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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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}
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":null,"pages":null},"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}
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":null,"pages":null},"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}
Pub Date : 2024-03-09DOI: 10.1109/OJVT.2024.3399072
Hongzhao Zheng;Mohamed Atia;Halim Yanikomeroglu
Channel and delay coefficient are two essential parameters for the characterization of a multipath propagation environment. It is crucial to generate realistic channel and delay coefficient in order to study the channel characteristics that involves signals propagating through environments with severe multipath effects. While many deterministic channel models, such as ray-tracing (RT), face challenges like high computational complexity, data requirements for geometrical information, and inapplicability for space-ground links, and nongeometry-based stochastic channel models (NGSCMs) might lack spatial consistency and offer lower accuracy, we present a scalable tutorial for the channel modeling of dual mobile space-ground links in urban areas, utilizing the Quasi Deterministic Radio Channel Generator (QuaDRiGa), which adopts a geometry-based stochastic channel model (GSCM), in conjunction with an International Telecommunication Union (ITU) provided state duration model. This tutorial allows for the generation of realistic channel and delay coefficients in a multipath environment for dual mobile space-ground links. We validate the accuracy of the work by analyzing the generated channel and delay coefficient from several aspects, such as received signal power and amplitude, multipath delay distribution, delay spread and Doppler spectrum.
{"title":"Realistic Channel and Delay Coefficient Generation for Dual Mobile Space-Ground Links: A Tutorial","authors":"Hongzhao Zheng;Mohamed Atia;Halim Yanikomeroglu","doi":"10.1109/OJVT.2024.3399072","DOIUrl":"10.1109/OJVT.2024.3399072","url":null,"abstract":"Channel and delay coefficient are two essential parameters for the characterization of a multipath propagation environment. It is crucial to generate realistic channel and delay coefficient in order to study the channel characteristics that involves signals propagating through environments with severe multipath effects. While many deterministic channel models, such as ray-tracing (RT), face challenges like high computational complexity, data requirements for geometrical information, and inapplicability for space-ground links, and nongeometry-based stochastic channel models (NGSCMs) might lack spatial consistency and offer lower accuracy, we present a scalable tutorial for the channel modeling of dual mobile space-ground links in urban areas, utilizing the Quasi Deterministic Radio Channel Generator (QuaDRiGa), which adopts a geometry-based stochastic channel model (GSCM), in conjunction with an International Telecommunication Union (ITU) provided state duration model. This tutorial allows for the generation of realistic channel and delay coefficients in a multipath environment for dual mobile space-ground links. We validate the accuracy of the work by analyzing the generated channel and delay coefficient from several aspects, such as received signal power and amplitude, multipath delay distribution, delay spread and Doppler spectrum.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":6.4,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10526419","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141004387","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 : 2024-03-08DOI: 10.1109/OJVT.2024.3398566
Shota Mori;Keiichi Mizutani;Hiroshi Harada
Improving spectral efficiency is an important issue for the next generation of the 5th generation mobile communication (5G) systems. Full-duplex cellular (FDC) and dynamic-FDC (DDC) systems based on the 5G signal format (5G-FDC and 5G-DDC) have gained substantial attention for introducing in-band full-duplex (IBFD) into 5G. However, self-interference (SI) at a base station (BS) and inter-user interference (IUI) in user equipment (UE) are significant hurdles in implementing FDC and DDC systems. This study proposes an IUI cancellation (IUIC) scheme based on successive interference cancellation tailored to the signal configuration and channel coding of 5G. Additionally, we introduce user scheduling and adaptive modulation algorithms for 5G-DDC. We evaluate the proposed schemes using link- and system-level simulations. The results demonstrate a remarkable 40 dB reduction in IUI with a 3.4 dB decline in reception quality. Furthermore, our IUIC method reduces the IUI of close-distance UE pairs, expands the candidate UE pairs for IBFD operation, and significantly enhances the IBFD application ratio in the downlink slot by 51.0% compared to conventional 5G-DDC. Moreover, the gain of the uplink average throughput increases by 11.4% when the BS and UE transmission powers are at their maximum.
