Pub Date : 2024-03-28DOI: 10.1109/OJVT.2024.3382886
Tho Le-Ngoc;Yuanzhe Gong;Mobeen Mahmood;Asil Koc;Robert Morawski;James Gary Griffiths;Philippe Guillemette;Jamal Zaid;Peiwei Wang
In-band full-duplex (FD) operation can double the spectral efficiency of massive multiple-input multiple-output (mMIMO) systems by allowing simultaneous transmission and reception over the same time/frequency slot. However, the main challenge encountered in implementing an FD radio wireless transceiver is to greatly suppress the residual self-interference (SI) generated from its own transmitter below the receiver noise floor to avoid performance degradation in the detection of the signal of interest received from remote transmitters. It is pointed out that the single-stage digital beamforming (DBF) scheme would introduce an impractically high complexity unsuitable for implementing FD-mMIMO. This paper considers an FD hybrid beamforming (FD-HBF) scheme for multi-user (MU)-mMIMO systems, in which large SI-suppression is achieved by exploring dynamic transmitter/receiver (Tx/Rx) isolation using RF-beamforming designs, and exploiting the degrees of freedom of a large number of antenna elements in separate Tx and Rx antenna arrays, in conjunction with high-performance baseband (BB) digital fractionally-spaced (FS) SI-cancellation (SIC) techniques. This paper starts with a discussion of the main parameters and impairments (in an mMIMO transceiver) that can impact the SI-suppression performance and the proposed RF-beamforming Tx/Rx isolation and BB SI-cancellation design strategies along with their achieved performance and complexities. Joint-beamforming optimization to maximize both Tx/Rx performance and isolation is discussed with an example of a nature-inspired optimization scheme to achieve an average Tx/Rx RF isolation of 64.4 dB and the best isolation of 76 dB. The paper continues with a description of an FD-mMIMO transceiver prototype using Tx/Rx 8x8-element antenna arrays along with analytical, simulation and measured results. Illustrative results indicate that the proposed combination of RF-beamforming Tx/Rx isolation and BB digital fractionally spaced SI-cancellation can offer an overall SI suppression of more than 131 dB and bring the residual SI below the receiver noise floor.
带内全双工（FD）操作允许在同一时间/频率槽内同时进行发射和接收，可将大规模多输入多输出（mMIMO）系统的频谱效率提高一倍。然而，在实现 FD 无线电无线收发器时遇到的主要挑战是如何将自身发射器产生的残余自干扰（SI）大大抑制在接收器噪声本底以下，以避免在检测从远程发射器接收到的相关信号时出现性能下降。有人指出，单级数字波束成形（DBF）方案会带来不切实际的高复杂性，不适合实现 FD-mMIMO。本文考虑了一种适用于多用户（MU）-mMIMO 系统的 FD 混合波束成形（FD-HBF）方案，在该方案中，通过使用射频波束成形设计探索动态发射器/接收器（Tx/Rx）隔离，并利用独立的 Tx 和 Rx 天线阵列中大量天线元件的自由度，结合高性能基带（BB）数字分数间隔（FS）SI 消除（SIC）技术，实现了大 SI 抑制。本文首先讨论了可能影响 SI 抑制性能的主要参数和损伤（在 mMIMO 收发器中），以及建议的射频波束成形 Tx/Rx 隔离和 BB SI 消除设计策略及其实现的性能和复杂性。本文以自然启发的优化方案为例，讨论了最大化 Tx/Rx 性能和隔离度的联合波束成形优化，该方案可实现 64.4 dB 的平均 Tx/Rx 射频隔离度和 76 dB 的最佳隔离度。论文还介绍了使用 Tx/Rx 8x8 元天线阵列的 FD-mMIMO 收发器原型，以及分析、模拟和测量结果。说明性结果表明，所建议的射频波束成形 Tx/Rx 隔离和 BB 数字分段式 SI 消除相结合，可提供超过 131 dB 的整体 SI 抑制，并使残余 SI 低于接收器本底噪声。
{"title":"Full-Duplex in Massive Multiple-Input Multiple-Output","authors":"Tho Le-Ngoc;Yuanzhe Gong;Mobeen Mahmood;Asil Koc;Robert Morawski;James Gary Griffiths;Philippe Guillemette;Jamal Zaid;Peiwei Wang","doi":"10.1109/OJVT.2024.3382886","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3382886","url":null,"abstract":"In-band full-duplex (FD) operation can double the spectral efficiency of massive multiple-input multiple-output (mMIMO) systems by allowing simultaneous transmission and reception over the same time/frequency slot. However, the main challenge encountered in implementing an FD radio wireless transceiver is to greatly suppress the residual self-interference (SI) generated from its own transmitter below the receiver noise floor to avoid performance degradation in the detection of the signal of interest received from remote transmitters. It is pointed out that the single-stage digital beamforming (DBF) scheme would introduce an impractically high complexity unsuitable for implementing FD-mMIMO. This paper considers an FD hybrid beamforming (FD-HBF) scheme for multi-user (MU)-mMIMO systems, in which large SI-suppression is achieved by exploring dynamic transmitter/receiver (Tx/Rx) isolation using RF-beamforming designs, and exploiting the degrees of freedom of a large number of antenna elements in separate Tx and Rx antenna arrays, in conjunction with high-performance baseband (BB) digital fractionally-spaced (FS) SI-cancellation (SIC) techniques. This paper starts with a discussion of the main parameters and impairments (in an mMIMO transceiver) that can impact the SI-suppression performance and the proposed RF-beamforming Tx/Rx isolation and BB SI-cancellation design strategies along with their achieved performance and complexities. Joint-beamforming optimization to maximize both Tx/Rx performance and isolation is discussed with an example of a nature-inspired optimization scheme to achieve an average Tx/Rx RF isolation of 64.4 dB and the best isolation of 76 dB. The paper continues with a description of an FD-mMIMO transceiver prototype using Tx/Rx 8x8-element antenna arrays along with analytical, simulation and measured results. Illustrative results indicate that the proposed combination of RF-beamforming Tx/Rx isolation and BB digital fractionally spaced SI-cancellation can offer an overall SI suppression of more than 131 dB and bring the residual SI below the receiver noise floor.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"560-576"},"PeriodicalIF":6.4,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10483101","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140633580","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 : 2024-03-25DOI: 10.1109/OJVT.2024.3379751
Jorge Carvajal-Rodríguez;Danny S. Guamán;Christian Tipantuña;Felipe Grijalva;Luis Felipe Urquiza
Unmanned aerial vehicles (UAVs) have seen remarkable improvements in their flight capabilities and computational power. Their applications span various domains, such as agriculture, military, and communications. To improve communication quality and coverage in UAV-enabled systems, understanding effective placement techniques is crucial. While research has explored optimal UAV placement in two dimensions, there is a need for a comprehensive three-dimensional (3D) analysis, particularly for resource optimization. This article presents a systematic mapping study on 3D placement in UAV-enabled communication systems, incorporating a threat analysis for the reliability of the results. It provides valuable insights for future research on 3D placement optimization techniques, specifically examining optimization objectives, model system features, problem types, and solution strategies. Our research reveals, on one hand, an emphasis on optimizing data rate throughput, power transmission, and ground coverage, and a predominant use of large-scale fading in the air-to-ground channel model; on the other hand, heuristic algorithms prevail as the solution strategy. Moreover, we identify gaps in achieving critical objectives such as the probability of outage, deployment costs, quality of experience, and spectrum optimization. This highlights the need for further exploration in the formulation aspects of the system, which includes small-scale fading, access techniques, and interference management.
