Pub Date : 2024-09-13DOI: 10.1109/OJVT.2024.3460979
Varvara V. Elesina;Carla E. Reinhardt;Lennart Thielecke;Tobias Doeker;Thomas Kürner
This paper present an initial approach to the analysis of the stationarity of time-variant channels in industrial environments, focusing on three distinct scenarios: 1) communication between a static access point (AP) and a sensor node (SN) mounted on a moving machine within a comprehensive industrial workspace, 2) communication between two static sensor node (SN) with a moving metal plate object between them, and 3) communication between two static robotic manipulators with a moving obstacle with varying movement speeds between them. The assumptions of the wide-sense stationary (WSS) and uncorrelated scatering (US), fundamental to channel modeling, are examined using local scattering function (LSF) collinearity metrics in both time and frequency domains. In blockage scenarios, where we compared the effects of two different types of obstacles – a metal plate and a robotic arm – the channel behavior can be divided into three distinct regions: fully stationary before and after the blockage, non-stationary during the transition periods, and either conditionally stationary or fully non-stationary during partial or full blockage, respectively. These distinctions were influenced by the type of blockage object and whether the scenario involved non-line-of-sight (NLOS) or obstructed-line-of-sight (OLOS) conditions. Notably, the speed of moving obstacles affects the duration and nature of non-stationary regions, with higher speeds leading to shorter and less distinct transition periods. The US assumption was found to be generally valid in the blockage scenarios but not in the AP scenario.
本文提出了一种分析工业环境中时变信道静止性的初步方法，重点关注三种不同的场景：1) 在一个综合工业工作区内，一个静态接入点（AP）和一个安装在移动机器上的传感器节点（SN）之间的通信；2) 两个静态传感器节点（SN）之间的通信，它们之间有一个移动的金属板物体；3) 两个静态机器人机械手之间的通信，它们之间有一个移动的障碍物，移动速度各不相同。利用时域和频域的局部散射函数（LSF）共线性指标，对信道建模的基本假设--广义静止（WSS）和非相关散射（US）进行了检验。在阻塞情况下，我们比较了金属板和机械臂这两种不同类型障碍物的影响，信道行为可分为三个不同的区域：阻塞前后完全静止、过渡期间非静止、部分或完全阻塞期间分别为有条件静止或完全非静止。这些区别受到障碍物类型以及情景是否涉及非视线（NLOS）或视线受阻（OLOS）条件的影响。值得注意的是，移动障碍物的速度会影响非稳态区域的持续时间和性质，速度越快，过渡时间越短，越不明显。研究发现，US 假设在阻塞情况下基本有效，但在 AP 情况下无效。
{"title":"Investigating the WSSUS Assumption in 300 GHz Time-Variant Channels in Industrial Environments","authors":"Varvara V. Elesina;Carla E. Reinhardt;Lennart Thielecke;Tobias Doeker;Thomas Kürner","doi":"10.1109/OJVT.2024.3460979","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3460979","url":null,"abstract":"This paper present an initial approach to the analysis of the stationarity of time-variant channels in industrial environments, focusing on three distinct scenarios: 1) communication between a static access point (AP) and a sensor node (SN) mounted on a moving machine within a comprehensive industrial workspace, 2) communication between two static sensor node (SN) with a moving metal plate object between them, and 3) communication between two static robotic manipulators with a moving obstacle with varying movement speeds between them. The assumptions of the wide-sense stationary (WSS) and uncorrelated scatering (US), fundamental to channel modeling, are examined using local scattering function (LSF) collinearity metrics in both time and frequency domains. In blockage scenarios, where we compared the effects of two different types of obstacles – a metal plate and a robotic arm – the channel behavior can be divided into three distinct regions: fully stationary before and after the blockage, non-stationary during the transition periods, and either conditionally stationary or fully non-stationary during partial or full blockage, respectively. These distinctions were influenced by the type of blockage object and whether the scenario involved non-line-of-sight (NLOS) or obstructed-line-of-sight (OLOS) conditions. Notably, the speed of moving obstacles affects the duration and nature of non-stationary regions, with higher speeds leading to shorter and less distinct transition periods. The US assumption was found to be generally valid in the blockage scenarios but not in the AP scenario.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1374-1385"},"PeriodicalIF":5.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10680312","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-10DOI: 10.1109/OJVT.2024.3457499
Mamunur Rashid;Tarek Elfouly;Nan Chen
