首页 > 最新文献

IEEE Open Journal of Vehicular Technology最新文献

英文 中文
A Verifiable Discrete Trust Model (VDTM) Using Congruent Federated Learning (CFL) for Social Internet of Vehicles 使用同义联合学习(CFL)的可验证离散信任模型(VDTM)用于社交车联网
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-25 DOI: 10.1109/OJVT.2024.3468164
Mohammed Mujib Alshahrani
The Social Internet of Vehicles (SIoV) connects cars that are nearby and uses different types of infrastructure to connect people with shared interests. A public, open tool, such as the cloud, is used to share information about things like tolls, traffic, weather, and more. When people share social information, the risks of data leaks and trustworthiness are still not dealt with. This article presents a Verifiable Discrete Trust Model (VDTM) that uses Congruent Federated Learning (CFL) to make social information-sharing tools more trustworthy. The proposed trust model ensures pre- and post-sharing trust verification of the communicating vehicles. Trust is verified as a global identity factor due to the inconsistency between sharing occasions. The CFL is accountable of checking forward and backward trust between the times before and after sharing. In this learning, the congruency is zero-variance detection on both occasions of information sharing. The learning does this check over and over to make sure there is discrete trust in information-sharing times between vehicles, between vehicles and infrastructure, or between vehicles and platforms. The identified trust is valid within the specific interval broadcasted during request initializations. Depending on the trust level, the sharing interval is authenticated using forward and reverse private keys. Therefore, the vehicle's trust results from the maximum information integrity observed in the pre-and post-sharing interval. For the maximum vehicles considered, the proposed model leverages the trust index by 8%, information sharing by 7.15%, and reducing key overhead by 9.35% and time consumption by 7.76%.
社会车辆互联网(SIoV)将附近的汽车连接起来,并利用不同类型的基础设施将有共同兴趣爱好的人联系起来。云计算等公共开放工具被用来共享收费、交通、天气等信息。当人们分享社交信息时,数据泄露和可信度的风险仍未得到解决。本文提出了一种可验证的离散信任模型(VDTM),该模型采用了同义联合学习(CFL)技术,使社交信息共享工具更加可信。所提出的信任模型可确保对通信工具进行共享前和共享后的信任验证。由于共享场合之间的不一致性,信任是作为全局身份因素进行验证的。CFL 负责检查共享前后的前向和后向信任。在这种学习中,信息共享的两个场合的一致性都是零差异检测。该学习反复进行这种检查,以确保车辆之间、车辆与基础设施之间或车辆与平台之间的信息共享时间存在离散信任。确定的信任在请求初始化期间广播的特定时间间隔内有效。根据信任级别,共享间隔使用正向和反向私钥进行验证。因此,车辆的信任度来自共享前后时间间隔内观察到的最大信息完整性。对于所考虑的最大车辆,所提出的模型利用信任指数提高了 8%,信息共享提高了 7.15%,密钥开销减少了 9.35%,时间消耗减少了 7.76%。
{"title":"A Verifiable Discrete Trust Model (VDTM) Using Congruent Federated Learning (CFL) for Social Internet of Vehicles","authors":"Mohammed Mujib Alshahrani","doi":"10.1109/OJVT.2024.3468164","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3468164","url":null,"abstract":"The Social Internet of Vehicles (SIoV) connects cars that are nearby and uses different types of infrastructure to connect people with shared interests. A public, open tool, such as the cloud, is used to share information about things like tolls, traffic, weather, and more. When people share social information, the risks of data leaks and trustworthiness are still not dealt with. This article presents a Verifiable Discrete Trust Model (VDTM) that uses Congruent Federated Learning (CFL) to make social information-sharing tools more trustworthy. The proposed trust model ensures pre- and post-sharing trust verification of the communicating vehicles. Trust is verified as a global identity factor due to the inconsistency between sharing occasions. The CFL is accountable of checking forward and backward trust between the times before and after sharing. In this learning, the congruency is zero-variance detection on both occasions of information sharing. The learning does this check over and over to make sure there is discrete trust in information-sharing times between vehicles, between vehicles and infrastructure, or between vehicles and platforms. The identified trust is valid within the specific interval broadcasted during request initializations. Depending on the trust level, the sharing interval is authenticated using forward and reverse private keys. Therefore, the vehicle's trust results from the maximum information integrity observed in the pre-and post-sharing interval. For the maximum vehicles considered, the proposed model leverages the trust index by 8%, information sharing by 7.15%, and reducing key overhead by 9.35% and time consumption by 7.76%.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10693441","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442990","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}
引用次数: 0
Federated Reinforcement Learning for Wireless Networks: Fundamentals, Challenges and Future Research Trends 无线网络的联合强化学习:基础、挑战和未来研究趋势
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-24 DOI: 10.1109/OJVT.2024.3466858
Sree Krishna Das;Ratna Mudi;Md. Siddikur Rahman;Khaled M. Rabie;Xingwang Li
The increasing popularity of Internet of Things (IoT)-based wireless services highlights the urgent need to upgrade fifth-generation (5G) wireless networks and beyond to accommodate these services. Although 5G networks currently support a variety of wireless services, they might not fully meet the high computational and communication resource demands of new applications. Issues such as latency, energy consumption, network congestion, signaling overhead, and potential privacy breaches contribute to this limitation. Machine learning (ML) frequently offers solutions to these problems. As a result, sixth-generation (6G) wireless technologies are being developed to address the deficiencies of 5G networks. Traditional ML methods are generally centralized. However, the vast amount of wireless data generated, growing privacy concerns, and the increasing computational capabilities of edge devices have led to a shift towards optimizing system performance in a distributed manner. This paper provides a thorough analysis of distributed learning techniques, including federated learning (FL), multi-agent reinforcement learning (MARL), and the multi-agent federated reinforcement learning (FRL) framework. It explains how these techniques can be effectively and efficiently implemented in wireless networks. These methods offer potential solutions to the challenges faced by current wireless networks, promising to create a more robust, capable, and versatile network that meets the growing demands of IoT and other emerging applications. Implementing the FRL framework can significantly improve the learning efficiency of wireless networks. To tackle the challenges posed by rapidly changing radio channels, we propose a robust FRL framework that enables local users to perform distributed power allocation, bandwidth allocation, interference mitigation, and communication mode selection. Finally, the paper outlines several future research directions aimed at effectively integrating the FRL framework into wireless networks.
