Pub Date : 2024-10-09DOI: 10.1109/OJVT.2024.3477937
Emmanouel T. Michailidis;Konstantinos Maliatsos;Demosthenes Vouyioukas
During the last few years, Unmanned Aerial Vehicles (UAVs) have increasingly become primary components of various critical civilian and military applications. As technology rapidly evolves, particularly in the realm of Software-Defined Radio (SDR) and Field-Programmable Gate Arrays (FPGAs), advanced communication protocols and signal processing methods are expected to emerge within UAV-based systems. Crucially, UAVs are expected to capitalize on SDR to enhance communication, sensing, data processing, and defense mechanisms. With this perspective in mind, this paper provides a comprehensive up-to-date review of the integration of SDR technology in UAV-based systems, encompassing the latest techniques, methodologies, and challenges. Specifically, this paper examines case studies and real-world implementations of SDR-assisted UAV-based systems across various domains, including communication, security, detection, classification, and localization, elucidating their efficacy, constraints, and areas for potential improvement. Through this review, valuable insights are offered to researchers, engineers, and practitioners interested in harnessing the synergies between SDR and UAV technologies to address the evolving requirements of contemporary applications and pave the path for future innovations in the field.
{"title":"Software-Defined Radio Deployments in UAV-Driven Applications: A Comprehensive Review","authors":"Emmanouel T. Michailidis;Konstantinos Maliatsos;Demosthenes Vouyioukas","doi":"10.1109/OJVT.2024.3477937","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3477937","url":null,"abstract":"During the last few years, Unmanned Aerial Vehicles (UAVs) have increasingly become primary components of various critical civilian and military applications. As technology rapidly evolves, particularly in the realm of Software-Defined Radio (SDR) and Field-Programmable Gate Arrays (FPGAs), advanced communication protocols and signal processing methods are expected to emerge within UAV-based systems. Crucially, UAVs are expected to capitalize on SDR to enhance communication, sensing, data processing, and defense mechanisms. With this perspective in mind, this paper provides a comprehensive up-to-date review of the integration of SDR technology in UAV-based systems, encompassing the latest techniques, methodologies, and challenges. Specifically, this paper examines case studies and real-world implementations of SDR-assisted UAV-based systems across various domains, including communication, security, detection, classification, and localization, elucidating their efficacy, constraints, and areas for potential improvement. Through this review, valuable insights are offered to researchers, engineers, and practitioners interested in harnessing the synergies between SDR and UAV technologies to address the evolving requirements of contemporary applications and pave the path for future innovations in the field.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1545-1586"},"PeriodicalIF":5.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10713191","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524213","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 : 2024-10-04DOI: 10.1109/OJVT.2024.3474518
H. Horler;B. Rastegari;S. X. Ng
In this work, a novel power auctioneers network is proposed to allow the sharing of resources from Edge Users in exchange for performance gains using either the Cooperative Non-Orthogonal Multiple Access (C-NOMA) or Half-Duplex Successive Relaying based C-NOMA protocol. The latter is presented as a novel method of using two relays in C-NOMA through successive relaying to overcome the multiplexing loss in traditional C-NOMA of the far user. This system exploits two matching-based algorithms based on game theory, namely Conventional Distributed Algorithm (CDA) and Pragmatic Distributed Algorithm (PDA), to handle the challenge of user pairing and power allocation in multi-carrier networks. These approaches use distributed methods to perform tasks on user devices to remove the strain on the base station's resources. Monte Carlo simulations demonstrate that the addition of these games to a wireless network provides a significant performance gain compared to traditional orthogonal multiple access methods, unoptimised C-NOMA, and the Distributed Matching Algorithm. Specifically, the cooperative game of PDA is shown to perform better in several scenarios, including when the subcarrier assignment was fixed and when EUs could occupy multiple subcarriers to enhance their throughput.
