Despite advancements in perception technology, achieving full autonomy in vehicles remains challenging partly due to limited situational awareness. Even with their sophisticated sensor arrays, autonomous vehicles often struggle to comprehend complex real-world environments due to the challenges associated with occlusion. A possible solution for addressing this limitation lies in the concept of vehicle-to-infrastructure cooperative driving, which enables vehicles to interact with various sensors implemented in the surrounding infrastructure. The infrastructure can share real-time data, such as traffic conditions, road hazards, and weather updates, facilitating safer and more efficient navigation. Within this framework, cooperative sensing is a crucial component, augmenting the onboard sensing capabilities of autonomous vehicles. Cooperative sensing surpasses traditional onboard sensors by leveraging a shared sensor network among vehicles and infrastructure. This approach mitigates challenges posed by occlusion, where objects are obscured from a vehicle's direct view. By pooling information from multiple sources, autonomous vehicles can gain a more comprehensive understanding of their surroundings, leading to enhanced safety and performance on the road. This study addresses a literature gap regarding information flow from real-world scenes to environmental models for cooperative V2I systems. It explores three core concepts essential for understanding the environment: sensing, perception, and mapping. This paper identifies the specific information required from infrastructure nodes, proposes an optimized sensor suite, discusses data processing algorithms, and investigates effective spatial model representations for cooperative sensing. This research informs the reader about the different challenges and opportunities associated with a V2I cooperative sensing system.
{"title":"Infrastructure Assisted Autonomous Driving: Research, Challenges, and Opportunities","authors":"Roshan George;Joseph Clancy;Tim Brophy;Ganesh Sistu;William O'Grady;Sunil Chandra;Fiachra Collins;Darragh Mullins;Edward Jones;Brian Deegan;Martin Glavin","doi":"10.1109/OJVT.2025.3542213","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3542213","url":null,"abstract":"Despite advancements in perception technology, achieving full autonomy in vehicles remains challenging partly due to limited situational awareness. Even with their sophisticated sensor arrays, autonomous vehicles often struggle to comprehend complex real-world environments due to the challenges associated with occlusion. A possible solution for addressing this limitation lies in the concept of vehicle-to-infrastructure cooperative driving, which enables vehicles to interact with various sensors implemented in the surrounding infrastructure. The infrastructure can share real-time data, such as traffic conditions, road hazards, and weather updates, facilitating safer and more efficient navigation. Within this framework, cooperative sensing is a crucial component, augmenting the onboard sensing capabilities of autonomous vehicles. Cooperative sensing surpasses traditional onboard sensors by leveraging a shared sensor network among vehicles and infrastructure. This approach mitigates challenges posed by occlusion, where objects are obscured from a vehicle's direct view. By pooling information from multiple sources, autonomous vehicles can gain a more comprehensive understanding of their surroundings, leading to enhanced safety and performance on the road. This study addresses a literature gap regarding information flow from real-world scenes to environmental models for cooperative V2I systems. It explores three core concepts essential for understanding the environment: sensing, perception, and mapping. This paper identifies the specific information required from infrastructure nodes, proposes an optimized sensor suite, discusses data processing algorithms, and investigates effective spatial model representations for cooperative sensing. This research informs the reader about the different challenges and opportunities associated with a V2I cooperative sensing system.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"662-716"},"PeriodicalIF":5.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10887285","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594293","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 : 2025-02-13DOI: 10.1109/OJVT.2025.3541891
Anam Manzoor;Reenu Mohandas;Anthony Scanlan;Eoin Martino Grua;Fiachra Collins;Ganesh Sistu;Ciarán Eising
Please check and confirm whether the authors affiliation in the first The automotive industry has made significant strides in enhancing road safety and enabling automated driving features through advanced computer vision techniques. This is particularly true for short-range vehicle automation, where non-linear fisheye cameras are commonly used. However, these cameras are challenged by optical distortions, known as fisheye geometric distortions, which lead to object deformation within the image and significant pixel distortion, particularly at the image periphery. Based on the observation that fisheye and spherical images exhibit at least superficially similar geometric characteristics, we investigate the applicability of spherical models—including Spherical Convolutional Neural Networks (CNNs) and Spherical Vision Transformers (ViTs)—to fisheye images, even though fisheye images are not truly spherical. We perform our comparison using fisheye datasets—Woodscape, SynWoodscape, and SynCityscapes in autonomous driving scenarios, with a specific focus on the ability of spherical methods (Spherical CNNs and ViTs) to manage fisheye distortions and compared them against traditional non-spherical methods. Our findings indicate that spherical methods effectively address fisheye distortions without needing extra data augmentations. This results in better mean Intersection over Union (mIoU) scores, pixel accuracy, and better surround-view perception than other modern approaches for fisheye semantic segmentation. However, we also find that spherical methods have a greater tendency to overfit smaller datasets compared with non-spherical models. These advancements highlight how non-linear camera images can take advantage of spherical approximations through spherical models in autonomous driving.