{"title":"3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study","authors":"Jorge Carvajal-Rodríguez;Danny S. Guamán;Christian Tipantuña;Felipe Grijalva;Luis Felipe Urquiza","doi":"10.1109/OJVT.2024.3379751","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3379751","url":null,"abstract":"Unmanned aerial vehicles (UAVs) have seen remarkable improvements in their flight capabilities and computational power. Their applications span various domains, such as agriculture, military, and communications. To improve communication quality and coverage in UAV-enabled systems, understanding effective placement techniques is crucial. While research has explored optimal UAV placement in two dimensions, there is a need for a comprehensive three-dimensional (3D) analysis, particularly for resource optimization. This article presents a systematic mapping study on 3D placement in UAV-enabled communication systems, incorporating a threat analysis for the reliability of the results. It provides valuable insights for future research on 3D placement optimization techniques, specifically examining optimization objectives, model system features, problem types, and solution strategies. Our research reveals, on one hand, an emphasis on optimizing data rate throughput, power transmission, and ground coverage, and a predominant use of large-scale fading in the air-to-ground channel model; on the other hand, heuristic algorithms prevail as the solution strategy. Moreover, we identify gaps in achieving critical objectives such as the probability of outage, deployment costs, quality of experience, and spectrum optimization. This highlights the need for further exploration in the formulation aspects of the system, which includes small-scale fading, access techniques, and interference management.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"523-559"},"PeriodicalIF":6.4,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10478734","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140559318","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 : 2024-03-18DOI: 10.1109/OJVT.2024.3378481
Anas Saci;Arafat Al-Dweik;Shihab Jimaa
This article proposes a novel Direct Detection (DD) scheme for multiple-input multiple-output (MIMO) unmanned aerial vehicle (UAV) communications where tedious, slow, and computationally demanding channel state information (CSI) estimation and detection processes are not required. The proposed detection scheme is achieved by exploiting the frequency and/or temporal correlation among the transmitted signals to directly extract the information symbols from the received signals. The results obtained show that the proposed scheme offers a significant advantage of approximately 15 dB performance gain compared to conventional linear detection schemes, even when such schemes are using perfect CSI. Furthermore, the proposed detection algorithm can be efficiently implemented using the Viterbi Algorithm, or its variants, to achieve further complexity reduction.
本文为多输入多输出（MIMO）无人飞行器（UAV）通信提出了一种新颖的直接检测（DD）方案，无需进行繁琐、缓慢且计算量大的信道状态信息（CSI）估计和检测过程。所提出的检测方案是利用发射信号之间的频率和/或时间相关性，直接从接收信号中提取信息符号。研究结果表明，与传统的线性检测方案相比，即使在使用完美 CSI 的情况下，拟议方案也能提供约 15 dB 的性能增益。此外，所提出的检测算法可通过使用 Viterbi 算法或其变体来有效实现，从而进一步降低复杂性。
{"title":"Near-Optimal Efficient MIMO Receiver for Miniature UAV-IoT Communications","authors":"Anas Saci;Arafat Al-Dweik;Shihab Jimaa","doi":"10.1109/OJVT.2024.3378481","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3378481","url":null,"abstract":"This article proposes a novel Direct Detection (DD) scheme for multiple-input multiple-output (MIMO) unmanned aerial vehicle (UAV) communications where tedious, slow, and computationally demanding channel state information (CSI) estimation and detection processes are not required. The proposed detection scheme is achieved by exploiting the frequency and/or temporal correlation among the transmitted signals to directly extract the information symbols from the received signals. The results obtained show that the proposed scheme offers a significant advantage of approximately 15 dB performance gain compared to conventional linear detection schemes, even when such schemes are using perfect CSI. Furthermore, the proposed detection algorithm can be efficiently implemented using the Viterbi Algorithm, or its variants, to achieve further complexity reduction.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"496-506"},"PeriodicalIF":6.4,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10474171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140345519","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 : 2024-03-16DOI: 10.1109/OJVT.2024.3402129
Zhipeng Wang;Soon Xin Ng;Mohammed EI-Hajjar
In recent years, unmanned aerial vehicles (UAVs) have been considered for many applications, such as disaster prevention and control, logistics and transportation, and wireless communication. Most UAVs need to be manually controlled using remote control, which can be challenging in many environments. Therefore, autonomous UAVs have attracted significant research interest, where most of the existing autonomous navigation algorithms suffer from long computation time and unsatisfactory performance. Hence, we propose a Deep Reinforcement Learning (DRL) UAV path planning algorithm based on cumulative reward and region segmentation. Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. The proposed region segmentation algorithm and cumulative reward model have been tested in different DRL techniques, where we show that the cumulative reward model can improve the training efficiency of deep neural networks by 30.8% and the region segmentation algorithm enables deep Q-network agent to avoid 99% of local optimal traps and assists deep deterministic policy gradient agent to avoid 92% of local optimal traps.