基于物联网(IoT)的无线服务日益普及,这凸显了升级第五代(5G)及以后的无线网络以适应这些服务的迫切需要。尽管 5G 网络目前支持各种无线服务,但可能无法完全满足新应用对计算和通信资源的高要求。延迟、能耗、网络拥塞、信令开销和潜在的隐私泄露等问题都是造成这种限制的原因。机器学习(ML)经常为这些问题提供解决方案。因此,目前正在开发第六代(6G)无线技术,以解决 5G 网络的不足。传统的 ML 方法通常是集中式的。然而,由于产生了大量无线数据、对隐私的日益关注以及边缘设备计算能力的不断提高,人们开始转向以分布式方式优化系统性能。本文全面分析了分布式学习技术,包括联合学习(FL)、多代理强化学习(MARL)和多代理联合强化学习(FRL)框架。它解释了如何在无线网络中有效和高效地实施这些技术。这些方法为应对当前无线网络面临的挑战提供了潜在的解决方案,有望创建一个更强大、更有能力、更多才多艺的网络,以满足物联网和其他新兴应用日益增长的需求。实施 FRL 框架可以显著提高无线网络的学习效率。为了应对瞬息万变的无线电信道带来的挑战,我们提出了一种稳健的 FRL 框架,使本地用户能够执行分布式功率分配、带宽分配、干扰缓解和通信模式选择。最后,本文概述了未来的几个研究方向,旨在将 FRL 框架有效地集成到无线网络中。
{"title":"Federated Reinforcement Learning for Wireless Networks: Fundamentals, Challenges and Future Research Trends","authors":"Sree Krishna Das;Ratna Mudi;Md. Siddikur Rahman;Khaled M. Rabie;Xingwang Li","doi":"10.1109/OJVT.2024.3466858","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3466858","url":null,"abstract":"The increasing popularity of Internet of Things (IoT)-based wireless services highlights the urgent need to upgrade fifth-generation (5G) wireless networks and beyond to accommodate these services. Although 5G networks currently support a variety of wireless services, they might not fully meet the high computational and communication resource demands of new applications. Issues such as latency, energy consumption, network congestion, signaling overhead, and potential privacy breaches contribute to this limitation. Machine learning (ML) frequently offers solutions to these problems. As a result, sixth-generation (6G) wireless technologies are being developed to address the deficiencies of 5G networks. Traditional ML methods are generally centralized. However, the vast amount of wireless data generated, growing privacy concerns, and the increasing computational capabilities of edge devices have led to a shift towards optimizing system performance in a distributed manner. This paper provides a thorough analysis of distributed learning techniques, including federated learning (FL), multi-agent reinforcement learning (MARL), and the multi-agent federated reinforcement learning (FRL) framework. It explains how these techniques can be effectively and efficiently implemented in wireless networks. These methods offer potential solutions to the challenges faced by current wireless networks, promising to create a more robust, capable, and versatile network that meets the growing demands of IoT and other emerging applications. Implementing the FRL framework can significantly improve the learning efficiency of wireless networks. To tackle the challenges posed by rapidly changing radio channels, we propose a robust FRL framework that enables local users to perform distributed power allocation, bandwidth allocation, interference mitigation, and communication mode selection. Finally, the paper outlines several future research directions aimed at effectively integrating the FRL framework into wireless networks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10691666","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142450916","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}
引用次数: 0
Software-Defined Radio-Based IEEE 802.15.4 SUN FSK Evaluation Platform for Highly Mobile Environments 适用于高度移动环境的基于软件无线电的 IEEE 802.15.4 SUN FSK 评估平台
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-18 DOI: 10.1109/OJVT.2024.3464349
Jaeseok Lim;Keito Nakura;Shota Mori;Hiroshi Harada
IEEE 802.15.4 smart utility network (SUN) frequency-shift keying (FSK) has attracted considerable attention as a wireless communication standard designed for use in essential applications required by Internet of Things (IoT) systems. However, longer transmission distances in highly mobile environments are required to support various applications in next-generation IoT systems, such as vehicle-to-everything, automated driving, and drone control systems. Although research on wide-area, highly mobile communications has been conducted via computer simulations, an experimental evaluation platform for further research has not been developed. In this study, we developed an experimental evaluation platform for SUN FSK in very high frequency bands. The developed platform comprises a signal generator-based transmitter and a software-defined radio-based receiver. It was proven to be capable of transmitting a power of ≥5 W through a power amplifier and was suitable for laboratory and field experiments. In addition, we developed received signal processing methods, including a packet detection method and a channel estimation method, which were designed to achieve wide-area, highly mobile communication. In laboratory experiments, the packet error rate characteristics required by IEEE 802.15.4 were achieved even at a transmission distance of >10 km at vehicular speeds of several tens of km/h.