{"title":"A Comparison of Spherical Neural Networks for Surround-View Fisheye Image Semantic Segmentation","authors":"Anam Manzoor;Reenu Mohandas;Anthony Scanlan;Eoin Martino Grua;Fiachra Collins;Ganesh Sistu;Ciarán Eising","doi":"10.1109/OJVT.2025.3541891","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3541891","url":null,"abstract":"Please check and confirm whether the authors affiliation in the first The automotive industry has made significant strides in enhancing road safety and enabling automated driving features through advanced computer vision techniques. This is particularly true for short-range vehicle automation, where non-linear fisheye cameras are commonly used. However, these cameras are challenged by optical distortions, known as fisheye geometric distortions, which lead to object deformation within the image and significant pixel distortion, particularly at the image periphery. Based on the observation that fisheye and spherical images exhibit at least superficially similar geometric characteristics, we investigate the applicability of spherical models—including Spherical Convolutional Neural Networks (CNNs) and Spherical Vision Transformers (ViTs)—to fisheye images, even though fisheye images are not truly spherical. We perform our comparison using fisheye datasets—<italic>Woodscape, SynWoodscape, and SynCityscapes</i> in autonomous driving scenarios, with a specific focus on the ability of spherical methods (Spherical CNNs and ViTs) to manage fisheye distortions and compared them against traditional non-spherical methods. Our findings indicate that spherical methods effectively address fisheye distortions without needing extra data augmentations. This results in better mean Intersection over Union (mIoU) scores, pixel accuracy, and better surround-view perception than other modern approaches for fisheye semantic segmentation. However, we also find that spherical methods have a greater tendency to overfit smaller datasets compared with non-spherical models. These advancements highlight how non-linear camera images can take advantage of spherical approximations through spherical models in autonomous driving.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"717-740"},"PeriodicalIF":5.3,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10884975","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594274","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 : 2025-02-10DOI: 10.1109/OJVT.2025.3540174
Zhipeng Wang;Soon Xin Ng;Mohammed El-Hajjar
Unmanned aerial vehicles (UAVs) can be considered in many applications, such as wireless communication, logistics transportation, agriculture and disaster prevention. The flexible maneuverability of UAVs also means that the UAV often operates in complex 3D environments, which requires efficient and reliable path planning system support. However, as a limited resource platform, the UAV systems cannot support highly complex path planning algorithms in lots of scenarios. In this paper, we propose a 3D spatial information compression (3DSIC) based deep reinforcement learning (DRL) algorithm for UAV path planning in cluttered 3D environments. Specifically, the proposed algorithm compresses the 3D spatial information to 2D through 3DSIC, and then combines the compressed 2D environment information with the current UAV layer spatial information to train UAV agents for path planning using neural networks. Additionally, the proposed 3DSIC is a plug and use module that can be combined with various DRL frameworks such as Deep Q-Network (DQN) and deep deterministic policy gradient (DDPG). Our simulation results show that the training efficiency of 3DSIC-DQN is 4.028 times higher than that directly implementing DQN in a $100 times 100 times 50$ 3D cluttered environment. Furthermore, the training efficiency of 3DSIC-DDPG is 3.9 times higher than the traditional DDPG in the same environment. Moreover, 3DSIC combined with fast recurrent stochastic value gradient (FRSVG), which can be considered as the most state-of-the-art DRL algorithm for UAV path planning, exhibits 2.35 times faster training speed compared with the original FRSVG algorithm.