{"title":"Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation","authors":"Zhipeng Wang;Soon Xin Ng;Mohammed EI-Hajjar","doi":"10.1109/OJVT.2024.3402129","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3402129","url":null,"abstract":"In recent years, unmanned aerial vehicles (UAVs) have been considered for many applications, such as disaster prevention and control, logistics and transportation, and wireless communication. Most UAVs need to be manually controlled using remote control, which can be challenging in many environments. Therefore, autonomous UAVs have attracted significant research interest, where most of the existing autonomous navigation algorithms suffer from long computation time and unsatisfactory performance. Hence, we propose a Deep Reinforcement Learning (DRL) UAV path planning algorithm based on cumulative reward and region segmentation. Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. The proposed region segmentation algorithm and cumulative reward model have been tested in different DRL techniques, where we show that the cumulative reward model can improve the training efficiency of deep neural networks by 30.8% and the region segmentation algorithm enables deep Q-network agent to avoid 99% of local optimal traps and assists deep deterministic policy gradient agent to avoid 92% of local optimal traps.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"737-751"},"PeriodicalIF":6.4,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10531630","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304035","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 provides a comprehensive overview of the evolution of Machine Learning (ML), from traditional to advanced, in its application and integration into unmanned aerial vehicle (UAV) communication frameworks and practical applications. The manuscript starts with an overview of the existing research on UAV communication and introduces the most traditional ML techniques. It then discusses UAVs as versatile actors in mobile networks, assuming different roles from airborne user equipment (UE) to base stations (BS). UAV have demonstrated considerable potential in addressing the evolving challenges of next-generation mobile networks, such as enhancing coverage and facilitating temporary hotspots but pose new hurdles including optimal positioning, trajectory optimization, and energy efficiency. We therefore conduct a comprehensive review of advanced ML strategies, ranging from federated learning, transfer and meta-learning to explainable AI, to address those challenges. Finally, the use of state-of-the-art ML algorithms in these capabilities is explored and their potential extension to cloud and/or edge computing based network architectures is highlighted.
本文全面概述了机器学习（ML）从传统到先进的演变过程，及其在无人机（UAV）通信框架和实际应用中的应用和集成。文稿首先概述了无人机通信方面的现有研究，并介绍了最传统的 ML 技术。然后讨论了无人机作为移动网络中的多面手，承担着从机载用户设备（UE）到基站（BS）的不同角色。无人机在应对下一代移动网络不断发展的挑战（如增强覆盖范围和促进临时热点）方面表现出了相当大的潜力，但也带来了新的障碍，包括优化定位、轨迹优化和能效。因此，我们全面回顾了先进的人工智能策略，从联合学习、迁移学习和元学习到可解释人工智能，以应对这些挑战。最后，我们探讨了最先进的人工智能算法在这些能力中的应用，并强调了这些算法扩展到基于云计算和/或边缘计算的网络架构的潜力。
{"title":"Advancing UAV Communications: A Comprehensive Survey of Cutting-Edge Machine Learning Techniques","authors":"Chenrui Sun;Gianluca Fontanesi;Berk Canberk;Amirhossein Mohajerzadeh;Symeon Chatzinotas;David Grace;Hamed Ahmadi","doi":"10.1109/OJVT.2024.3401024","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3401024","url":null,"abstract":"This paper provides a comprehensive overview of the evolution of Machine Learning (ML), from traditional to advanced, in its application and integration into unmanned aerial vehicle (UAV) communication frameworks and practical applications. The manuscript starts with an overview of the existing research on UAV communication and introduces the most traditional ML techniques. It then discusses UAVs as versatile actors in mobile networks, assuming different roles from airborne user equipment (UE) to base stations (BS). UAV have demonstrated considerable potential in addressing the evolving challenges of next-generation mobile networks, such as enhancing coverage and facilitating temporary hotspots but pose new hurdles including optimal positioning, trajectory optimization, and energy efficiency. We therefore conduct a comprehensive review of advanced ML strategies, ranging from federated learning, transfer and meta-learning to explainable AI, to address those challenges. Finally, the use of state-of-the-art ML algorithms in these capabilities is explored and their potential extension to cloud and/or edge computing based network architectures is highlighted.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"825-854"},"PeriodicalIF":5.3,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10531095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141624107","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 : 2024-03-14DOI: 10.1109/OJVT.2024.3400901