The transition of the automotive sector to electric vehicles (EVs) necessitates research on charging demand forecasting for optimal station placement and capacity planning. In the literature, extensive studies have been conducted on model-based and probabilistic EV charging demand forecasting schemes. The studies provide a solid research foundation but result in complicated models with limited scalability. Meanwhile, emerging machine learning techniques bring promising prospects, yet exhibit suboptimal performance with insufficient data. Additionally, existing studies often overlook several critical areas such as overcoming data scarcity, security and privacy concerns, managing the inherent stochasticity of demand data, selecting forecasting methods for a specific feature, and developing standardized performance metrics. Considering the impact of the research topic, EV charging demand forecasting demands careful study. In this paper, we present a comprehensive survey of EV charging demand forecasting, focusing on both probabilistic and learning algorithms. First, we introduce the general procedure of EV charging demand forecasting, encompassing data sources, data pre-processing, and the key EV features. We then provide a taxonomy of existing EV charging demand forecasting techniques, followed by a critical analysis and comparative study of state-of-the-art research. Finally, we discuss open issues, which offer useful insights and future direction for various stakeholders.
{"title":"A Comprehensive Survey of Electric Vehicle Charging Demand Forecasting Techniques","authors":"Mamunur Rashid;Tarek Elfouly;Nan Chen","doi":"10.1109/OJVT.2024.3457499","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3457499","url":null,"abstract":"The transition of the automotive sector to electric vehicles (EVs) necessitates research on charging demand forecasting for optimal station placement and capacity planning. In the literature, extensive studies have been conducted on model-based and probabilistic EV charging demand forecasting schemes. The studies provide a solid research foundation but result in complicated models with limited scalability. Meanwhile, emerging machine learning techniques bring promising prospects, yet exhibit suboptimal performance with insufficient data. Additionally, existing studies often overlook several critical areas such as overcoming data scarcity, security and privacy concerns, managing the inherent stochasticity of demand data, selecting forecasting methods for a specific feature, and developing standardized performance metrics. Considering the impact of the research topic, EV charging demand forecasting demands careful study. In this paper, we present a comprehensive survey of EV charging demand forecasting, focusing on both probabilistic and learning algorithms. First, we introduce the general procedure of EV charging demand forecasting, encompassing data sources, data pre-processing, and the key EV features. We then provide a taxonomy of existing EV charging demand forecasting techniques, followed by a critical analysis and comparative study of state-of-the-art research. Finally, we discuss open issues, which offer useful insights and future direction for various stakeholders.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1348-1373"},"PeriodicalIF":5.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10670452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-09DOI: 10.1109/OJVT.2024.3456035
Jose Matute;Sergio Diaz;Ali Karimoddini
Achieving robust path tracking is essential for efficiently operating autonomous driving systems, particularly in unpredictable environments. This paper introduces a novel path-tracking control methodology utilizing a variable second-order Sliding Mode Control (SMC) approach. The proposed control strategy addresses the challenges posed by uncertainties and disturbances by reconfiguring and expanding the state-space matrix of a kinematic bicycle model guaranteeing Lyapunov stability and convergence of the system. A state prediction is integrated into the developed SMC to mitigate response time delays. Furthermore, the controller integrates adaptive mechanisms to adjust time-varying parameters within the control formulation based on longitudinal velocity, thereby enhancing path-tracking performance and reducing chattering phenomena. The effectiveness of the proposed approach is comprehensively evaluated through simulations and experiments encompassing challenging driving scenarios characterized by high-curvature paths, varying altitudes, and sensor disturbances, typical in rural driving environments. Results demonstrate that disturbances have varying impacts depending on the type of sensor affected. Real-world tests validate these findings, offering practical insights for automated vehicle path-tracking implementation.