IEEE 802.15.4 智能公用事业网络(SUN)频移键控(FSK)作为物联网(IoT)系统所需的基本应用而设计的无线通信标准引起了广泛关注。然而,要支持下一代物联网系统中的各种应用,如车对物、自动驾驶和无人机控制系统,就需要在高度移动的环境中实现更远的传输距离。虽然有关广域高移动通信的研究已通过计算机模拟进行,但用于进一步研究的实验评估平台尚未开发出来。在本研究中,我们开发了一个用于超高频段 SUN FSK 的实验评估平台。开发的平台包括一个基于信号发生器的发射器和一个基于软件定义无线电的接收器。实验证明,该平台能够通过功率放大器发射功率≥5 W 的信号,适用于实验室和现场实验。此外,我们还开发了接收信号处理方法,包括数据包检测方法和信道估计方法,旨在实现广域高移动通信。在实验室实验中,即使在传输距离大于 10 千米、车速为几十千米/小时的情况下,也能达到 IEEE 802.15.4 所要求的数据包错误率特性。
{"title":"Software-Defined Radio-Based IEEE 802.15.4 SUN FSK Evaluation Platform for Highly Mobile Environments","authors":"Jaeseok Lim;Keito Nakura;Shota Mori;Hiroshi Harada","doi":"10.1109/OJVT.2024.3464349","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3464349","url":null,"abstract":"IEEE 802.15.4 smart utility network (SUN) frequency-shift keying (FSK) has attracted considerable attention as a wireless communication standard designed for use in essential applications required by Internet of Things (IoT) systems. However, longer transmission distances in highly mobile environments are required to support various applications in next-generation IoT systems, such as vehicle-to-everything, automated driving, and drone control systems. Although research on wide-area, highly mobile communications has been conducted via computer simulations, an experimental evaluation platform for further research has not been developed. In this study, we developed an experimental evaluation platform for SUN FSK in very high frequency bands. The developed platform comprises a signal generator-based transmitter and a software-defined radio-based receiver. It was proven to be capable of transmitting a power of ≥5 W through a power amplifier and was suitable for laboratory and field experiments. In addition, we developed received signal processing methods, including a packet detection method and a channel estimation method, which were designed to achieve wide-area, highly mobile communication. In laboratory experiments, the packet error rate characteristics required by IEEE 802.15.4 were achieved even at a transmission distance of >10 km at vehicular speeds of several tens of km/h.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684162","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579187","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}
引用次数: 0
A New Physical Layer Security Scheme Based on Adaptive Bit Channel Selection for Polar-Coded OFDM 基于极性编码 OFDM 自适应比特信道选择的新型物理层安全方案
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-17 DOI: 10.1109/OJVT.2024.3462599
Yuki Kuraya;Hideki Ochiai
We propose a new physical layer security scheme for a wiretap channel in polar-coded OFDM-based wireless communication systems. Our approach is based on the adaptive bit channel selection, where the input bit channels of polar code are selected according to the frequency selectivity of the main channel. Specifically, the polar code is constructed by the legitimate receiver based on its observed channel state information (CSI), and the receiver informs the transmitter of the resulting code structure. Since the proposed scheme attempts to improve the block error rate (BLER) performance exclusively for the main channel, it provides a significant performance gain over the wiretap channel, as long as the channel of the eavesdropper is not highly correlated with that of the legitimate receiver. On the assumption that the wiretap channel is uncorrelated with the main channel, simulation results demonstrate that the main channel can achieve significant performance gains over the wiretap channel, even under the worst-case scenario where the selected polar code structure (i.e., a set of the bit channels selected by the legitimate receiver for information transmission) is completely known to the eavesdropper. We also consider the case where the main channel and wiretap channel are correlated and reveal that our approach is effective even in the presence of mild channel correlation. Finally, the effect of the channel estimation error on the resulting BLER is also examined, pointing out the importance of accurate CSI acquisition at the receiver side.
我们针对基于极性编码的 OFDM 无线通信系统中的窃听信道提出了一种新的物理层安全方案。我们的方法基于自适应比特信道选择,即根据主信道的频率选择性来选择极化码的输入比特信道。具体来说,极地编码由合法接收器根据其观测到的信道状态信息(CSI)构建,接收器将生成的编码结构通知发射器。由于所提出的方案只试图改善主信道的块误码率(BLER)性能,因此只要窃听者的信道与合法接收器的信道不是高度相关,该方案就能显著提高窃听信道的性能。在窃听信道与主信道不相关的假设下,仿真结果表明,即使在窃听者完全知道所选极地编码结构(即合法接收器选择用于信息传输的一组比特信道)的最坏情况下,主信道也能比窃听信道获得显著的性能提升。我们还考虑了主信道和窃听信道相关的情况,发现即使存在轻微的信道相关性,我们的方法也是有效的。最后,我们还研究了信道估计误差对结果 BLER 的影响,指出了在接收端准确获取 CSI 的重要性。
{"title":"A New Physical Layer Security Scheme Based on Adaptive Bit Channel Selection for Polar-Coded OFDM","authors":"Yuki Kuraya;Hideki Ochiai","doi":"10.1109/OJVT.2024.3462599","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3462599","url":null,"abstract":"We propose a new physical layer security scheme for a wiretap channel in polar-coded OFDM-based wireless communication systems. Our approach is based on the \u0000<italic>adaptive bit channel selection</i>\u0000, where the input bit channels of polar code are selected according to the frequency selectivity of the main channel. Specifically, the polar code is constructed by the legitimate receiver based on its observed channel state information (CSI), and the receiver informs the transmitter of the resulting code structure. Since the proposed scheme attempts to improve the block error rate (BLER) performance exclusively for the main channel, it provides a significant performance gain over the wiretap channel, as long as the channel of the eavesdropper is not highly correlated with that of the legitimate receiver. On the assumption that the wiretap channel is uncorrelated with the main channel, simulation results demonstrate that the main channel can achieve significant performance gains over the wiretap channel, even under the worst-case scenario where the selected polar code structure (i.e., a set of the bit channels selected by the legitimate receiver for information transmission) is completely known to the eavesdropper. We also consider the case where the main channel and wiretap channel are correlated and reveal that our approach is effective even in the presence of mild channel correlation. Finally, the effect of the channel estimation error on the resulting BLER is also examined, pointing out the importance of accurate CSI acquisition at the receiver side.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681442","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376538","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}
