Pub Date : 2024-12-30DOI: 10.1109/OJVT.2024.3524057
J. M. Sánchez-Martín;C. Gijón;M. Toril;S. Luna-Ramírez;V. Wille
Radio access network optimization is a critical task in current cellular systems. For this purpose, Minimization of Drive Test (MDT) functionality provides mobile operators with georeferenced network performance statistics to tune radio propagation models in re-planning tools. However, some samples in MDT traces contain critical location errors due to the user equipment's energy-saving, thus making MDT data filtering vital to guarantee an adequate performance of MDT-driven algorithms. Supervised Learning (SL) allows to train automatic systems for detecting abnormal MDT measurements by using a labeled dataset. Unfortunately, labeling MDT data is a labor-intensive task, that can be alleviated by using Self-Supervised Learning (SSL). This work presents a novel SSL method to detect MDT measurements with abnormal position information in road scenarios. For this purpose, a dataset is first labeled by combining unlabeled MDT traces from high-mobility users and freely available land use maps, and then an SL classifier is trained. Model assessment is carried out using MDT data collected in a live Long-Term Evolution (LTE) network. Performance analysis includes the comparison of six well-known SL algorithms and 3 different sets of input features aiming to improve model accuracy, generalizability, and explainability, respectively. Results show that considering predictors regarding positioning error increases model accuracy, whereas omitting this information allows to cover a wider range of terminals. Likewise, Shapley Additive exPlanations (SHAP) analysis proves that the use of high-level predictors significantly improves model explainability.
{"title":"Anomaly Detection in High Mobility MDT Traces Through Self-Supervised Learning","authors":"J. M. Sánchez-Martín;C. Gijón;M. Toril;S. Luna-Ramírez;V. Wille","doi":"10.1109/OJVT.2024.3524057","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3524057","url":null,"abstract":"Radio access network optimization is a critical task in current cellular systems. For this purpose, Minimization of Drive Test (MDT) functionality provides mobile operators with georeferenced network performance statistics to tune radio propagation models in re-planning tools. However, some samples in MDT traces contain critical location errors due to the user equipment's energy-saving, thus making MDT data filtering vital to guarantee an adequate performance of MDT-driven algorithms. Supervised Learning (SL) allows to train automatic systems for detecting abnormal MDT measurements by using a labeled dataset. Unfortunately, labeling MDT data is a labor-intensive task, that can be alleviated by using Self-Supervised Learning (SSL). This work presents a novel SSL method to detect MDT measurements with abnormal position information in road scenarios. For this purpose, a dataset is first labeled by combining unlabeled MDT traces from high-mobility users and freely available land use maps, and then an SL classifier is trained. Model assessment is carried out using MDT data collected in a live Long-Term Evolution (LTE) network. Performance analysis includes the comparison of six well-known SL algorithms and 3 different sets of input features aiming to improve model accuracy, generalizability, and explainability, respectively. Results show that considering predictors regarding positioning error increases model accuracy, whereas omitting this information allows to cover a wider range of terminals. Likewise, Shapley Additive exPlanations (SHAP) analysis proves that the use of high-level predictors significantly improves model explainability.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"396-411"},"PeriodicalIF":5.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818611","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106229","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 : 2024-12-24DOI: 10.1109/OJVT.2024.3521637
Andreas F. Molisch;Christoph F. Mecklenbräuker;Thomas Zemen;Ales Prokes;Markus Hofer;Faruk Pasic;Hussein Hammoud
Vehicle-to-everything (V2X) communications is an important part of future driver assistance and traffic control systems that will reduce accidents and congestion. The millimeter-wave (mmWave) band shows great promise to enable the high-data-rate links that are required or at least beneficial for such systems. To design such systems, we first need a detailed understanding of the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2X) propagation channels. This paper provides a systematic account of a series of measurement campaigns for such channels, conducted by the four research institutions of the authors over the past year. After a description of the similarities and differences of the channel sounders used in the campaigns, a description of the measurements in two European and one American city is given, and the scenarios of convoy, opposite-lane passing, and overtaking, are described. This is then followed by key results, presenting both sample results of power delay profiles and delay Doppler (or angular) spectra, as well as the statistical description such as delay spread and size of stationarity region. We also discuss the availability of spatial diversity in V2I connections and the correlation of the channels between different frequency bands.