{"title":"Sliding Mode Control for Robust Path Tracking of Automated Vehicles in Rural Environments","authors":"Jose Matute;Sergio Diaz;Ali Karimoddini","doi":"10.1109/OJVT.2024.3456035","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3456035","url":null,"abstract":"Achieving robust path tracking is essential for efficiently operating autonomous driving systems, particularly in unpredictable environments. This paper introduces a novel path-tracking control methodology utilizing a variable second-order Sliding Mode Control (SMC) approach. The proposed control strategy addresses the challenges posed by uncertainties and disturbances by reconfiguring and expanding the state-space matrix of a kinematic bicycle model guaranteeing Lyapunov stability and convergence of the system. A state prediction is integrated into the developed SMC to mitigate response time delays. Furthermore, the controller integrates adaptive mechanisms to adjust time-varying parameters within the control formulation based on longitudinal velocity, thereby enhancing path-tracking performance and reducing chattering phenomena. The effectiveness of the proposed approach is comprehensively evaluated through simulations and experiments encompassing challenging driving scenarios characterized by high-curvature paths, varying altitudes, and sensor disturbances, typical in rural driving environments. Results demonstrate that disturbances have varying impacts depending on the type of sensor affected. Real-world tests validate these findings, offering practical insights for automated vehicle path-tracking implementation.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1314-1325"},"PeriodicalIF":5.3,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10669799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142377112","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}
A perturbation-based nulling control beamforming (PNCB) scheme is proposed to effectively mitigate multi-user interference (MUI) in multi-user massive multiple-input multiple-output (MU-mMIMO) systems. This is achieved through the precise alignment of deep and wide radiation nulls in the potential interference directions, considering the realistic heterogeneous element radiation patterns (ERPs). Utilizing measured ERPs from an 8 × 8 antenna array prototype, this study conducts a thorough analysis of ERP variations across different positions in the array. The ERP symmetry knowledge is leveraged to enhance the optimization efficiency by reapplying optimized beamforming vectors to symmetric sub-arrays. The proposed PNCB scheme initiates optimization with weights derived from the linearly constrained minimum variance approach, followed by strategic weight perturbations implemented with particle swarm optimization. This process fine-tunes the sub-optimal beamforming vectors to address discrepancies caused by non-uniform ERPs. Illustrative results demonstrate interference suppression levels exceeding 52.4 dB in multi-user scenarios, without significantly affecting the main-lobe radiation patterns. The nulling width control algorithm achieves an average nulling level ranging from −45.3 dB to −57.7 dB across a 6-degree angle span. Further studies delve into the impact of attenuator and phase-shifter quantization on the nulling level, offering insights into performance variations with different hardware configurations. Experimental validation in an anechoic chamber, involving two users with distinct 20 MHz modulation signals, confirms the effectiveness of the proposed PNCB approach, ensuring reliable and efficient communication in MU-mMIMO systems. The results demonstrate an average enhancement of 22.0 dB in the signal-to-interference ratio, effectively reducing the MUI to near the noise floor. The efficacy of the proposed PNCB scheme is further evidenced by the high-quality received constellation diagrams, with enhanced error vector magnitude performance.