引用次数: 0
Investigating the WSSUS Assumption in 300 GHz Time-Variant Channels in Industrial Environments 研究工业环境中 300 GHz 时变信道中的 WSSUS 假设
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-13 DOI: 10.1109/OJVT.2024.3460979
Varvara V. Elesina;Carla E. Reinhardt;Lennart Thielecke;Tobias Doeker;Thomas Kürner
This paper present an initial approach to the analysis of the stationarity of time-variant channels in industrial environments, focusing on three distinct scenarios: 1) communication between a static access point (AP) and a sensor node (SN) mounted on a moving machine within a comprehensive industrial workspace, 2) communication between two static sensor node (SN) with a moving metal plate object between them, and 3) communication between two static robotic manipulators with a moving obstacle with varying movement speeds between them. The assumptions of the wide-sense stationary (WSS) and uncorrelated scatering (US), fundamental to channel modeling, are examined using local scattering function (LSF) collinearity metrics in both time and frequency domains. In blockage scenarios, where we compared the effects of two different types of obstacles – a metal plate and a robotic arm – the channel behavior can be divided into three distinct regions: fully stationary before and after the blockage, non-stationary during the transition periods, and either conditionally stationary or fully non-stationary during partial or full blockage, respectively. These distinctions were influenced by the type of blockage object and whether the scenario involved non-line-of-sight (NLOS) or obstructed-line-of-sight (OLOS) conditions. Notably, the speed of moving obstacles affects the duration and nature of non-stationary regions, with higher speeds leading to shorter and less distinct transition periods. The US assumption was found to be generally valid in the blockage scenarios but not in the AP scenario.
本文提出了一种分析工业环境中时变信道静止性的初步方法,重点关注三种不同的场景:1) 在一个综合工业工作区内,一个静态接入点(AP)和一个安装在移动机器上的传感器节点(SN)之间的通信;2) 两个静态传感器节点(SN)之间的通信,它们之间有一个移动的金属板物体;3) 两个静态机器人机械手之间的通信,它们之间有一个移动的障碍物,移动速度各不相同。利用时域和频域的局部散射函数(LSF)共线性指标,对信道建模的基本假设--广义静止(WSS)和非相关散射(US)进行了检验。在阻塞情况下,我们比较了金属板和机械臂这两种不同类型障碍物的影响,信道行为可分为三个不同的区域:阻塞前后完全静止、过渡期间非静止、部分或完全阻塞期间分别为有条件静止或完全非静止。这些区别受到障碍物类型以及情景是否涉及非视线(NLOS)或视线受阻(OLOS)条件的影响。值得注意的是,移动障碍物的速度会影响非稳态区域的持续时间和性质,速度越快,过渡时间越短,越不明显。研究发现,US 假设在阻塞情况下基本有效,但在 AP 情况下无效。
{"title":"Investigating the WSSUS Assumption in 300 GHz Time-Variant Channels in Industrial Environments","authors":"Varvara V. Elesina;Carla E. Reinhardt;Lennart Thielecke;Tobias Doeker;Thomas Kürner","doi":"10.1109/OJVT.2024.3460979","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3460979","url":null,"abstract":"This paper present an initial approach to the analysis of the stationarity of time-variant channels in industrial environments, focusing on three distinct scenarios: 1) communication between a static access point (AP) and a sensor node (SN) mounted on a moving machine within a comprehensive industrial workspace, 2) communication between two static sensor node (SN) with a moving metal plate object between them, and 3) communication between two static robotic manipulators with a moving obstacle with varying movement speeds between them. The assumptions of the wide-sense stationary (WSS) and uncorrelated scatering (US), fundamental to channel modeling, are examined using local scattering function (LSF) collinearity metrics in both time and frequency domains. In blockage scenarios, where we compared the effects of two different types of obstacles – a metal plate and a robotic arm – the channel behavior can be divided into three distinct regions: fully stationary before and after the blockage, non-stationary during the transition periods, and either conditionally stationary or fully non-stationary during partial or full blockage, respectively. These distinctions were influenced by the type of blockage object and whether the scenario involved non-line-of-sight (NLOS) or obstructed-line-of-sight (OLOS) conditions. Notably, the speed of moving obstacles affects the duration and nature of non-stationary regions, with higher speeds leading to shorter and less distinct transition periods. The US assumption was found to be generally valid in the blockage scenarios but not in the AP scenario.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10680312","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408735","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}
引用次数: 0
A Comprehensive Survey of Electric Vehicle Charging Demand Forecasting Techniques 电动汽车充电需求预测技术综合调查
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-10 DOI: 10.1109/OJVT.2024.3457499
Mamunur Rashid;Tarek Elfouly;Nan Chen
The transition of the automotive sector to electric vehicles (EVs) necessitates research on charging demand forecasting for optimal station placement and capacity planning. In the literature, extensive studies have been conducted on model-based and probabilistic EV charging demand forecasting schemes. The studies provide a solid research foundation but result in complicated models with limited scalability. Meanwhile, emerging machine learning techniques bring promising prospects, yet exhibit suboptimal performance with insufficient data. Additionally, existing studies often overlook several critical areas such as overcoming data scarcity, security and privacy concerns, managing the inherent stochasticity of demand data, selecting forecasting methods for a specific feature, and developing standardized performance metrics. Considering the impact of the research topic, EV charging demand forecasting demands careful study. In this paper, we present a comprehensive survey of EV charging demand forecasting, focusing on both probabilistic and learning algorithms. First, we introduce the general procedure of EV charging demand forecasting, encompassing data sources, data pre-processing, and the key EV features. We then provide a taxonomy of existing EV charging demand forecasting techniques, followed by a critical analysis and comparative study of state-of-the-art research. Finally, we discuss open issues, which offer useful insights and future direction for various stakeholders.