{"title":"Millimeter-Wave V2X Channel Measurements in Urban Environments","authors":"Andreas F. Molisch;Christoph F. Mecklenbräuker;Thomas Zemen;Ales Prokes;Markus Hofer;Faruk Pasic;Hussein Hammoud","doi":"10.1109/OJVT.2024.3521637","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3521637","url":null,"abstract":"Vehicle-to-everything (V2X) communications is an important part of future driver assistance and traffic control systems that will reduce accidents and congestion. The millimeter-wave (mmWave) band shows great promise to enable the high-data-rate links that are required or at least beneficial for such systems. To design such systems, we first need a detailed understanding of the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2X) propagation channels. This paper provides a systematic account of a series of measurement campaigns for such channels, conducted by the four research institutions of the authors over the past year. After a description of the similarities and differences of the channel sounders used in the campaigns, a description of the measurements in two European and one American city is given, and the scenarios of convoy, opposite-lane passing, and overtaking, are described. This is then followed by key results, presenting both sample results of power delay profiles and delay Doppler (or angular) spectra, as well as the statistical description such as delay spread and size of stationarity region. We also discuss the availability of spatial diversity in V2I connections and the correlation of the channels between different frequency bands.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"520-541"},"PeriodicalIF":5.3,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10814933","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403850","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 : 2024-12-23DOI: 10.1109/OJVT.2024.3521091
Omar S. Aba Hussen;Shaiful J. Hashim;Nasri Sulaiman Member;S.A.R. Alhaddad;Bassam Y. Ribbfors;Masanobu Umeda;Keiichi Katamine
This research optimizes an electric vehicle (EV) sharing system for a university campus, focusing on different demand patterns and peak times within an Intelligent Transportation System (ITS) framework. The main objectives are to reduce the number of unserved demands and operational costs. A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. In addition to conventional decision variables, dynamic dual relocation thresholds and charge levels are introduced as decision variables to enhance optimization. The study compares two scenarios: Equally Distributed Demand (EDD) and Non-Equally Distributed Demand (NEDD), customized for the University Putra Malaysia (UPM) campus. Findings indicate that the NEDD scenario, which concentrates on specific demand areas, effectively decreases unserved demands and operational costs. Additionally, a station-specific approach expanded the solution space, improving adaptability and resulting in notable reductions in operational costs and smaller but meaningful improvements in unserved demands, especially during peak periods. By setting station-specific relocation thresholds and charge levels, resources were deployed efficiently, minimizing unnecessary relocations. The use of dynamic values for dual relocation thresholds and charge-to-work levels further optimized the process, reducing operational costs significantly, with a lesser impact on unserved demands across both scenarios. This research offers valuable insights into the implementation of EV sharing systems in educational institutions, emphasizing the advantages of focused resource allocation and the integration of dynamic decision variables.