{"title":"Perturbation-Based Nulling Control Beamforming With Measured Element Radiation Patterns for MU-mMIMO","authors":"Yuanzhe Gong;Arish Yaseen;Tingrui Zhang;Robert Morawski;Tho Le-Ngoc","doi":"10.1109/OJVT.2024.3453951","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3453951","url":null,"abstract":"A perturbation-based nulling control beamforming (PNCB) scheme is proposed to effectively mitigate multi-user interference (MUI) in multi-user massive multiple-input multiple-output (MU-mMIMO) systems. This is achieved through the precise alignment of deep and wide radiation nulls in the potential interference directions, considering the realistic heterogeneous element radiation patterns (ERPs). Utilizing measured ERPs from an 8 × 8 antenna array prototype, this study conducts a thorough analysis of ERP variations across different positions in the array. The ERP symmetry knowledge is leveraged to enhance the optimization efficiency by reapplying optimized beamforming vectors to symmetric sub-arrays. The proposed PNCB scheme initiates optimization with weights derived from the linearly constrained minimum variance approach, followed by strategic weight perturbations implemented with particle swarm optimization. This process fine-tunes the sub-optimal beamforming vectors to address discrepancies caused by non-uniform ERPs. Illustrative results demonstrate interference suppression levels exceeding 52.4 dB in multi-user scenarios, without significantly affecting the main-lobe radiation patterns. The nulling width control algorithm achieves an average nulling level ranging from −45.3 dB to −57.7 dB across a 6-degree angle span. Further studies delve into the impact of attenuator and phase-shifter quantization on the nulling level, offering insights into performance variations with different hardware configurations. Experimental validation in an anechoic chamber, involving two users with distinct 20 MHz modulation signals, confirms the effectiveness of the proposed PNCB approach, ensuring reliable and efficient communication in MU-mMIMO systems. The results demonstrate an average enhancement of 22.0 dB in the signal-to-interference ratio, effectively reducing the MUI to near the noise floor. The efficacy of the proposed PNCB scheme is further evidenced by the high-quality received constellation diagrams, with enhanced error vector magnitude performance.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1273-1293"},"PeriodicalIF":5.3,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10663863","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274920","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}
Terahertz (THz) communication is a cutting-edge technology for the sixth-generation (6G) networks, offering vast bandwidths and data rates up to terabits per second, significantly advancing vehicular connectivity and services. However, THz signals are impacted by attenuation, path loss, and beam misalignment. Furthermore, the requisite high Nyquist sampling rates for THz systems increase the computational and system complexity of the receiver. A promising solution to navigate these obstacles involves the use of intelligent reflecting surfaces (IRS)-enhanced multiple-input multiple-output (MIMO) technology, which steers THz wave propagation. However, the substantial dimensions associated with IRS and MIMO extend the near-field, particularly at THz frequencies, as indicated by the Rayleigh distance and suffer from beam squint. To reduce system complexity and reduce sampling to sub-Nyquist rate, we propose a novel receiver design for an IRS-assisted near-field MIMO THz system that employs low-complexity compressed sensing. This method introduces an IRS signal-matched (IRSSM) measurement matrix with beam squint for capturing the transmitted signal at a sub-Nyquist rate, taking advantage of the sparsity in the signal and THz channels, and signal recovery using the deep learning (DL) model. Simulation results for symbol error rate (SER) and normalized mean square error (NMSE) performance indicate that the proposed DL-based receiver outperforms conventional recovery algorithms based on orthogonal matching pursuit (OMP) CS-recovery and dictionary-shrinkage estimation (DSE).
{"title":"Deep Learning Model for CS-Based Signal Recovery for IRS-Assisted Near-Field THz MIMO System","authors":"Vaishali Sharma;Prakhar Keshari;Sanjeev Sharma;Kuntal Deka;Ondrej Krejcar;Vimal Bhatia","doi":"10.1109/OJVT.2024.3452412","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3452412","url":null,"abstract":"Terahertz (THz) communication is a cutting-edge technology for the sixth-generation (6G) networks, offering vast bandwidths and data rates up to terabits per second, significantly advancing vehicular connectivity and services. However, THz signals are impacted by attenuation, path loss, and beam misalignment. Furthermore, the requisite high Nyquist sampling rates for THz systems increase the computational and system complexity of the receiver. A promising solution to navigate these obstacles involves the use of intelligent reflecting surfaces (IRS)-enhanced multiple-input multiple-output (MIMO) technology, which steers THz wave propagation. However, the substantial dimensions associated with IRS and MIMO extend the near-field, particularly at THz frequencies, as indicated by the Rayleigh distance and suffer from beam squint. To reduce system complexity and reduce sampling to sub-Nyquist rate, we propose a novel receiver design for an IRS-assisted near-field MIMO THz system that employs low-complexity compressed sensing. This method introduces an IRS signal-matched (IRSSM) measurement matrix with beam squint for capturing the transmitted signal at a sub-Nyquist rate, taking advantage of the sparsity in the signal and THz channels, and signal recovery using the deep learning (DL) model. Simulation results for symbol error rate (SER) and normalized mean square error (NMSE) performance indicate that the proposed DL-based receiver outperforms conventional recovery algorithms based on orthogonal matching pursuit (OMP) CS-recovery and dictionary-shrinkage estimation (DSE).","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1326-1335"},"PeriodicalIF":5.3,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10660298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376540","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}