Pedro H. D. Almeida;Hugerles S. Silva;Ugo S. Dias;Rausley A. A. de Souza;Iguatemi E. Fonseca;Yonghui Li
In this article, exact expressions are presented for the probability density function, cumulative distribution function, moment generating function, and higher-order moments of the instantaneous signal-to-noise ratio, considering the product and the sum of the products of $N$$alpha$ - $mathcal {F}$ variates with pointing errors. New expressions for the outage probability (OP), bit error probability (BEP), ergodic channel capacity, and the area under the receiver operating characteristics (AUC) are deduced, as well as the asymptotic ones. The obtained expressions are used to assess the influence of various channels and system parameters on the system performance. We analyze a scenario considering dual-hop terahertz links and another regarding reconfigurable intelligent surfaces (RIS)-assisted systems. All expressions derived in this work are new, and Monte Carlo simulations corroborate the analytical curves shown.
{"title":"Cascaded and Sum of Cascaded Over $boldsymbol{alpha }$–$boldsymbol{mathcal {F}}$ Fading Channels With Pointing Error Impairment","authors":"Pedro H. D. Almeida;Hugerles S. Silva;Ugo S. Dias;Rausley A. A. de Souza;Iguatemi E. Fonseca;Yonghui Li","doi":"10.1109/OJVT.2024.3400901","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3400901","url":null,"abstract":"In this article, exact expressions are presented for the probability density function, cumulative distribution function, moment generating function, and higher-order moments of the instantaneous signal-to-noise ratio, considering the product and the sum of the products of \u0000<inline-formula><tex-math>$N$</tex-math></inline-formula>\u0000 \u0000<inline-formula><tex-math>$alpha$</tex-math></inline-formula>\u0000-\u0000<inline-formula><tex-math>$mathcal {F}$</tex-math></inline-formula>\u0000 variates with pointing errors. New expressions for the outage probability (OP), bit error probability (BEP), ergodic channel capacity, and the area under the receiver operating characteristics (AUC) are deduced, as well as the asymptotic ones. The obtained expressions are used to assess the influence of various channels and system parameters on the system performance. We analyze a scenario considering dual-hop terahertz links and another regarding reconfigurable intelligent surfaces (RIS)-assisted systems. All expressions derived in this work are new, and Monte Carlo simulations corroborate the analytical curves shown.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"752-761"},"PeriodicalIF":6.4,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10530352","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141294950","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 : 2024-03-13DOI: 10.1109/OJVT.2024.3400607
Davide De Simone;Maria Stefania Carmeli;Salvatore D'Arco;Luigi Piegari;Pietro Tricoli
Light railways are a low carbon emission form of transport, but it is often difficult to electrify tracks in central urban areas. This limitation can be avoided by integrating an on-board battery storage connected to the dc bus of the traction inverter with a boost dc/dc converter. However, the boost converter requires a bulky inductor and introduces additional power losses that are undesirable. This paper proposes to replace the standard induction motor with an open ended winding induction motor connected at one end to the overhead line with the traction inverter and to the other end to a battery with a second inverter in order to reduce the power losses of the traction drive. The paper addresses design and control aspects for light rail vehicles with open ended winding induction machines when the power supply is partly from the overhead line and partly from the on board battery. Moreover, the paper studies in detail the hybrid operations of the traction system i.e., when the overhead line charges the battery during coasting or at the stops. Finally, numerical simulations for a real use case are presented to quantify the reduction of power losses in comparison to the standard solution.