{"title":"A 3D Spatial Information Compression Based Deep Reinforcement Learning Technique for UAV Path Planning in Cluttered Environments","authors":"Zhipeng Wang;Soon Xin Ng;Mohammed El-Hajjar","doi":"10.1109/OJVT.2025.3540174","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3540174","url":null,"abstract":"Unmanned aerial vehicles (UAVs) can be considered in many applications, such as wireless communication, logistics transportation, agriculture and disaster prevention. The flexible maneuverability of UAVs also means that the UAV often operates in complex 3D environments, which requires efficient and reliable path planning system support. However, as a limited resource platform, the UAV systems cannot support highly complex path planning algorithms in lots of scenarios. In this paper, we propose a 3D spatial information compression (3DSIC) based deep reinforcement learning (DRL) algorithm for UAV path planning in cluttered 3D environments. Specifically, the proposed algorithm compresses the 3D spatial information to 2D through 3DSIC, and then combines the compressed 2D environment information with the current UAV layer spatial information to train UAV agents for path planning using neural networks. Additionally, the proposed 3DSIC is a plug and use module that can be combined with various DRL frameworks such as Deep Q-Network (DQN) and deep deterministic policy gradient (DDPG). Our simulation results show that the training efficiency of 3DSIC-DQN is 4.028 times higher than that directly implementing DQN in a <inline-formula><tex-math>$100 times 100 times 50$</tex-math></inline-formula> 3D cluttered environment. Furthermore, the training efficiency of 3DSIC-DDPG is 3.9 times higher than the traditional DDPG in the same environment. Moreover, 3DSIC combined with fast recurrent stochastic value gradient (FRSVG), which can be considered as the most state-of-the-art DRL algorithm for UAV path planning, exhibits 2.35 times faster training speed compared with the original FRSVG algorithm.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"647-661"},"PeriodicalIF":5.3,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10878448","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583247","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 : 2025-01-30DOI: 10.1109/OJVT.2025.3536782
{"title":"2024 Index IEEE Open Journal of Vehicular Technology Vol. 5","authors":"","doi":"10.1109/OJVT.2025.3536782","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3536782","url":null,"abstract":"","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1766-1790"},"PeriodicalIF":5.3,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858486","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105977","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 : 2025-01-29DOI: 10.1109/OJVT.2025.3536176
Michal Frivaldsky;Matúš Danko;Tristan Schoenfelder;Martin Zavrel
This article examines the design challenges of hybrid energy storage systems (HESS) for electric vehicles (EVs), focusing on optimization based on driving profiles. Rising carbon dioxide emissions, especially in road traffic, require advanced energy solutions. In particular, electric vehicles offer great potential for reducing emissions in the transport sector. However, existing energy storage technologies such as lithium batteries have significant limitations in terms of power and energy density as well as cost efficiency, etc. To address these limitations, this study examines battery-SC hybrid systems, which represent a form of HESS. Using MATLAB Simulink, energy and power requirements are calculated for selected urban, combined, and motorway driving cycles. Based on the simulation results, which are obtained from mathematical vehicle dynamics models, this paper determines optimal configurations for battery and SC modules. Key findings highlight the trade-offs in performance, weight, and cost when designing HESS for varying vehicle classes. The study concludes that while HESS solutions significantly enhance energy efficiency and extend battery lifespan, their implementation remains complex and cost-intensive for medium and high-class vehicles. For lower-class vehicles, HESS offers an effective strategy to balance energy and power demands, contributing to sustainable transport solutions. The results provide important insights for the development of scalable and efficient hybrid storage systems that are designed for specific driving conditions.