{"title":"Game Theoretical Approaches for Optimizing Multi-Carrier Half-Duplex Successive Relaying Based Cooperative NOMA","authors":"H. Horler;B. Rastegari;S. X. Ng","doi":"10.1109/OJVT.2024.3474518","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3474518","url":null,"abstract":"In this work, a novel power auctioneers network is proposed to allow the sharing of resources from Edge Users in exchange for performance gains using either the Cooperative Non-Orthogonal Multiple Access (C-NOMA) or Half-Duplex Successive Relaying based C-NOMA protocol. The latter is presented as a novel method of using two relays in C-NOMA through successive relaying to overcome the multiplexing loss in traditional C-NOMA of the far user. This system exploits two matching-based algorithms based on game theory, namely Conventional Distributed Algorithm (CDA) and Pragmatic Distributed Algorithm (PDA), to handle the challenge of user pairing and power allocation in multi-carrier networks. These approaches use distributed methods to perform tasks on user devices to remove the strain on the base station's resources. Monte Carlo simulations demonstrate that the addition of these games to a wireless network provides a significant performance gain compared to traditional orthogonal multiple access methods, unoptimised C-NOMA, and the Distributed Matching Algorithm. Specifically, the cooperative game of PDA is shown to perform better in several scenarios, including when the subcarrier assignment was fixed and when EUs could occupy multiple subcarriers to enhance their throughput.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1663-1679"},"PeriodicalIF":5.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705068","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636284","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 : 2024-10-03DOI: 10.1109/OJVT.2024.3474426
I. Safak Bayram;Xiang Shi
In light of governmental policies phasing out petrol/diesel car sales, the vehicle retail sector is transforming to focus solely on electric vehicles (EVs). Given their available physical space and access to a high volume of EVs, future vehicle retailers are ideally positioned to operate as bidirectional charging hubs. This paper explores the challenges and opportunities this presents for EV retailers. Current EV battery technology is examined, including degradation mechanisms associated with grid-to-vehicle and vehicle-to-everything applications. Next, bidirectional chargers and relevant industry protocols are analyzed in detail. The U.K. energy market's ancillary services are also investigated, with a focus on the specific performance requirements of different market types. Leveraging publicly available datasets from six mainstream EV models, the suitability of various EV fleets for each market is assessed. Finally, recent V2G projects are analyzed, and the broader societal implications of bidirectional charging hubs are discussed.
{"title":"Bidirectional Charging Hubs in the Electric Vehicle Retail Landscape: Opportunities and Challenges for the U.K. Case","authors":"I. Safak Bayram;Xiang Shi","doi":"10.1109/OJVT.2024.3474426","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3474426","url":null,"abstract":"In light of governmental policies phasing out petrol/diesel car sales, the vehicle retail sector is transforming to focus solely on electric vehicles (EVs). Given their available physical space and access to a high volume of EVs, future vehicle retailers are ideally positioned to operate as bidirectional charging hubs. This paper explores the challenges and opportunities this presents for EV retailers. Current EV battery technology is examined, including degradation mechanisms associated with grid-to-vehicle and vehicle-to-everything applications. Next, bidirectional chargers and relevant industry protocols are analyzed in detail. The U.K. energy market's ancillary services are also investigated, with a focus on the specific performance requirements of different market types. Leveraging publicly available datasets from six mainstream EV models, the suitability of various EV fleets for each market is assessed. Finally, recent V2G projects are analyzed, and the broader societal implications of bidirectional charging hubs are discussed.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1470-1495"},"PeriodicalIF":5.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452771","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}
This paper introduces a preamble arbitration rule and interference suppression (PARIS) method for ultra-wideband (UWB) in-vehicle networks. Advancements in the automotive technology have led to increased reliance on wire harnesses, resulting in higher costs, electronic integration challenges, and adverse environmental effects. To address these problems, we explored the use of UWB wireless networks, which are characterized by low transmission power and superior signal penetration capabilities. A significant challenge associated with implementing UWB in automotive environments is the increased frame error rate (FER) caused by UWB interference. Our experiments indicate that vehicles equipped with identical UWB networks exhibit an FER of approximately 6% when positioned closely. This level of FER is problematic for automotive applications, where reliable communication is paramount. To mitigate this problem, we developed an PARIS communication algorithm that is robust against interference. As identified in this study, PARIS leverages two key characteristics of UWB. First, it prioritizes the timing of signal reception over radio signal power, enhancing interference suppression by activating the receiver at the optimal moment before the desired frame arrives, thereby minimizing data loss. Second, the algorithm exploits the hierarchical nature of preamble codes in simultaneously received frames, reducing data loss rate to the order of $10^{-5}$ by prioritizing frames from critical communication devices based on the preamble code hierarchy. Implementing the UWB-based PARIS method in wireless vehicle networks can reduce the weight of the wire harnesses by approximately 20%, offering a promising solution to the challenges posed by traditional wiring systems.