{"title":"Design and Control of Hybrid Electric Light Rail Vehicles With Open Ended Winding Machines","authors":"Davide De Simone;Maria Stefania Carmeli;Salvatore D'Arco;Luigi Piegari;Pietro Tricoli","doi":"10.1109/OJVT.2024.3400607","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3400607","url":null,"abstract":"Light railways are a low carbon emission form of transport, but it is often difficult to electrify tracks in central urban areas. This limitation can be avoided by integrating an on-board battery storage connected to the dc bus of the traction inverter with a boost dc/dc converter. However, the boost converter requires a bulky inductor and introduces additional power losses that are undesirable. This paper proposes to replace the standard induction motor with an open ended winding induction motor connected at one end to the overhead line with the traction inverter and to the other end to a battery with a second inverter in order to reduce the power losses of the traction drive. The paper addresses design and control aspects for light rail vehicles with open ended winding induction machines when the power supply is partly from the overhead line and partly from the on board battery. Moreover, the paper studies in detail the hybrid operations of the traction system i.e., when the overhead line charges the battery during coasting or at the stops. Finally, numerical simulations for a real use case are presented to quantify the reduction of power losses in comparison to the standard solution.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"695-703"},"PeriodicalIF":6.4,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10530114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141096334","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 : 2024-03-11DOI: 10.1109/OJVT.2024.3375451
Sandra Roger;Carmen Botella-Mascarell;David Martín-Sacristán;David García-Roger;Jose F. Monserrat;Tommy Svensson
The concept of sustainability has been recently extended to cover economic and social factors besides the traditional environmental ones. This paper reflects on the potential of mobile communication standards towards achieving sustainable mobility, with focus on vehicular communications and use cases in smart cities scenarios. In this context, intelligent transportation systems, including connected and autonomous vehicles, will be key for developing affordable and sustainable infrastructures and services. We start by identifying three current technology trends, namely, towards climate neutral; cloudification and edge computing; and Big Data and artificial intelligence, and then we examine their capability to enable sustainable Vehicle-to-Everything (V2X) communication systems in beyond 5G and 6G networks. In the second part of the paper, a set of selected use case categories involving connected and autonomous vehicles is presented, showcasing the potential impact of the selected technology trends. Finally, a review of the estimates of the quantitative savings that could be achieved in environmental-related parameters such as energy/fuel consumption and greenhouse gas emissions is provided.
{"title":"Sustainable Mobility in B5G/6G: V2X Technology Trends and Use Cases","authors":"Sandra Roger;Carmen Botella-Mascarell;David Martín-Sacristán;David García-Roger;Jose F. Monserrat;Tommy Svensson","doi":"10.1109/OJVT.2024.3375451","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3375451","url":null,"abstract":"The concept of sustainability has been recently extended to cover economic and social factors besides the traditional environmental ones. This paper reflects on the potential of mobile communication standards towards achieving sustainable mobility, with focus on vehicular communications and use cases in smart cities scenarios. In this context, intelligent transportation systems, including connected and autonomous vehicles, will be key for developing affordable and sustainable infrastructures and services. We start by identifying three current technology trends, namely, towards climate neutral; cloudification and edge computing; and Big Data and artificial intelligence, and then we examine their capability to enable sustainable Vehicle-to-Everything (V2X) communication systems in beyond 5G and 6G networks. In the second part of the paper, a set of selected use case categories involving connected and autonomous vehicles is presented, showcasing the potential impact of the selected technology trends. Finally, a review of the estimates of the quantitative savings that could be achieved in environmental-related parameters such as energy/fuel consumption and greenhouse gas emissions is provided.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"459-472"},"PeriodicalIF":6.4,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10465596","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140321719","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}