{"title":"Design Issues of Hybrid Energy Storage Systems of Electric Vehicles According to Driving Profiles","authors":"Michal Frivaldsky;Matúš Danko;Tristan Schoenfelder;Martin Zavrel","doi":"10.1109/OJVT.2025.3536176","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3536176","url":null,"abstract":"This article examines the design challenges of hybrid energy storage systems (HESS) for electric vehicles (EVs), focusing on optimization based on driving profiles. Rising carbon dioxide emissions, especially in road traffic, require advanced energy solutions. In particular, electric vehicles offer great potential for reducing emissions in the transport sector. However, existing energy storage technologies such as lithium batteries have significant limitations in terms of power and energy density as well as cost efficiency, etc. To address these limitations, this study examines battery-SC hybrid systems, which represent a form of HESS. Using MATLAB Simulink, energy and power requirements are calculated for selected urban, combined, and motorway driving cycles. Based on the simulation results, which are obtained from mathematical vehicle dynamics models, this paper determines optimal configurations for battery and SC modules. Key findings highlight the trade-offs in performance, weight, and cost when designing HESS for varying vehicle classes. The study concludes that while HESS solutions significantly enhance energy efficiency and extend battery lifespan, their implementation remains complex and cost-intensive for medium and high-class vehicles. For lower-class vehicles, HESS offers an effective strategy to balance energy and power demands, contributing to sustainable transport solutions. The results provide important insights for the development of scalable and efficient hybrid storage systems that are designed for specific driving conditions.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"619-631"},"PeriodicalIF":5.3,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10857387","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521473","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}
Wireless Smart Utility Network Field Area Network (Wi-SUN FAN) is a technical specification of Wi-SUN that introduces multi-hop machine-to-machine transmission for advanced smart city infrastructure. Wi-SUN FAN uses the Internet Protocol Version 6 (IPv6) Routing Protocol for Low-Power and Lossy Network (RPL) as the routing protocol and expected transmission count (ETX) as the routing metric to build multi-hop networks. ETX is used to convert number of communications into a link metric, which measures the quality of communication between nodes. This metric measures the relative distance to the root node via adjacent nodes to determine the parent node. However, this method of determining link metrics may cause nodes to frequently change their parents. If a node selects a parent with poor link quality, the communication reliability deteriorates; therefore, each node must appropriately select a candidate parent node. This article presents the transmission characteristics of Wi-SUN FANs and highlights the problems of conventional link metrics. Based on this, a novel method is proposed for calculating the link metric. The performed computer simulations verified the superiority of the proposed metric when the packet generation rate remained unaffected by the generation of control frames that switched the parent nodes. Furthermore, the transmission success rate of the media access control (MAC) frame was experimentally measured in an office building using Wi-SUN FAN communication modules based on the proposed method. The evaluation confirmed that the proposed link metric improved the minimum MAC frame transmission success rate by 24.2% and the average success rate by 10.4%.
{"title":"Stabilized Multi-Hop Route Construction Using a Modified Link Metric for Wi-SUN FAN Systems","authors":"Ryuichi Nagao;Daiki Hotta;Hiroko Masaki;Keiichi Mizutani;Hiroshi Harada","doi":"10.1109/OJVT.2025.3534842","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3534842","url":null,"abstract":"Wireless Smart Utility Network Field Area Network (Wi-SUN FAN) is a technical specification of Wi-SUN that introduces multi-hop machine-to-machine transmission for advanced smart city infrastructure. Wi-SUN FAN uses the Internet Protocol Version 6 (IPv6) Routing Protocol for Low-Power and Lossy Network (RPL) as the routing protocol and expected transmission count (ETX) as the routing metric to build multi-hop networks. ETX is used to convert number of communications into a link metric, which measures the quality of communication between nodes. This metric