{"title":"Inter-User Interference Cancellation Scheme for 5G-Based Dynamic Full-Duplex Cellular System","authors":"Shota Mori;Keiichi Mizutani;Hiroshi Harada","doi":"10.1109/OJVT.2024.3398566","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3398566","url":null,"abstract":"Improving spectral efficiency is an important issue for the next generation of the 5th generation mobile communication (5G) systems. Full-duplex cellular (FDC) and dynamic-FDC (DDC) systems based on the 5G signal format (5G-FDC and 5G-DDC) have gained substantial attention for introducing in-band full-duplex (IBFD) into 5G. However, self-interference (SI) at a base station (BS) and inter-user interference (IUI) in user equipment (UE) are significant hurdles in implementing FDC and DDC systems. This study proposes an IUI cancellation (IUIC) scheme based on successive interference cancellation tailored to the signal configuration and channel coding of 5G. Additionally, we introduce user scheduling and adaptive modulation algorithms for 5G-DDC. We evaluate the proposed schemes using link- and system-level simulations. The results demonstrate a remarkable 40 dB reduction in IUI with a 3.4 dB decline in reception quality. Furthermore, our IUIC method reduces the IUI of close-distance UE pairs, expands the candidate UE pairs for IBFD operation, and significantly enhances the IBFD application ratio in the downlink slot by 51.0% compared to conventional 5G-DDC. Moreover, the gain of the uplink average throughput increases by 11.4% when the BS and UE transmission powers are at their maximum.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":6.4,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10522968","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141182060","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 : 2024-03-05DOI: 10.1109/OJVT.2024.3373721
Yazid M. Khattabi;Yazan H. Al-Badarneh;Mohamed-Slim Alouini
This article considers an interference-based radio-frequency energy harvesting (RF-EH)-empowered wireless dual-hop amplify-and-forward relaying system in which an ambient interferer is beneficially utilized as the solely free power source for EH and detrimentally considered as the dominant factor that corrupts its receivers. Three EH modes are considered and analyzed separately. In mode I, energy is harvested only by the source; in mode II, energy is harvested only by the relay; and in mode III, energy is harvested concurrently by both the source and relay. Under these modes, exact and approximate analytical expressions are derived for the system's outage probability, which are directly used to determine the system's delay-limited throughput as a performance figure of merit. Thorough numerical and simulation results are presented to verify the analytical work and to demonstrate the system's throughput performance under different system and channel parameters. For example, results reveal that for given channel conditions, increasing the interferer's power reduces the throughput in case of modes I and II, and has no effect on it in case of mode III. Also, for given interferer's power, improving the channel conditions between the interferer and a harvesting node, improves the throughput, while improving them between the interferer and a receiving node, degrades the throughput.
本文探讨了一种基于干扰的射频能量收集（RF-EH）供电无线双跳放大和前向中继系统，在该系统中，环境干扰器被用作 EH 的唯一免费电源，并被视为干扰其接收器的不利因素。本文考虑并分别分析了三种 EH 模式。在模式 I 中，能量仅由信号源采集；在模式 II 中，能量仅由中继器采集；在模式 III 中，能量由信号源和中继器同时采集。在这些模式下，得出了系统中断概率的精确和近似分析表达式，这些表达式可直接用于确定系统的延迟限制吞吐量，作为性能参数。为了验证分析结果，并证明系统在不同系统和信道参数下的吞吐量性能，我们给出了详尽的数值和仿真结果。例如，结果显示，在给定信道条件下，增加干扰功率会降低模式 I 和模式 II 的吞吐量，而对模式 III 则没有影响。此外，在给定干扰功率的情况下，改善干扰器与收获节点之间的信道条件可提高吞吐量，而改善干扰器与接收节点之间的信道条件则会降低吞吐量。
{"title":"On the Performance of Interference-Based Energy-Harvesting-Enabled Wireless AF Relaying Communication Systems","authors":"Yazid M. Khattabi;Yazan H. Al-Badarneh;Mohamed-Slim Alouini","doi":"10.1109/OJVT.2024.3373721","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3373721","url":null,"abstract":"This article considers an interference-based radio-frequency energy harvesting (RF-EH)-empowered wireless dual-hop amplify-and-forward relaying system in which an ambient interferer is beneficially utilized as the solely free power source for EH and detrimentally considered as the dominant factor that corrupts its receivers. Three EH modes are considered and analyzed separately. In mode I, energy is harvested only by the source; in mode II, energy is harvested only by the relay; and in mode III, energy is harvested concurrently by both the source and relay. Under these modes, exact and approximate analytical expressions are derived for the system's outage probability, which are directly used to determine the system's delay-limited throughput as a performance figure of merit. Thorough numerical and simulation results are presented to verify the analytical work and to demonstrate the system's throughput performance under different system and channel parameters. For example, results reveal that for given channel conditions, increasing the interferer's power reduces the throughput in case of modes I and II, and has no effect on it in case of mode III. Also, for given interferer's power, improving the channel conditions between the interferer and a harvesting node, improves the throughput, while improving them between the interferer and a receiving node, degrades the throughput.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":null,"pages":null},"PeriodicalIF":6.4,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10460164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140321718","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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