estimation errors are compensated by means of an adaptive component. The parameters of the robust observer-based neuroadaptive ST2-RBF network are optimally determined by applying the Coronavirus disease optimization algorithm (COVIDOA), which mimics the replication mechanism of Coronaviruses taking over the human cells. The results indicate that the COVIDOA can reduce the cost function for neuroadaptive ST2-RBF controller compared to other strategies. Comparison of numerical results is presented to show the efficacy of the suggested technique. Interestingly, based on implementation results, the designed methodology is able to control the AEPS system successfully.
{"title":"Automotive Electric Power Steering Control With Robust Observer Based Neuroadaptive Type-2 Radial Basis Function Methodology","authors":"Abdollah Amirkhani;Masoud Shirzadeh;Jamshid Heydari","doi":"10.1109/OJVT.2024.3383516","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3383516","url":null,"abstract":"In this article, a simplified type-2 (ST2) radial basis function (RBF) based neuroadaptive technique for controlling an automotive electric power steering (AEPS) system is designed. The dynamics of the AEPS are assumed to be unknown and the system is subjected to certain disturbances. A ST2-RBF system is proposed for approximating the unknown nonlinear functions. The ST2-RBF parameters are tuned online based on the adaptation laws obtained via Lyapunov stability analysis. A robust observer is also used in this process. The effects of uncertainties as well as approximation and estimation errors are compensated by means of an adaptive component. The parameters of the robust observer-based neuroadaptive ST2-RBF network are optimally determined by applying the Coronavirus disease optimization algorithm (COVIDOA), which mimics the replication mechanism of Coronaviruses taking over the human cells. The results indicate that the COVIDOA can reduce the cost function for neuroadaptive ST2-RBF controller compared to other strategies. Comparison of numerical results is presented to show the efficacy of the suggested technique. Interestingly, based on implementation results, the designed methodology is able to control the AEPS system successfully.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"592-605"},"PeriodicalIF":6.4,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10487011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140633569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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