measures the relative distance to the root node via adjacent nodes to determine the parent node. However, this method of determining link metrics may cause nodes to frequently change their parents. If a node selects a parent with poor link quality, the communication reliability deteriorates; therefore, each node must appropriately select a candidate parent node. This article presents the transmission characteristics of Wi-SUN FANs and highlights the problems of conventional link metrics. Based on this, a novel method is proposed for calculating the link metric. The performed computer simulations verified the superiority of the proposed metric when the packet generation rate remained unaffected by the generation of control frames that switched the parent nodes. Furthermore, the transmission success rate of the media access control (MAC) frame was experimentally measured in an office building using Wi-SUN FAN communication modules based on the proposed method. The evaluation confirmed that the proposed link metric improved the minimum MAC frame transmission success rate by 24.2% and the average success rate by 10.4%.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"607-618"},"PeriodicalIF":5.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10855464","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489077","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 : 2025-01-24DOI: 10.1109/OJVT.2025.3533368
Samuel Thornton;Nithin Santhanam;Rajeev Chhajer;Sujit Dey
Vehicular sensing has reached new heights due to advances in external perception systems enabled by the increasing number and type of sensors in vehicles, as well as the availability of on-board computing. These changes have led to improvements in driver safety and have also created a highly heterogeneous environment of vehicles on the road today in terms of sensing and computing. Using collaborative perception, the information obtained by vehicles with sensing capabilities can be expanded and improved, and older vehicles that lack external sensors and computing capabilities can be informed of potential hazards, opening the opportunity to improve traffic efficiency and safety on the roads. However, achieving real-time collaborative perception is a difficult task due to the dynamic availability of vehicular sensing and computing and the highly variable nature of vehicular communications. To address these challenges, we propose a Heterogeneous Adaptive Collaborative Perception (HAdCoP) framework which utilizes a Context-aware Latency Prediction Network (CaLPeN) to intelligently select which vehicles should transmit their sensor data, the specific individual and collaborative perception tasks, and the amount of computational offloading that should be utilized given information about the current state of the environment. Additionally, we propose an Adaptive Perception Frequency (APF) model to determine the optimal end-to-end latency requirement according to the current state of the environment. The proposed CaLPeN model outperforms six implemented comparison models in terms of effective mean average precision (EmAP), beating the next best model's performance by 5.5% on average when tested on the OPV2V perception dataset using two different combinations of wireless communication conditions and vehicular sensor/computing distributions.
{"title":"Real-Time Heterogeneous Collaborative Perception in Edge-Enabled Vehicular Environments","authors":"Samuel Thornton;Nithin Santhanam;Rajeev Chhajer;Sujit Dey","doi":"10.1109/OJVT.2025.3533368","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3533368","url":null,"abstract":"Vehicular sensing has reached new heights due to advances in external perception systems enabled by the increasing number and type of sensors in vehicles, as well as the availability of on-board computing. These changes have led to improvements in driver safety and have also created a highly heterogeneous environment of vehicles on the road today in terms of sensing and computing. Using collaborative perception, the information obtained by vehicles with sensing capabilities can be expanded and improved, and older vehicles that lack external sensors and computing capabilities can be informed of potential hazards, opening the opportunity to improve traffic efficiency and safety on the roads. However, achieving real-time collaborative perception is a difficult task due to the dynamic availability of vehicular sensing and computing and the highly variable nature of vehicular communications. To address these challenges, we propose a Heterogeneous Adaptive Collaborative Perception (HAdCoP) framework which utilizes a Context-aware Latency Prediction