The demodulation reference signal of the 5G Multiple-Input Multiple-Output Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) waveform has been designed for supporting Minimum Mean-Square Error-Interference Rejection Combining (MMSE-IRC) equalization, which has become the state-of-the-art, owing to its enhanced performance in the case of dense frequency reuse, which is typical in 5G. By contrast, in the 4G LTE system, typically turbo equalization techniques were used. The family of Non-Linear receiver techniques tend to be eminently suitable for tough rank-deficient scenarios, when the received signal constellation becomes linearly non-separable. Hence, we propose a novel receiver for interference-constrained MIMO-OFDM systems, relying on a linear MMSE-IRC detector intrinsically amalgamated with an additional NL equalizer. In this way, we may achieve the best of both worlds, retaining the interference rejection capability of the MMSE-IRC detector and the superior performance of the NL equalizer. Our solution circumvents the potential failure of the MMSE-IRC, when the MIMO channels' degree freedom is completely exhausted by the desired users in case the transmitter has a high number of transmission layers for example. Based on this concept, we then design a novel NL equalizer relying on the Smart Ordering and Candidate Adding (SOCA) algorithm. This reduced complexity NL detection algorithm is particularly well suited for practical hardware implementation using parallel processing at a low latency. Briefly, the proposed scheme employs the MMSE-IRC detector for mitigating the interference. It makes the first estimate of the desired user signals and then uses the SOCA detector for further decontaminating the received signals. It also generates the soft information, enabling turbo equalization, wherein iterative detector and decoder iteratively exchange their soft information. We present BLock Error Rate (BLER) results, which show that the proposed scheme can always achieve superior performance to the conventional MMSE-IRC detector at the cost of increasing the complexity. In some cases, our proposed scheme can obtain about 1.5 dB gain, at the cost of 4 times higher complexity. We demonstrate that the complexity of the SOCA detector can be reduced by adjusting its parameterization or at the cost of reducing the self-consistency of the soft information produced by the SOCA detector, which slightly erodes the BLER performance. In order to mitigate this, we propose to use Deep Learning (DL) for enhancing the accuracy of the soft information. Using this technique, we show that the MMSE-IRC-NL-SOCA detector relying on DL attains about 3 dB gain at the cost of only marginally increasing the complexity, compared to the proposed MMSE-IRC-NL-SOCA scheme.
{"title":"A Three-Stage-Concatenated Non-Linear MMSE Interference Rejection Combining Aided MIMO-OFDM Receiver and its EXIT-Chart Analysis","authors":"Jue Chen;Siyao Lu;Tsang-Yi Wang;Jwo-Yuh Wu;Chih-Peng Li;Soon Xin Ng;Robert G. Maunder;Lajos Hanzo","doi":"10.1109/OJVT.2024.3375217","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3375217","url":null,"abstract":"The demodulation reference signal of the 5G Multiple-Input Multiple-Output Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) waveform has been designed for supporting Minimum Mean-Square Error-Interference Rejection Combining (MMSE-IRC) equalization, which has become the state-of-the-art, owing to its enhanced performance in the case of dense frequency reuse, which is typical in 5G. By contrast, in the 4G LTE system, typically turbo equalization techniques were used. The family of Non-Linear receiver techniques tend to be eminently suitable for tough rank-deficient scenarios, when the received signal constellation becomes linearly non-separable. Hence, we propose a novel receiver for interference-constrained MIMO-OFDM systems, relying on a linear MMSE-IRC detector intrinsically amalgamated with an additional NL equalizer. In this way, we may achieve the best of both worlds, retaining the interference rejection capability of the MMSE-IRC detector and the superior performance of the NL equalizer. Our solution circumvents the potential failure of the MMSE-IRC, when the MIMO channels' degree freedom is completely exhausted by the desired users in case the transmitter has a high number of transmission layers for example. Based on this concept, we then design a novel NL equalizer relying on the Smart Ordering and Candidate Adding (SOCA) algorithm. This reduced complexity NL detection algorithm is particularly well suited for practical hardware implementation using parallel processing at a low latency. Briefly, the proposed scheme employs the MMSE-IRC detector for mitigating the interference. It makes the first estimate of the desired user signals and then uses the SOCA detector for further decontaminating the received signals. It also generates the soft information, enabling turbo equalization, wherein