Unmanned aerial vehicles (UAVs) are becoming increasingly popular as mobile base stations due to their flexible deployment and low-cost features, particularly for emergency communications, traffic offloading, and terrestrial communications infrastructure failures. This paper presents an autonomous trajectory control method for multiple UAVs equipped with base stations for UAV-enabled wireless communications. The objective of this work is to address the optimization challenge of maximizing both communication coverage and network throughput for ground users. The proposed multi-aerial base station trajectory control (MATC) scheme employs a two-stage learning approach. Initially, we developed a long short-term memory-based link quality estimation model to assess each user's link quality over time. The trajectory of the aerial base stations is then continuously adjusted through a centralized multi-agent deep reinforcement learning algorithm to optimize communication performance. We evaluated our proposed system using real channel measurement data, i.e., amplitude and phase signal information. Notably, the proposed approach operates solely on received signals from users, without requiring knowledge of their specific locations. The proposed MATC strategy achieves 97.41% communication coverage while maintaining satisfactory system throughput performance. Numerical results demonstrate that the proposed method significantly enhances both communication coverage and network throughput in comparison to the base line algorithms.
{"title":"A Centralized Multi-Agent DRL-Based Trajectory Control Strategy for Unmanned Aerial Vehicle-Enabled Wireless Communications","authors":"Getaneh Berie Tarekegn;Rong-Terng Juang;Belayneh Abebe Tesfaw;Hsin-Piao Lin;Huan-Chia Hsu;Robel Berie Tarekegn;Li-Chia Tai","doi":"10.1109/OJVT.2024.3451143","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3451143","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are becoming increasingly popular as mobile base stations due to their flexible deployment and low-cost features, particularly for emergency communications, traffic offloading, and terrestrial communications infrastructure failures. This paper presents an autonomous trajectory control method for multiple UAVs equipped with base stations for UAV-enabled wireless communications. The objective of this work is to address the optimization challenge of maximizing both communication coverage and network throughput for ground users. The proposed multi-aerial base station trajectory control (MATC) scheme employs a two-stage learning approach. Initially, we developed a long short-term memory-based link quality estimation model to assess each user's link quality over time. The trajectory of the aerial base stations is then continuously adjusted through a centralized multi-agent deep reinforcement learning algorithm to optimize communication performance. We evaluated our proposed system using real channel measurement data, i.e., amplitude and phase signal information. Notably, the proposed approach operates solely on received signals from users, without requiring knowledge of their specific locations. The proposed MATC strategy achieves 97.41% communication coverage while maintaining satisfactory system throughput performance. Numerical results demonstrate that the proposed method significantly enhances both communication coverage and network throughput in comparison to the base line algorithms.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1230-1241"},"PeriodicalIF":5.3,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10654501","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235822","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 study proposes a dynamic full-duplex cellular (DDC) system by introducing an in-band full-duplex in a phased manner into a conventional time-division duplex (TDD)-based cellular system. Further, we propose and evaluate appropriate user equipment (UE) scheduling and transmission power control schemes for DDC in dense urban multi-cell environments. The proposed DDC sufficiently suppresses inter-cell interference through fully distributed resource allocation, which does not require information exchange among neighboring cells. In particular, the propagation loss compensation factor, UE transmission power limit, and assumed uplink signal-to-noise plus interference power ratio (SINR) adjustment factor prove to be essential. By appropriately setting these factors, the proposed DDC system improves the average throughput of the downlink (DL) by 13.2% and uplink by 31.6% compared with the conventional TDD system. Moreover, we observe a 2.5% improvement in the DL 5% user throughput. The results of this study are expected to contribute to the realization of a high-capacity wide-area IoT network backbone by improving the efficiency of utilization of limited spectral resources, especially in the sub-6 GHz band.