{"title":"Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks","authors":"Omar S. Aba Hussen;Shaiful J. Hashim;Nasri Sulaiman Member;S.A.R. Alhaddad;Bassam Y. Ribbfors;Masanobu Umeda;Keiichi Katamine","doi":"10.1109/OJVT.2024.3521091","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3521091","url":null,"abstract":"This research optimizes an electric vehicle (EV) sharing system for a university campus, focusing on different demand patterns and peak times within an Intelligent Transportation System (ITS) framework. The main objectives are to reduce the number of unserved demands and operational costs. A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. In addition to conventional decision variables, dynamic dual relocation thresholds and charge levels are introduced as decision variables to enhance optimization. The study compares two scenarios: Equally Distributed Demand (EDD) and Non-Equally Distributed Demand (NEDD), customized for the University Putra Malaysia (UPM) campus. Findings indicate that the NEDD scenario, which concentrates on specific demand areas, effectively decreases unserved demands and operational costs. Additionally, a station-specific approach expanded the solution space, improving adaptability and resulting in notable reductions in operational costs and smaller but meaningful improvements in unserved demands, especially during peak periods. By setting station-specific relocation thresholds and charge levels, resources were deployed efficiently, minimizing unnecessary relocations. The use of dynamic values for dual relocation thresholds and charge-to-work levels further optimized the process, reducing operational costs significantly, with a lesser impact on unserved demands across both scenarios. This research offers valuable insights into the implementation of EV sharing systems in educational institutions, emphasizing the advantages of focused resource allocation and the integration of dynamic decision variables.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"315-331"},"PeriodicalIF":5.3,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10811944","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993437","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 : 2024-12-23DOI: 10.1109/OJVT.2024.3490479
{"title":"IEEE Vehicular Technology Society IEEE Open Journal on Vehicular Technology Information","authors":"","doi":"10.1109/OJVT.2024.3490479","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3490479","url":null,"abstract":"","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"C4-C4"},"PeriodicalIF":5.3,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10812005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875084","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 presents a comprehensive hazard analysis, risk assessment, and loss evaluation for an Evasive Minimum Risk Maneuvering (EMRM) system designed for autonomous vehicles. The EMRM system is designed to improve collision avoidance and mitigate loss severity by drawing inspiration from professional drivers who perform aggressive maneuvers while maintaining stability for effective risk mitigation. Recent advances in autonomous vehicle technology demonstrate a growing capability for high-performance maneuvers. This paper discusses a comprehensive safety verification process and establishes a clear safety goal to enhance the validation of the testing. The study systematically identifies potential hazards and assesses their risks to overall safety and the protection of vulnerable road users. A novel loss evaluation approach is introduced that focuses on the impact of mitigation maneuvers on loss severity. In addition, the proposed mitigation integrity level can be used to verify the minimum-risk maneuver feature. This paper applies a verification method to evasive maneuvering, contributing to the development of more reliable active safety features in autonomous driving systems.
{"title":"High-Resolution Safety Verification for Evasive Obstacle Avoidance in Autonomous Vehicles","authors":"Aliasghar Arab;Milad Khaleghi;Alireza Partovi;Alireza Abbaspour;Chaitanya Shinde;Yashar Mousavi;Vahid Azimi;Ali Karimmoddini","doi":"10.1109/OJVT.2024.3519951","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3519951","url":null,"abstract":"This paper presents a comprehensive hazard analysis, risk assessment, and loss evaluation for an Evasive Minimum Risk Maneuvering (EMRM) system designed for autonomous vehicles. The EMRM system is designed to improve collision avoidance and mitigate loss severity by drawing inspiration from professional drivers who perform aggressive maneuvers while maintaining stability for effective risk mitigation. Recent advances in autonomous vehicle technology demonstrate a growing capability for high-performance maneuvers. This paper discusses a comprehensive safety verification process and establishes a clear safety goal to enhance the validation of the testing. The study systematically identifies potential hazards and assesses their risks to overall safety and the protection of vulnerable road users. A novel loss evaluation approach is introduced that focuses on the impact of mitigation maneuvers on loss severity. In addition, the proposed mitigation integrity level can be used to verify the minimum-risk maneuver feature. This paper applies a verification method to evasive maneuvering, contributing to the development of more reliable active safety features in autonomous driving systems.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"276-287"},"PeriodicalIF":5.3,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10806869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937887","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 : 2024-12-16DOI: 10.1109/OJVT.2024.3517580
Bitan Banerjee;Robert C. Elliott;Witold A. Krzymień;Ivo Maljević
Most current stochastic geometric modeling of heterogeneous cellular networks (HetNets) assumes independent deployment of small-cell base stations (SBSs) with respect to macrocell base stations (MBSs), which leads to limited enhancement in network coverage and capacity. Therefore, in this paper we propose a new HetNet deployment model where the locations of SBSs are correlated with those of the MBSs. We place the SBSs at the vertices of each macrocell, where the macrocells are modeled by a Poisson-Voronoi tessellation with the MBSs as seeds. Theoretical analysis of this deployment scheme is performed using the tools of stochastic geometry. A novel distribution is also derived for the distance between the typical user and its closest SBS. Two tractable expressions for the distance distribution between a user and its closest SBS are presented, obtained by modeling the locations of SBSs as a Poisson point process and a $beta$-Ginibre point process. The latter models the SBS placement more accurately as it captures the correlation between the MBSs and SBSs. The performance of the proposed model is evaluated for several values of the network parameters and our results demonstrate the improvement in the coverage probability and rate coverage compared to other schemes in the literature.