Network (CaLPeN) to intelligently select which vehicles should transmit their sensor data, the specific individual and collaborative perception tasks, and the amount of computational offloading that should be utilized given information about the current state of the environment. Additionally, we propose an Adaptive Perception Frequency (APF) model to determine the optimal end-to-end latency requirement according to the current state of the environment. The proposed CaLPeN model outperforms six implemented comparison models in terms of effective mean average precision (EmAP), beating the next best model's performance by 5.5% on average when tested on the OPV2V perception dataset using two different combinations of wireless communication conditions and vehicular sensor/computing distributions.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"471-486"},"PeriodicalIF":5.3,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10852339","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388613","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 : 2025-01-23DOI: 10.1109/OJVT.2025.3533081
Ashraf Al-Rimawi;Faeik T Al Rabee;Arafat Al-Dweik
In beyond 5G (B5G), the higher directivity and attenuation make millimeter-wave (mmWave) very vulnerable to blockages that degrades the system performance. However, reconfigurable intelligent surface (RIS) is considered as a key enabler for B5G applications to avoid the blockages effect. In this paper, to accurately model real-world behavior, we investigate a new analytical framework model for a RIS-aided wireless communication system with a random user deployment over Nakagami-<inline-formula><tex-math>$m$</tex-math></inline-formula> fading channel where the user's position distributes according to random waypoint (RWP) model, to characterize the performance of the system, considering direct and indirect links. As a result, new expressions for end-to-end signal-to-noise ratio (SNR), coverage probability, and ergodic capacity (EC) are derived. The impact of different metrics such as: blockages density (<inline-formula><tex-math>$lambda _{b}$</tex-math></inline-formula>), number of RIS reflecting elements (<inline-formula><tex-math>$N$</tex-math></inline-formula>), fading parameter at the indirect link (<inline-formula><tex-math>$m_{R}$</tex-math></inline-formula>), and path loss parameter (<inline-formula><tex-math>$alpha$</tex-math></inline-formula>) has been studied to evaluate the system performance. The results provide valuable insights into the performance of the system under these metrics. The coverage probability is degraded by increasing the blockage density and path loss parameter as they hinder the signal propagation and limit the signal strength at the MU. For example, at <inline-formula><tex-math>$-10$</tex-math></inline-formula> dB, the coverage probability is degrading from <inline-formula><tex-math>$8times 10^{-2}$</tex-math></inline-formula> for blockage density <inline-formula><tex-math>$lambda _{b}=3$</tex-math></inline-formula> Blockes/<inline-formula><tex-math>$km^{2}$</tex-math></inline-formula> to <inline-formula><tex-math>$5times 10^{-5}$</tex-math></inline-formula> at <inline-formula><tex-math>$lambda _{b}=11$</tex-math></inline-formula> Blockes/<inline-formula><tex-math>$km^{2}$</tex-math></inline-formula>. On the other hand, increasing the number of RIS reflecting elements (<inline-formula><tex-math>$N$</tex-math></inline-formula>) and fading parameter (<inline-formula><tex-math>$m_{R}$</tex-math></inline-formula>) at the indirect link, improves the coverage probability by enhancing the signal strength, reducing the effects of fading, and compensating for environmental challenges such as blockages. For example, the coverage probability, at <inline-formula><tex-math>$-10$</tex-math></inline-formula> dB, increases from <inline-formula><tex-math>$3times 10^{-1}$</tex-math></inline-formula> at number of reflecting elements <inline-formula><tex-math>$N = 15$</tex-math></inline-formula> to <inline-formula><tex-math>$8times 10^{-1}$</tex-math></inline-formula> at <inline-formula><tex-math>$N=40$</tex-math></inline-formula>. As