{"title":"Dynamic Full-Duplex Cellular System for Wide Area IoT Network Backbone","authors":"Keiichi Mizutani;Kazuki Nishikori;Kyoya Teramae;Hiroto Kuriki;Takeshi Matsumura;Hiroshi Harada","doi":"10.1109/OJVT.2024.3450279","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3450279","url":null,"abstract":"This study proposes a dynamic full-duplex cellular (DDC) system by introducing an in-band full-duplex in a phased manner into a conventional time-division duplex (TDD)-based cellular system. Further, we propose and evaluate appropriate user equipment (UE) scheduling and transmission power control schemes for DDC in dense urban multi-cell environments. The proposed DDC sufficiently suppresses inter-cell interference through fully distributed resource allocation, which does not require information exchange among neighboring cells. In particular, the propagation loss compensation factor, UE transmission power limit, and assumed uplink signal-to-noise plus interference power ratio (SINR) adjustment factor prove to be essential. By appropriately setting these factors, the proposed DDC system improves the average throughput of the downlink (DL) by 13.2% and uplink by 31.6% compared with the conventional TDD system. Moreover, we observe a 2.5% improvement in the DL 5% user throughput. The results of this study are expected to contribute to the realization of a high-capacity wide-area IoT network backbone by improving the efficiency of utilization of limited spectral resources, especially in the sub-6 GHz band.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1215-1229"},"PeriodicalIF":5.3,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648807","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142230853","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 : 2024-08-23DOI: 10.1109/OJVT.2024.3449144
Stefano Caputo;Stefano Ricci;Lorenzo Mucchi
This article presents a thorough investigation into the contrasting dynamics of full-duplex and half-duplex communication within the framework of visible light communication (VLC) networks compliant with the IEEE 802.15.7 standard. The main contributions of this research deal with Field Programmable Gate Array (FPGA) implementation, experimental data acquisition, interference evaluation, and performance assessment. In particular, the study delves into implementing both full-duplex and half-duplex communication schemes using FPGA technology for vehicular communications compliant to the IEEE 802.15.7 standard. Full-duplex is obtained by simultaneously transmitting over the same optical channel, without any multiplexing or access division strategy. Through experimental data acquisition, the paper provides a detailed comparison of the two communication schemes, shedding light on their respective strengths and limitations. Furthermore, the paper introduces an interference evaluation framework, which contributes to the understanding of the real benefits of full-duplex VLC through theoretical modeling of the interference and experimental validation. The performance evaluation section quantifies key metrics, allowing for a comprehensive assessment of the overall efficacy of full-duplex and half-duplex VLC systems in a vehicular network context. This research offers a perspective on the practical implications and trade-offs associated with adopting either half- and full-duplex VLC communication paradigm, paving the way for informed decision-making in the design and deployment of intelligent transportation systems (ITS) based on IEEE 802.15.7 networks.
{"title":"IEEE 802.15.7-Compliant Full Duplex Visible Light Communication: Interference Analysis and Experimentation","authors":"Stefano Caputo;Stefano Ricci;Lorenzo Mucchi","doi":"10.1109/OJVT.2024.3449144","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3449144","url":null,"abstract":"This article presents a thorough investigation into the contrasting dynamics of full-duplex and half-duplex communication within the framework of visible light communication (VLC) networks compliant with the IEEE 802.15.7 standard. The main contributions of this research deal with Field Programmable Gate Array (FPGA) implementation, experimental data acquisition, interference evaluation, and performance assessment. In particular, the study delves into implementing both full-duplex and half-duplex communication schemes using FPGA technology for vehicular communications compliant to the IEEE 802.15.7 standard. Full-duplex is obtained by simultaneously transmitting over the same optical channel, without any multiplexing or access division strategy. Through experimental data acquisition, the paper provides a detailed comparison of the two communication schemes, shedding light on their respective strengths and limitations. Furthermore, the paper introduces an interference evaluation framework, which contributes to the understanding of the real benefits of full-duplex VLC through theoretical modeling of the interference and experimental validation. The performance evaluation section quantifies key metrics, allowing for a comprehensive assessment of the overall efficacy of full-duplex and half-duplex VLC systems in a vehicular network context. This research offers a perspective on the practical implications and trade-offs associated with adopting either half- and full-duplex VLC communication paradigm, paving the way for informed decision-making in the design and deployment of intelligent transportation systems (ITS) based on IEEE 802.15.7 networks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1242-1255"},"PeriodicalIF":5.3,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10645235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235937","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 : 2024-08-21DOI: 10.1109/OJVT.2024.3447449
Luis-Bernardo Hernandez-Salinas;Juan Terven;E. A. Chavez-Urbiola;Diana-Margarita Córdova-Esparza;Julio-Alejandro Romero-González;Amadeo Arguelles;Ilse Cervantes
In the fast-growing automotive technology sector, it has become increasingly clear that there is a need for cars with smarter and more interactive systems. This article presents the Intelligent Driving Assistance System (IDAS), an artificial intelligence system that enables the driver to use voice commands to access various features of a car. The primary component of IDAS is a Large Language Model (LLM), which, through retrieval augmented generation (RAG), can efficiently read and understand the car manual for immediate context-based aid. In addition, this system incorporates speech recognition and speech synthesis capabilities, it can understand commands given in multiple languages, improving user experiences among diverse driver communities. Our results show a minimum response time of one second for the pipeline using GPT-4o-mini and Mistral Nemo.