{"title":"Improved Coverage of Massive MIMO HetNets Modeled Using Stochastic Geometry Techniques","authors":"Bitan Banerjee;Robert C. Elliott;Witold A. Krzymień;Ivo Maljević","doi":"10.1109/OJVT.2024.3517580","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3517580","url":null,"abstract":"Most current stochastic geometric modeling of heterogeneous cellular networks (HetNets) assumes independent deployment of small-cell base stations (SBSs) with respect to macrocell base stations (MBSs), which leads to limited enhancement in network coverage and capacity. Therefore, in this paper we propose a new HetNet deployment model where the locations of SBSs are correlated with those of the MBSs. We place the SBSs at the vertices of each macrocell, where the macrocells are modeled by a Poisson-Voronoi tessellation with the MBSs as seeds. Theoretical analysis of this deployment scheme is performed using the tools of stochastic geometry. A novel distribution is also derived for the distance between the typical user and its closest SBS. Two tractable expressions for the distance distribution between a user and its closest SBS are presented, obtained by modeling the locations of SBSs as a Poisson point process and a <inline-formula><tex-math>$beta$</tex-math></inline-formula>-Ginibre point process. The latter models the SBS placement more accurately as it captures the correlation between the MBSs and SBSs. The performance of the proposed model is evaluated for several values of the network parameters and our results demonstrate the improvement in the coverage probability and rate coverage compared to other schemes in the literature.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"741-773"},"PeriodicalIF":5.3,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10803018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637902","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 : 2024-12-16DOI: 10.1109/OJVT.2024.3519135
Safiu A. Gbadamosi;Gerhard P. Hancke;Adnan M. Abu-Mahfouz
In industrial factory automation and control system, reliable communication for automated guided vehicles (AGVs) in dynamic, interference laden factory settings are essential particularly for real-time operations. Device-to-device (D2D) technology can enhance industrial network performance by offloading traffic and improving resource utilization. However, deploying D2D-enabled networks presents challenges such as interference control and imperfect channel state information (ICSI). In this paper, we investigate an adaptive resource allocation and mode switching strategy (ARAMS) in D2D-enabled industrial small cell (SC) networks with ICSI to maximize the system throughput and address reuse interference for AGVs. The ARAMS scheme integrates mode switching (MS), channel-quality factor (CQF), and power control (PC) within a bi-phasic resource-sharing (RS) algorithm to lower the computational complexity. In the initial phase, the operational mode for each D2D user (DU) per cell is adaptively selected based on the channel gain ratio (CGR). Subsequently, it computes the CQF for each cell with a reuse DU to identify an optimal reuse partner. The final phase employs the Lagrangian dual decomposition method to decide the DU's and industrial cellular users (CUs) optimum distributed power to maximize the system throughput under the interference constraints. The numerical results show that as channel estimation error variance (CEEV) increases, the ARAMS scheme consistently outperforms other approaches in maximizing system throughput, except for the AIMS scheme.