随着汽车行业向电动汽车(EV)过渡,有必要对充电需求预测进行研究,以优化充电桩布局和容量规划。文献中对基于模型和概率的电动汽车充电需求预测方案进行了大量研究。这些研究提供了坚实的研究基础,但导致模型复杂,可扩展性有限。同时,新兴的机器学习技术前景广阔,但在数据不足的情况下表现不佳。此外,现有研究往往忽略了几个关键领域,如克服数据稀缺、安全和隐私问题,管理需求数据固有的随机性,针对特定特征选择预测方法,以及制定标准化的性能指标。考虑到研究课题的影响,电动汽车充电需求预测需要仔细研究。在本文中,我们对电动汽车充电需求预测进行了全面研究,重点关注概率算法和学习算法。首先,我们介绍了电动汽车充电需求预测的一般流程,包括数据源、数据预处理和电动汽车的关键特征。然后,我们对现有的电动汽车充电需求预测技术进行了分类,并对最新研究成果进行了批判性分析和比较研究。最后,我们讨论了开放性问题,为各利益相关方提供了有用的见解和未来方向。
{"title":"A Comprehensive Survey of Electric Vehicle Charging Demand Forecasting Techniques","authors":"Mamunur Rashid;Tarek Elfouly;Nan Chen","doi":"10.1109/OJVT.2024.3457499","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3457499","url":null,"abstract":"The transition of the automotive sector to electric vehicles (EVs) necessitates research on charging demand forecasting for optimal station placement and capacity planning. In the literature, extensive studies have been conducted on model-based and probabilistic EV charging demand forecasting schemes. The studies provide a solid research foundation but result in complicated models with limited scalability. Meanwhile, emerging machine learning techniques bring promising prospects, yet exhibit suboptimal performance with insufficient data. Additionally, existing studies often overlook several critical areas such as overcoming data scarcity, security and privacy concerns, managing the inherent stochasticity of demand data, selecting forecasting methods for a specific feature, and developing standardized performance metrics. Considering the impact of the research topic, EV charging demand forecasting demands careful study. In this paper, we present a comprehensive survey of EV charging demand forecasting, focusing on both probabilistic and learning algorithms. First, we introduce the general procedure of EV charging demand forecasting, encompassing data sources, data pre-processing, and the key EV features. We then provide a taxonomy of existing EV charging demand forecasting techniques, followed by a critical analysis and comparative study of state-of-the-art research. Finally, we discuss open issues, which offer useful insights and future direction for various stakeholders.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10670452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376539","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}
引用次数: 0
Sliding Mode Control for Robust Path Tracking of Automated Vehicles in Rural Environments 农村环境中自动驾驶汽车鲁棒路径跟踪的滑模控制
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-09 DOI: 10.1109/OJVT.2024.3456035
Jose Matute;Sergio Diaz;Ali Karimoddini
Achieving robust path tracking is essential for efficiently operating autonomous driving systems, particularly in unpredictable environments. This paper introduces a novel path-tracking control methodology utilizing a variable second-order Sliding Mode Control (SMC) approach. The proposed control strategy addresses the challenges posed by uncertainties and disturbances by reconfiguring and expanding the state-space matrix of a kinematic bicycle model guaranteeing Lyapunov stability and convergence of the system. A state prediction is integrated into the developed SMC to mitigate response time delays. Furthermore, the controller integrates adaptive mechanisms to adjust time-varying parameters within the control formulation based on longitudinal velocity, thereby enhancing path-tracking performance and reducing chattering phenomena. The effectiveness of the proposed approach is comprehensively evaluated through simulations and experiments encompassing challenging driving scenarios characterized by high-curvature paths, varying altitudes, and sensor disturbances, typical in rural driving environments. Results demonstrate that disturbances have varying impacts depending on the type of sensor affected. Real-world tests validate these findings, offering practical insights for automated vehicle path-tracking implementation.