本文介绍了一种用于超宽带（UWB）车载网络的前导码仲裁规则和干扰抑制（PARIS）方法。汽车技术的进步使人们越来越依赖线束，导致成本上升、电子集成难题和不利的环境影响。为了解决这些问题，我们探索使用 UWB 无线网络，其特点是传输功率低、信号穿透能力强。在汽车环境中实施 UWB 的一个重大挑战是 UWB 干扰导致的帧误码率（FER）增加。我们的实验表明，配备相同 UWB 网络的车辆在紧密定位时，FER 约为 6%。对于通信可靠性至关重要的汽车应用来说，这种水平的 FER 是个问题。为了缓解这一问题，我们开发了一种具有抗干扰能力的 PARIS 通信算法。正如本研究中所确定的，PARIS 利用了 UWB 的两个关键特性。首先，它优先考虑信号接收时间而不是无线电信号功率，通过在所需帧到达前的最佳时机启动接收器来增强干扰抑制能力，从而最大限度地减少数据丢失。其次，该算法利用了同时接收的帧中前导码的层次性，通过根据前导码层次对来自关键通信设备的帧进行优先级排序，将数据丢失率降低到 10^{-5}$ 的数量级。在无线车载网络中实施基于 UWB 的 PARIS 方法，可将线束重量减轻约 20%，为应对传统布线系统带来的挑战提供了一个前景广阔的解决方案。
{"title":"Preamble Arbitration Rule and Interference Suppression-Based Polling Medium Access Control for In-Vehicle Ultra-Wideband Networks","authors":"Makoto Okuhara;Nobuyuki Kurioka;Shigeki Mitoh;Patrick Finnerty;Chikara Ohta","doi":"10.1109/OJVT.2024.3474430","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3474430","url":null,"abstract":"This paper introduces a preamble arbitration rule and interference suppression (PARIS) method for ultra-wideband (UWB) in-vehicle networks. Advancements in the automotive technology have led to increased reliance on wire harnesses, resulting in higher costs, electronic integration challenges, and adverse environmental effects. To address these problems, we explored the use of UWB wireless networks, which are characterized by low transmission power and superior signal penetration capabilities. A significant challenge associated with implementing UWB in automotive environments is the increased frame error rate (FER) caused by UWB interference. Our experiments indicate that vehicles equipped with identical UWB networks exhibit an FER of approximately 6% when positioned closely. This level of FER is problematic for automotive applications, where reliable communication is paramount. To mitigate this problem, we developed an PARIS communication algorithm that is robust against interference. As identified in this study, PARIS leverages two key characteristics of UWB. First, it prioritizes the timing of signal reception over radio signal power, enhancing interference suppression by activating the receiver at the optimal moment before the desired frame arrives, thereby minimizing data loss. Second, the algorithm exploits the hierarchical nature of preamble codes in simultaneously received frames, reducing data loss rate to the order of \u0000<inline-formula><tex-math>$10^{-5}$</tex-math></inline-formula>\u0000 by prioritizing frames from critical communication devices based on the preamble code hierarchy. Implementing the UWB-based PARIS method in wireless vehicle networks can reduce the weight of the wire harnesses by approximately 20%, offering a promising solution to the challenges posed by traditional wiring systems.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1518-1531"},"PeriodicalIF":5.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524212","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 : 2024-09-30DOI: 10.1109/OJVT.2024.3471252
Xianhao Lu;Longjun Wang
With the increasing integration of renewable energy into power grids, ensuring the stability and reliability of power grids has become crucial. The intermittency of renewable energy poses a challenge for the frequency and voltage control of power grids. As an adjustable flexible load, electric vehicles (EVs) have emerged as an important solution for grid frequency and voltage control. A joint control and optimization strategy for electric vehicle aggregators (EVAs) to participate in grid frequency and voltage regulation based on a cloud-edge collaborative hierarchical scheduling architecture is proposed, and a multi-timescale EV charging pile cluster (EVC) scheduling model is established with the goal of maximizing the EVA profit. The strategy and model are grounded in the ancillary service market process. The EVA forecasts and optimizes to declare the active and reactive power capacities of the EVC to the market before the day and hour and controls the EVC to respond quickly and accurately to the frequency and voltage regulation instructions in the real-time stage. The methods of rolling optimization, model predictive control, evaluation of the feasible energy region and real-time capacity correction are adopted to coordinate the active and reactive power of EVC. The feasibility and effectiveness of the strategy are verified by an example, which provides an important reference for EVAs participating in power grid interactions.