{"title":"Adaptive Resource Allocation and Mode Switching for D2D Networks With Imperfect CSI in AGV-Based Factory Automation","authors":"Safiu A. Gbadamosi;Gerhard P. Hancke;Adnan M. Abu-Mahfouz","doi":"10.1109/OJVT.2024.3519135","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3519135","url":null,"abstract":"In industrial factory automation and control system, reliable communication for automated guided vehicles (AGVs) in dynamic, interference laden factory settings are essential particularly for real-time operations. Device-to-device (D2D) technology can enhance industrial network performance by offloading traffic and improving resource utilization. However, deploying D2D-enabled networks presents challenges such as interference control and imperfect channel state information (ICSI). In this paper, we investigate an adaptive resource allocation and mode switching strategy (ARAMS) in D2D-enabled industrial small cell (SC) networks with ICSI to maximize the system throughput and address reuse interference for AGVs. The ARAMS scheme integrates mode switching (MS), channel-quality factor (CQF), and power control (PC) within a bi-phasic resource-sharing (RS) algorithm to lower the computational complexity. In the initial phase, the operational mode for each D2D user (DU) per cell is adaptively selected based on the channel gain ratio (CGR). Subsequently, it computes the CQF for each cell with a reuse DU to identify an optimal reuse partner. The final phase employs the Lagrangian dual decomposition method to decide the DU's and industrial cellular users (CUs) optimum distributed power to maximize the system throughput under the interference constraints. The numerical results show that as channel estimation error variance (CEEV) increases, the ARAMS scheme consistently outperforms other approaches in maximizing system throughput, except for the AIMS scheme.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"288-300"},"PeriodicalIF":5.3,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10804206","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975792","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 : 2024-12-16DOI: 10.1109/OJVT.2024.3512052
Edward Au
{"title":"Editorial: Message From the Editor-in-Chief","authors":"Edward Au","doi":"10.1109/OJVT.2024.3512052","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3512052","url":null,"abstract":"","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"viii-viii"},"PeriodicalIF":5.3,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10803008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825779","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 : 2024-12-16DOI: 10.1109/OJVT.2024.3518621
Rafael P. Torres;Jesús R. Pérez
This paper presents a novel lower boundary for the coherence block (ChB) length in time-variant wireless channels. A rigorous estimation of the ChB length is important for the proper design of systems based on time division duplex-orthogonal frequency division multiplexing (TDD-OFDM). ChB length is especially relevant in the case of massive multiple input-multiple output (m-MIMO) systems, as it determines the overhead due to the massive channel estimation and, consequently, the spectral efficiency that can be achieved. The proposed boundary is based on a tractable propagation model, is related to easily obtainable channel parameters, and applicable to radio channels with temporal variation due to both the movement of the users and the movement of objects that surround them; including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and industrial Machine-to-Machine (M2M) communications.
{"title":"A Lower Boundary on the Length of the Coherence Block in Vehicular Communications Channels","authors":"Rafael P. Torres;Jesús R. Pérez","doi":"10.1109/OJVT.2024.3518621","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3518621","url":null,"abstract":"This paper presents a novel lower boundary for the coherence block (ChB) length in time-variant wireless channels. A rigorous estimation of the ChB length is important for the proper design of systems based on time division duplex-orthogonal frequency division multiplexing (TDD-OFDM). ChB length is especially relevant in the case of massive multiple input-multiple output (m-MIMO) systems, as it determines the overhead due to the massive channel estimation and, consequently, the spectral efficiency that can be achieved. The proposed boundary is based on a tractable propagation model, is related to easily obtainable channel parameters, and applicable to radio channels with temporal variation due to both the movement of the users and the movement of objects that surround them; including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and industrial Machine-to-Machine (M2M) communications.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"256-264"},"PeriodicalIF":5.3,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10804205","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905784","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 : 2024-12-12DOI: 10.1109/OJVT.2024.3490477
{"title":"IEEE Open Journal of Vehicular Technology Information for Authors","authors":"","doi":"10.1109/OJVT.2024.3490477","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3490477","url":null,"abstract":"","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"C4-C4"},"PeriodicalIF":5.3,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10795781","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810414","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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