iterative detector and decoder iteratively exchange their soft information. We present BLock Error Rate (BLER) results, which show that the proposed scheme can always achieve superior performance to the conventional MMSE-IRC detector at the cost of increasing the complexity. In some cases, our proposed scheme can obtain about 1.5 dB gain, at the cost of 4 times higher complexity. We demonstrate that the complexity of the SOCA detector can be reduced by adjusting its parameterization or at the cost of reducing the self-consistency of the soft information produced by the SOCA detector, which slightly erodes the BLER performance. In order to mitigate this, we propose to use Deep Learning (DL) for enhancing the accuracy of the soft information. Using this technique, we show that the MMSE-IRC-NL-SOCA detector relying on DL attains about 3 dB gain at the cost of only marginally increasing the complexity, compared to the proposed MMSE-IRC-NL-SOCA scheme.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"507-522"},"PeriodicalIF":6.4,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10465599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555865","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}
Research on vehicle-to-everything (V2X) is attracting significant attention nowadays, driven by the recent advances in beyond-5G (B5G) networks and the multi-access edge computing (MEC) paradigm. However, the inherent heterogeneity of B5G combined with the security vulnerabilities of MEC infrastructure in dynamic V2X scenarios introduces unprecedented challenges. Efficient resource and security management in multi-domain V2X environments is vital, especially with the growing threat of distributed denial-of-service (DDoS) attacks against critical V2X services within MEC. Our approach employs the zero-touch network and service management (ZSM) standard, integrating autonomous security into end-to-end (E2E) slicing management. We consider an entire 5G network, including vehicular user equipment, radio access networks, MEC, and core components, in the presence of DDoS targeting V2X services. Our framework complies with security service-level agreements (SSLAs) and policies, autonomously deploying and interconnecting security sub-slices across domains. Security requirements are continuously monitored and, upon DDoS detection, our framework reacts with a coordinated E2E strategy. The strategy mitigates DDoS at the MEC and deploys countermeasures in neighboring domains. Performance assessment reveals effective DDoS detection and mitigation with low latency, aligned with the mission-critical nature of certain V2X services. This work is part of ETSI ZSM PoC “security SLA assurance in 5G network slices”.
{"title":"ZSM-Based E2E Security Slice Management for DDoS Attack Protection in MEC-Enabled V2X Environments","authors":"Rodrigo Asensio-Garriga;Pol Alemany;Alejandro M. Zarca;Roshan Sedar;Charalampos Kalalas;Jordi Ortiz;Ricard Vilalta;Raul Muñoz;Antonio Skarmeta","doi":"10.1109/OJVT.2024.3375448","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3375448","url":null,"abstract":"Research on vehicle-to-everything (V2X) is attracting significant attention nowadays, driven by the recent advances in beyond-5G (B5G) networks and the multi-access edge computing (MEC) paradigm. However, the inherent heterogeneity of B5G combined with the security vulnerabilities of MEC infrastructure in dynamic V2X scenarios introduces unprecedented challenges. Efficient resource and security management in multi-domain V2X environments is vital, especially with the growing threat of distributed denial-of-service (DDoS) attacks against critical V2X services within MEC. Our approach employs the zero-touch network and service management (ZSM) standard, integrating autonomous security into end-to-end (E2E) slicing management. We consider an entire 5G network, including vehicular user equipment, radio access networks, MEC, and core components, in the presence of DDoS targeting V2X services. Our framework complies with security service-level agreements (SSLAs) and policies, autonomously deploying and interconnecting security sub-slices across domains. Security requirements are continuously monitored and, upon DDoS detection, our framework reacts with a coordinated E2E strategy. The strategy mitigates DDoS at the MEC and deploys countermeasures in neighboring domains. Performance assessment reveals effective DDoS detection and mitigation with low latency, aligned with the mission-critical nature of certain V2X services. This work is part of ETSI ZSM PoC “security SLA assurance in 5G network slices”.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"485-495"},"PeriodicalIF":6.4,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10465254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140340026","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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