实现稳健的路径跟踪对于高效运行自动驾驶系统至关重要,尤其是在不可预测的环境中。本文介绍了一种利用可变二阶滑模控制(SMC)方法的新型路径跟踪控制方法。所提出的控制策略通过重新配置和扩展自行车运动学模型的状态空间矩阵,保证了系统的 Lyapunov 稳定性和收敛性,从而应对了不确定性和干扰带来的挑战。所开发的 SMC 中集成了状态预测功能,以减少响应时间延迟。此外,控制器还集成了自适应机制,可根据纵向速度调整控制公式中的时变参数,从而提高路径跟踪性能并减少颤振现象。通过模拟和实验全面评估了所提方法的有效性,包括具有挑战性的驾驶场景,其特点是高曲率路径、不同海拔高度和传感器干扰(典型的农村驾驶环境)。结果表明,干扰会根据受影响传感器的类型产生不同的影响。实际测试验证了这些发现,为自动驾驶车辆路径跟踪的实施提供了实用的见解。
{"title":"Sliding Mode Control for Robust Path Tracking of Automated Vehicles in Rural Environments","authors":"Jose Matute;Sergio Diaz;Ali Karimoddini","doi":"10.1109/OJVT.2024.3456035","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3456035","url":null,"abstract":"Achieving robust path tracking is essential for efficiently operating autonomous driving systems, particularly in unpredictable environments. This paper introduces a novel path-tracking control methodology utilizing a variable second-order Sliding Mode Control (SMC) approach. The proposed control strategy addresses the challenges posed by uncertainties and disturbances by reconfiguring and expanding the state-space matrix of a kinematic bicycle model guaranteeing Lyapunov stability and convergence of the system. A state prediction is integrated into the developed SMC to mitigate response time delays. Furthermore, the controller integrates adaptive mechanisms to adjust time-varying parameters within the control formulation based on longitudinal velocity, thereby enhancing path-tracking performance and reducing chattering phenomena. The effectiveness of the proposed approach is comprehensively evaluated through simulations and experiments encompassing challenging driving scenarios characterized by high-curvature paths, varying altitudes, and sensor disturbances, typical in rural driving environments. Results demonstrate that disturbances have varying impacts depending on the type of sensor affected. Real-world tests validate these findings, offering practical insights for automated vehicle path-tracking implementation.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10669799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142377112","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}
引用次数: 0
Perturbation-Based Nulling Control Beamforming With Measured Element Radiation Patterns for MU-mMIMO 基于扰动的空心化控制波束成形与用于 MU-mMIMO 的测量元素辐射模式
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-03 DOI: 10.1109/OJVT.2024.3453951
Yuanzhe Gong;Arish Yaseen;Tingrui Zhang;Robert Morawski;Tho Le-Ngoc
A perturbation-based nulling control beamforming (PNCB) scheme is proposed to effectively mitigate multi-user interference (MUI) in multi-user massive multiple-input multiple-output (MU-mMIMO) systems. This is achieved through the precise alignment of deep and wide radiation nulls in the potential interference directions, considering the realistic heterogeneous element radiation patterns (ERPs). Utilizing measured ERPs from an 8 × 8 antenna array prototype, this study conducts a thorough analysis of ERP variations across different positions in the array. The ERP symmetry knowledge is leveraged to enhance the optimization efficiency by reapplying optimized beamforming vectors to symmetric sub-arrays. The proposed PNCB scheme initiates optimization with weights derived from the linearly constrained minimum variance approach, followed by strategic weight perturbations implemented with particle swarm optimization. This process fine-tunes the sub-optimal beamforming vectors to address discrepancies caused by non-uniform ERPs. Illustrative results demonstrate interference suppression levels exceeding 52.4 dB in multi-user scenarios, without significantly affecting the main-lobe radiation patterns. The nulling width control algorithm achieves an average nulling level ranging from −45.3 dB to −57.7 dB across a 6-degree angle span. Further studies delve into the impact of attenuator and phase-shifter quantization on the nulling level, offering insights into performance variations with different hardware configurations. Experimental validation in an anechoic chamber, involving two users with distinct 20 MHz modulation signals, confirms the effectiveness of the proposed PNCB approach, ensuring reliable and efficient communication in MU-mMIMO systems. The results demonstrate an average enhancement of 22.0 dB in the signal-to-interference ratio, effectively reducing the MUI to near the noise floor. The efficacy of the proposed PNCB scheme is further evidenced by the high-quality received constellation diagrams, with enhanced error vector magnitude performance.
本文提出了一种基于扰动的空化控制波束成形(PNCB)方案,以有效缓解多用户大规模多输入多输出(MU-mMIMO)系统中的多用户干扰(MUI)。考虑到现实的异质元素辐射模式 (ERP),该方案通过在潜在干扰方向精确调整深宽辐射空来实现。本研究利用 8 × 8 天线阵列原型测得的 ERP,对阵列中不同位置的 ERP 变化进行了深入分析。利用 ERP 对称性知识,将优化后的波束成形矢量重新应用于对称子阵列,从而提高优化效率。所提出的 PNCB 方案利用线性约束最小方差方法得出的权重启动优化,然后利用粒子群优化实施战略性权重扰动。这一过程对次优波束成形向量进行微调,以解决非均匀 ERP 造成的差异。示例结果表明,在多用户场景下,干扰抑制水平超过 52.4 dB,且不会对主叶辐射模式产生显著影响。消隐宽度控制算法在 6 度角跨度范围内实现了 -45.3 dB 至 -57.7 dB 的平均消隐水平。进一步的研究深入探讨了衰减器和移相器量化对消隐电平的影响,深入探讨了不同硬件配置下的性能变化。在电波暗室中进行的实验验证涉及两个使用不同 20 MHz 调制信号的用户,证实了所提出的 PNCB 方法的有效性,确保了 MU-mMIMO 系统的可靠和高效通信。结果表明,信号干扰比平均提高了 22.0 dB,有效地将 MUI 降低到接近噪声本底。高质量的接收星座图和增强的误差矢量幅度性能进一步证明了所提出的 PNCB 方案的功效。