{"title":"Coverage Probability of RIS-Assisted Wireless Communication Systems With Random User Deployment Over Nakagami-$m$ Fading Channel","authors":"Ashraf Al-Rimawi;Faeik T Al Rabee;Arafat Al-Dweik","doi":"10.1109/OJVT.2025.3533081","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3533081","url":null,"abstract":"In beyond 5G (B5G), the higher directivity and attenuation make millimeter-wave (mmWave) very vulnerable to blockages that degrades the system performance. However, reconfigurable intelligent surface (RIS) is considered as a key enabler for B5G applications to avoid the blockages effect. In this paper, to accurately model real-world behavior, we investigate a new analytical framework model for a RIS-aided wireless communication system with a random user deployment over Nakagami-<inline-formula><tex-math>$m$</tex-math></inline-formula> fading channel where the user's position distributes according to random waypoint (RWP) model, to characterize the performance of the system, considering direct and indirect links. As a result, new expressions for end-to-end signal-to-noise ratio (SNR), coverage probability, and ergodic capacity (EC) are derived. The impact of different metrics such as: blockages density (<inline-formula><tex-math>$lambda _{b}$</tex-math></inline-formula>), number of RIS reflecting elements (<inline-formula><tex-math>$N$</tex-math></inline-formula>), fading parameter at the indirect link (<inline-formula><tex-math>$m_{R}$</tex-math></inline-formula>), and path loss parameter (<inline-formula><tex-math>$alpha$</tex-math></inline-formula>) has been studied to evaluate the system performance. The results provide valuable insights into the performance of the system under these metrics. The coverage probability is degraded by increasing the blockage density and path loss parameter as they hinder the signal propagation and limit the signal strength at the MU. For example, at <inline-formula><tex-math>$-10$</tex-math></inline-formula> dB, the coverage probability is degrading from <inline-formula><tex-math>$8times 10^{-2}$</tex-math></inline-formula> for blockage density <inline-formula><tex-math>$lambda _{b}=3$</tex-math></inline-formula> Blockes/<inline-formula><tex-math>$km^{2}$</tex-math></inline-formula> to <inline-formula><tex-math>$5times 10^{-5}$</tex-math></inline-formula> at <inline-formula><tex-math>$lambda _{b}=11$</tex-math></inline-formula> Blockes/<inline-formula><tex-math>$km^{2}$</tex-math></inline-formula>. On the other hand, increasing the number of RIS reflecting elements (<inline-formula><tex-math>$N$</tex-math></inline-formula>) and fading parameter (<inline-formula><tex-math>$m_{R}$</tex-math></inline-formula>) at the indirect link, improves the coverage probability by enhancing the signal strength, reducing the effects of fading, and compensating for environmental challenges such as blockages. For example, the coverage probability, at <inline-formula><tex-math>$-10$</tex-math></inline-formula> dB, increases from <inline-formula><tex-math>$3times 10^{-1}$</tex-math></inline-formula> at number of reflecting elements <inline-formula><tex-math>$N = 15$</tex-math></inline-formula> to <inline-formula><tex-math>$8times 10^{-1}$</tex-math></inline-formula> at <inline-formula><tex-math>$N=40$</tex-math></inline-formula>. As ","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"596-606"},"PeriodicalIF":5.3,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10851370","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430595","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 : 2025-01-22DOI: 10.1109/OJVT.2025.3532848
Hugo Hawkins;Chao Xu;Lie-Liang Yang;Lajos Hanzo
There is a dearth of publications on the subject of spreading-aided Orthogonal Time Frequency Space (OTFS) solutions, especially for Integrated Sensing and Communication (ISAC), even though Code Division Multiple Access (CDMA) assisted multi-user OTFS (CDMA/OTFS) exhibits tangible benefits. Hence, this work characterises both the communication Bit Error Rate (BER) and sensing Root Mean Square Error (RMSE) performance of Code Division Multiple Access OTFS (CDMA/OTFS), and contrasts them to pure OTFS. Three CDMA/OTFS configurations are considered: Delay Code Division Multiple Access OTFS (Dl-CDMA/OTFS), Doppler Code Division Multiple Access OTFS (Dp-CDMA/OTFS), and Delay Doppler Code Division Multiple Access OTFS (DD-CDMA/OTFS), which harness direct sequence spreading along the delay axis, Doppler axis, and DD domains respectively. For each configuration, the performance of Gold, Hadamard, and Zadoff-Chu sequences is investigated. The results demonstrate that Zadoff-Chu Dl-CDMA/OTFS and DD-CDMA/OTFS consistently outperform pure OTFS sensing, whilst maintaining a similar communication performance at the same throughput. The extra modulation complexity of CDMA/OTFS is similar to that of other OTFS multi-user methodologies, but the demodulation complexity of CDMA/OTFS is lower than that of some other OTFS multi-user methodologies. CDMA/OTFS sensing can also consistently outperform OTFS sensing whilst not requiring any additional complexity for target parameter estimation. Therefore, CDMA/OTFS is an appealing candidate for implementing multi-user OTFS ISAC.