随着可再生能源越来越多地并入电网，确保电网的稳定性和可靠性变得至关重要。可再生能源的间歇性给电网的频率和电压控制带来了挑战。作为一种可调节的灵活负载，电动汽车（EV）已成为电网频率和电压控制的重要解决方案。本文提出了一种基于云边协作分层调度架构的电动汽车聚合器（EVA）参与电网频率和电压调节的联合控制和优化策略，并以电动汽车聚合器利润最大化为目标，建立了一个多时间尺度的电动汽车充电桩集群（EVC）调度模型。该策略和模型以辅助服务市场流程为基础。EVA 通过预测和优化，在日、小时前向市场申报 EVC 的有功和无功功率容量，并在实时阶段控制 EVC 快速、准确地响应频率和电压调节指令。采用滚动优化、模型预测控制、可行能量区域评估和实时容量修正等方法来协调 EVC 的有功和无功功率。通过实例验证了该策略的可行性和有效性，为参与电网互动的 EVA 提供了重要参考。
{"title":"Cloud-Edge Collaboration Control Strategy for Electric Vehicle Aggregators Participating in Frequency and Voltage Regulation","authors":"Xianhao Lu;Longjun Wang","doi":"10.1109/OJVT.2024.3471252","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3471252","url":null,"abstract":"With the increasing integration of renewable energy into power grids, ensuring the stability and reliability of power grids has become crucial. The intermittency of renewable energy poses a challenge for the frequency and voltage control of power grids. As an adjustable flexible load, electric vehicles (EVs) have emerged as an important solution for grid frequency and voltage control. A joint control and optimization strategy for electric vehicle aggregators (EVAs) to participate in grid frequency and voltage regulation based on a cloud-edge collaborative hierarchical scheduling architecture is proposed, and a multi-timescale EV charging pile cluster (EVC) scheduling model is established with the goal of maximizing the EVA profit. The strategy and model are grounded in the ancillary service market process. The EVA forecasts and optimizes to declare the active and reactive power capacities of the EVC to the market before the day and hour and controls the EVC to respond quickly and accurately to the frequency and voltage regulation instructions in the real-time stage. The methods of rolling optimization, model predictive control, evaluation of the feasible energy region and real-time capacity correction are adopted to coordinate the active and reactive power of EVC. The feasibility and effectiveness of the strategy are verified by an example, which provides an important reference for EVAs participating in power grid interactions.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1532-1544"},"PeriodicalIF":5.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10700604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524183","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}
An effortless charging experience will boost electric vehicle (xEV) adoption and assure driver satisfaction. Tailoring the charging experience incorporating smart algorithms introduces an exciting set of development opportunities. The goal of a smart charging algorithm is to lay down an accurate estimation of charging power needs for each user. As recommender systems (RS) are frequently used for tailored services and products, a novel RS based approach is developed in this study. Based on a collaborative-filtering principle, an RS agent will customize charging power transient prioritizing the physical principles governing the battery system, correlated to customer preferences. However, parallel to other RS applications, a collaborative-filtering for charging power transient design may suffer from the cold-start problem. This paper thus aims to prescribe a remedy for the cold-start problem encountered in RS specifically for charging power transient design. The RS is cold-started based on multiphysical modelling, combined with customer driving styles. It is shown that using 7 fundamental charging power transients would capture about 70% of a set of representative charging power transient population. Matching a unsupervised learning based clustering pipeline for 7 possible customer driving styles, an RS agent can prescribe 7 charging power transients automatically and cold-start the RS until more data is available.
{"title":"A Physics-Informed Cold-Start Capability for xEV Charging Recommender System","authors":"Raik Orbay;Aditya Pratap Singh;Johannes Emilsson;Michele Becciani;Evelina Wikner;Victor Gustafson;Torbjörn Thiringer","doi":"10.1109/OJVT.2024.3469577","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3469577","url":null,"abstract":"An effortless charging experience will boost electric vehicle (xEV) adoption and assure driver satisfaction. Tailoring the charging experience incorporating smart algorithms introduces an exciting set of development opportunities. The goal of a smart charging algorithm is to lay down an accurate estimation of charging power needs for each user. As recommender systems (RS) are frequently used for tailored services and products, a novel RS based approach is developed in this study. Based on a collaborative-filtering principle, an RS agent will customize charging power transient prioritizing the physical principles governing the battery system, correlated to customer preferences. However, parallel to other RS applications, a collaborative-filtering for charging power transient design may suffer from the cold-start problem. This paper thus aims to prescribe a remedy for the cold-start problem encountered in RS specifically for charging power transient design. The RS is cold-started based on multiphysical modelling, combined with customer driving styles. It is shown that using 7 fundamental charging power transients would capture about 70% of a set of representative charging power transient population. Matching a unsupervised learning based clustering pipeline for 7 possible customer driving styles, an RS agent can prescribe 7 charging power transients automatically and cold-start the RS until more data is available.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1457-1469"},"PeriodicalIF":5.3,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10697286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142450898","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 : 2024-09-25DOI: 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%.
{"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":"5 ","pages":"1441-1456"},"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}
Pub Date : 2024-09-24DOI: 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.
{"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":"5 ","pages":"1400-1440"},"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}
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":"5 ","pages":"1637-1649"},"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}
Pub Date : 2024-09-17DOI: 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.
{"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":"5 ","pages":"1336-1347"},"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}
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