{"title":"Perturbation-Based Nulling Control Beamforming With Measured Element Radiation Patterns for MU-mMIMO","authors":"Yuanzhe Gong;Arish Yaseen;Tingrui Zhang;Robert Morawski;Tho Le-Ngoc","doi":"10.1109/OJVT.2024.3453951","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3453951","url":null,"abstract":"A perturbation-based nulling control beamforming (PNCB) scheme is proposed to effectively mitigate multi-user interference (MUI) in multi-user massive multiple-input multiple-output (MU-mMIMO) systems. This is achieved through the precise alignment of deep and wide radiation nulls in the potential interference directions, considering the realistic heterogeneous element radiation patterns (ERPs). Utilizing measured ERPs from an 8 × 8 antenna array prototype, this study conducts a thorough analysis of ERP variations across different positions in the array. The ERP symmetry knowledge is leveraged to enhance the optimization efficiency by reapplying optimized beamforming vectors to symmetric sub-arrays. The proposed PNCB scheme initiates optimization with weights derived from the linearly constrained minimum variance approach, followed by strategic weight perturbations implemented with particle swarm optimization. This process fine-tunes the sub-optimal beamforming vectors to address discrepancies caused by non-uniform ERPs. Illustrative results demonstrate interference suppression levels exceeding 52.4 dB in multi-user scenarios, without significantly affecting the main-lobe radiation patterns. The nulling width control algorithm achieves an average nulling level ranging from −45.3 dB to −57.7 dB across a 6-degree angle span. Further studies delve into the impact of attenuator and phase-shifter quantization on the nulling level, offering insights into performance variations with different hardware configurations. Experimental validation in an anechoic chamber, involving two users with distinct 20 MHz modulation signals, confirms the effectiveness of the proposed PNCB approach, ensuring reliable and efficient communication in MU-mMIMO systems. The results demonstrate an average enhancement of 22.0 dB in the signal-to-interference ratio, effectively reducing the MUI to near the noise floor. The efficacy of the proposed PNCB scheme is further evidenced by the high-quality received constellation diagrams, with enhanced error vector magnitude performance.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10663863","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274920","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}
引用次数: 0
Deep Learning Model for CS-Based Signal Recovery for IRS-Assisted Near-Field THz MIMO System 基于 CS 的深度学习模型用于 IRS 辅助近场 THz MIMO 系统的信号恢复
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-08-30 DOI: 10.1109/OJVT.2024.3452412
Vaishali Sharma;Prakhar Keshari;Sanjeev Sharma;Kuntal Deka;Ondrej Krejcar;Vimal Bhatia
Terahertz (THz) communication is a cutting-edge technology for the sixth-generation (6G) networks, offering vast bandwidths and data rates up to terabits per second, significantly advancing vehicular connectivity and services. However, THz signals are impacted by attenuation, path loss, and beam misalignment. Furthermore, the requisite high Nyquist sampling rates for THz systems increase the computational and system complexity of the receiver. A promising solution to navigate these obstacles involves the use of intelligent reflecting surfaces (IRS)-enhanced multiple-input multiple-output (MIMO) technology, which steers THz wave propagation. However, the substantial dimensions associated with IRS and MIMO extend the near-field, particularly at THz frequencies, as indicated by the Rayleigh distance and suffer from beam squint. To reduce system complexity and reduce sampling to sub-Nyquist rate, we propose a novel receiver design for an IRS-assisted near-field MIMO THz system that employs low-complexity compressed sensing. This method introduces an IRS signal-matched (IRSSM) measurement matrix with beam squint for capturing the transmitted signal at a sub-Nyquist rate, taking advantage of the sparsity in the signal and THz channels, and signal recovery using the deep learning (DL) model. Simulation results for symbol error rate (SER) and normalized mean square error (NMSE) performance indicate that the proposed DL-based receiver outperforms conventional recovery algorithms based on orthogonal matching pursuit (OMP) CS-recovery and dictionary-shrinkage estimation (DSE).
太赫兹(THz)通信是第六代(6G)网络的尖端技术,可提供高达每秒太比特的巨大带宽和数据传输速率,极大地推动了车辆连接和服务的发展。然而,太赫兹信号会受到衰减、路径损耗和波束偏差的影响。此外,太赫兹系统所需的高奈奎斯特采样率也增加了接收器的计算和系统复杂性。要克服这些障碍,一个很有前景的解决方案是采用智能反射面(IRS)增强型多输入多输出(MIMO)技术,引导太赫兹波的传播。然而,与 IRS 和 MIMO 相关的巨大尺寸扩展了近场,特别是在太赫兹频率下,如瑞利距离所示,并受到光束斜视的影响。为了降低系统复杂性并将采样率降至奈奎斯特以下,我们提出了一种新颖的接收器设计,用于采用低复杂度压缩传感的 IRS 辅助近场多输入多输出太赫兹系统。该方法引入了带波束斜视的 IRS 信号匹配(IRSSM)测量矩阵,利用信号和太赫兹信道的稀疏性,以亚奈奎斯特速率捕获传输信号,并使用深度学习(DL)模型进行信号恢复。符号错误率(SER)和归一化均方误差(NMSE)性能的仿真结果表明,所提出的基于 DL 的接收器优于基于正交匹配追寻(OMP)CS 恢复和字典缩减估计(DSE)的传统恢复算法。
{"title":"Deep Learning Model for CS-Based Signal Recovery for IRS-Assisted Near-Field THz MIMO System","authors":"Vaishali Sharma;Prakhar Keshari;Sanjeev Sharma;Kuntal Deka;Ondrej Krejcar;Vimal Bhatia","doi":"10.1109/OJVT.2024.3452412","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3452412","url":null,"abstract":"Terahertz (THz) communication is a cutting-edge technology for the sixth-generation (6G) networks, offering vast bandwidths and data rates up to terabits per second, significantly advancing vehicular connectivity and services. However, THz signals are impacted by attenuation, path loss, and beam misalignment. Furthermore, the requisite high Nyquist sampling rates for THz systems increase the computational and system complexity of the receiver. A promising solution to navigate these obstacles involves the use of intelligent reflecting surfaces (IRS)-enhanced multiple-input multiple-output (MIMO) technology, which steers THz wave propagation. However, the substantial dimensions associated with IRS and MIMO extend the