{"title":"CDMA/OTFS Sensing Outperforms Pure OTFS at the Same Communication Throughput","authors":"Hugo Hawkins;Chao Xu;Lie-Liang Yang;Lajos Hanzo","doi":"10.1109/OJVT.2025.3532848","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3532848","url":null,"abstract":"There is a dearth of publications on the subject of spreading-aided Orthogonal Time Frequency Space (OTFS) solutions, especially for Integrated Sensing and Communication (ISAC), even though Code Division Multiple Access (CDMA) assisted multi-user OTFS (CDMA/OTFS) exhibits tangible benefits. Hence, this work characterises both the communication Bit Error Rate (BER) and sensing Root Mean Square Error (RMSE) performance of Code Division Multiple Access OTFS (CDMA/OTFS), and contrasts them to pure OTFS. Three CDMA/OTFS configurations are considered: Delay Code Division Multiple Access OTFS (Dl-CDMA/OTFS), Doppler Code Division Multiple Access OTFS (Dp-CDMA/OTFS), and Delay Doppler Code Division Multiple Access OTFS (DD-CDMA/OTFS), which harness direct sequence spreading along the delay axis, Doppler axis, and DD domains respectively. For each configuration, the performance of Gold, Hadamard, and Zadoff-Chu sequences is investigated. The results demonstrate that Zadoff-Chu Dl-CDMA/OTFS and DD-CDMA/OTFS consistently outperform pure OTFS sensing, whilst maintaining a similar communication performance at the same throughput. The extra modulation complexity of CDMA/OTFS is similar to that of other OTFS multi-user methodologies, but the demodulation complexity of CDMA/OTFS is lower than that of some other OTFS multi-user methodologies. CDMA/OTFS sensing can also consistently outperform OTFS sensing whilst not requiring any additional complexity for target parameter estimation. Therefore, CDMA/OTFS is an appealing candidate for implementing multi-user OTFS ISAC.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"502-519"},"PeriodicalIF":5.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10849597","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388542","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 : 2025-01-20DOI: 10.1109/OJVT.2025.3531916
Martin Lerch;Philipp Svoboda;Josef Resch;Markus Rupp
Vehicular repeater systems improve the mobile coverage inside railroad cars by amplifying the signals received by a pick-up antenna on the roof and distributing the amplified signals inside the car. Uplink signals are received accordingly in the cars, amplified and transmitted via the roof antenna. At the same time, amplified noise is also transmitted. In uplink direction, this can lead to impairments of mobile communication in the entire cell. However, in vehicular repeater systems there are other sources of uplink interference that could be mistakenly be interpreted as additive noise. In addition to the influence of additive noise, in this paper we investigate the influence of inter-symbol interference due to direct propagation through the windows, interference due to passive intermodulation that can occur in the indoor antenna, and interference due to limited isolation between the indoor and outdoor antenna. We introduce a pathloss model for a vehicle repeater system. Based on this model, we investigate the influence of these different sources of interference on the uplink experimentally. Depending on the kind of interference, we conduct our investigations over different system parameters, such as the penetration loss of the windows, isolation between the indoor and outdoor antenna, and the gain settings of the repeater. The findings presented in this study provide valuable insights for network operators and researchers, facilitating the design of robust and efficient vehicular repeater systems that enhance connectivity and user experience in cellular wireless networks.
{"title":"Cellular Uplink Impairments in Vehicular Repeater Deployments","authors":"Martin Lerch;Philipp Svoboda;Josef Resch;Markus Rupp","doi":"10.1109/OJVT.2025.3531916","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3531916","url":null,"abstract":"Vehicular repeater systems improve the mobile coverage inside railroad cars by amplifying the signals received by a pick-up antenna on the roof and distributing the amplified signals inside the car. Uplink signals are received accordingly in the cars, amplified and transmitted via the roof antenna. At the same time, amplified noise is also transmitted. In uplink direction, this can lead to impairments of mobile communication in the entire cell. However, in vehicular repeater systems there are other sources of uplink interference that could be mistakenly be interpreted as additive noise. In addition to the influence of additive noise, in this paper we investigate the influence of inter-symbol interference due to direct propagation through the windows, interference due to passive intermodulation that can occur in the indoor antenna, and interference due to limited isolation between the indoor and outdoor antenna. We introduce a pathloss model for a vehicle repeater system. Based on this model, we investigate the influence of these different sources of interference on the uplink experimentally. Depending on the kind of interference, we conduct our investigations over different system parameters, such as the penetration loss of the windows, isolation between the indoor and outdoor antenna, and the gain settings of the repeater. The findings presented in this study provide valuable insights for network operators and researchers, facilitating the design of robust and efficient vehicular repeater systems that enhance connectivity and user experience in cellular wireless networks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"487-501"},"PeriodicalIF":5.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10848174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388662","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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