near-field, particularly at THz frequencies, as indicated by the Rayleigh distance and suffer from beam squint. To reduce system complexity and reduce sampling to sub-Nyquist rate, we propose a novel receiver design for an IRS-assisted near-field MIMO THz system that employs low-complexity compressed sensing. This method introduces an IRS signal-matched (IRSSM) measurement matrix with beam squint for capturing the transmitted signal at a sub-Nyquist rate, taking advantage of the sparsity in the signal and THz channels, and signal recovery using the deep learning (DL) model. Simulation results for symbol error rate (SER) and normalized mean square error (NMSE) performance indicate that the proposed DL-based receiver outperforms conventional recovery algorithms based on orthogonal matching pursuit (OMP) CS-recovery and dictionary-shrinkage estimation (DSE).","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10660298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376540","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}
引用次数: 0
A Centralized Multi-Agent DRL-Based Trajectory Control Strategy for Unmanned Aerial Vehicle-Enabled Wireless Communications 基于 DRL 的无人机无线通信集中式多代理轨迹控制策略
IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-08-28 DOI: 10.1109/OJVT.2024.3451143
Getaneh Berie Tarekegn;Rong-Terng Juang;Belayneh Abebe Tesfaw;Hsin-Piao Lin;Huan-Chia Hsu;Robel Berie Tarekegn;Li-Chia Tai
Unmanned aerial vehicles (UAVs) are becoming increasingly popular as mobile base stations due to their flexible deployment and low-cost features, particularly for emergency communications, traffic offloading, and terrestrial communications infrastructure failures. This paper presents an autonomous trajectory control method for multiple UAVs equipped with base stations for UAV-enabled wireless communications. The objective of this work is to address the optimization challenge of maximizing both communication coverage and network throughput for ground users. The proposed multi-aerial base station trajectory control (MATC) scheme employs a two-stage learning approach. Initially, we developed a long short-term memory-based link quality estimation model to assess each user's link quality over time. The trajectory of the aerial base stations is then continuously adjusted through a centralized multi-agent deep reinforcement learning algorithm to optimize communication performance. We evaluated our proposed system using real channel measurement data, i.e., amplitude and phase signal information. Notably, the proposed approach operates solely on received signals from users, without requiring knowledge of their specific locations. The proposed MATC strategy achieves 97.41% communication coverage while maintaining satisfactory system throughput performance. Numerical results demonstrate that the proposed method significantly enhances both communication coverage and network throughput in comparison to the base line algorithms.
无人飞行器(UAV)因其部署灵活、成本低廉等特点,正日益成为移动基站的热门选择,特别是在应急通信、流量卸载和地面通信基础设施故障等方面。本文介绍了一种针对配备基站的多架无人机的自主轨迹控制方法,用于支持无人机的无线通信。这项工作的目标是解决通信覆盖范围和地面用户网络吞吐量最大化的优化难题。所提出的多航空基站轨迹控制(MATC)方案采用了两阶段学习法。首先,我们开发了一个基于长短期记忆的链路质量估计模型,以评估每个用户随时间变化的链路质量。然后,通过集中式多代理深度强化学习算法不断调整空中基站的轨迹,以优化通信性能。我们利用真实的信道测量数据,即振幅和相位信号信息,对我们提出的系统进行了评估。值得注意的是,所提出的方法只需接收来自用户的信号即可运行,无需了解用户的具体位置。拟议的 MATC 策略实现了 97.41% 的通信覆盖率,同时保持了令人满意的系统吞吐量性能。数值结果表明,与基础算法相比,所提出的方法显著提高了通信覆盖率和网络吞吐量。
{"title":"A Centralized Multi-Agent DRL-Based Trajectory Control Strategy for Unmanned Aerial Vehicle-Enabled Wireless Communications","authors":"Getaneh Berie Tarekegn;Rong-Terng Juang;Belayneh Abebe Tesfaw;Hsin-Piao Lin;Huan-Chia Hsu;Robel Berie Tarekegn;Li-Chia Tai","doi":"10.1109/OJVT.2024.3451143","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3451143","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are becoming increasingly popular as mobile base stations due to their flexible deployment and low-cost features, particularly for emergency communications, traffic offloading, and terrestrial communications infrastructure failures. This paper presents an autonomous trajectory control method for multiple UAVs equipped with base stations for UAV-enabled wireless communications. The objective of this work is to address the optimization challenge of maximizing both communication coverage and network throughput for ground users. The proposed multi-aerial base station trajectory control (MATC) scheme employs a two-stage learning approach. Initially, we developed a long short-term memory-based link quality estimation model to assess each user's link quality over time. The trajectory of the aerial base stations is then continuously adjusted through a centralized multi-agent deep reinforcement learning algorithm to optimize communication performance. We evaluated our proposed system using real channel measurement data, i.e., amplitude and phase signal information. Notably, the proposed approach operates solely on received signals from users, without requiring knowledge of their specific locations. The proposed MATC strategy achieves 97.41% communication coverage while maintaining satisfactory system throughput performance. Numerical results demonstrate that the proposed method significantly enhances both communication coverage and network throughput in comparison to the base line algorithms.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10654501","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235822","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}
引用次数: 0
期刊
IEEE Open Journal of Vehicular Technology
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1