{"title":"IDAS: Intelligent Driving Assistance System Using RAG","authors":"Luis-Bernardo Hernandez-Salinas;Juan Terven;E. A. Chavez-Urbiola;Diana-Margarita Córdova-Esparza;Julio-Alejandro Romero-González;Amadeo Arguelles;Ilse Cervantes","doi":"10.1109/OJVT.2024.3447449","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3447449","url":null,"abstract":"In the fast-growing automotive technology sector, it has become increasingly clear that there is a need for cars with smarter and more interactive systems. This article presents the Intelligent Driving Assistance System (IDAS), an artificial intelligence system that enables the driver to use voice commands to access various features of a car. The primary component of IDAS is a Large Language Model (LLM), which, through retrieval augmented generation (RAG), can efficiently read and understand the car manual for immediate context-based aid. In addition, this system incorporates speech recognition and speech synthesis capabilities, it can understand commands given in multiple languages, improving user experiences among diverse driver communities. Our results show a minimum response time of one second for the pipeline using GPT-4o-mini and Mistral Nemo.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1139-1165"},"PeriodicalIF":5.3,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643289","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142159101","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}
In recent years, research on reconfigurable intelligent surface (RIS) has received extensive attention due to its capability to manipulate the propagation of incident electromagnetic waves in a programmable manner to smartly configure the channel environment, thereby optimizing the overall performance of the system. Several RIS architectures have been proposed, including simultaneous transmitting and reflecting RIS (STAR-RIS) and beyond diagonal RIS (BD RIS) architectures. Compared to the conventional RIS architecture, these structures offer broader service ranges and enhanced performance, albeit accompanied by more complex circuit design and higher computational overhead. In this paper, we design a multi-sector RIS joint service model based on the BD RIS architecture and we compare the corresponding system rates, circuit complexity, and gains provided by different architectures. Additionally, we derive the theoretical receive power for the proposed model based on non-diagonal and diagonal phase shift optimization methods, demonstrating that the total rate of the non-diagonal group connected architecture approaches the theoretical values of a fully connected architecture. Theoretical analysis based on the gains between different models under various user-RIS positions confirm that the multi-sector RIS joint service model can achieve $30%-100%$ gains as the users' positions change, while also saving on the overall hardware costs of the RIS system design. Furthermore, we explore the optimal trade-off between the performance and circuit complexity among different architectures. Simulation results show that performance versus complexity trade-off of the different considered architectures.
{"title":"Reconfigurable Intelligent Surface Relying on Low-Complexity Joint Sector Non-Diagonal Structure","authors":"Yinuo Dong;Qingchao Li;Soon Xin Ng;Mohammed El-Hajjar","doi":"10.1109/OJVT.2024.3447109","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3447109","url":null,"abstract":"In recent years, research on reconfigurable intelligent surface (RIS) has received extensive attention due to its capability to manipulate the propagation of incident electromagnetic waves in a programmable manner to smartly configure the channel environment, thereby optimizing the overall performance of the system. Several RIS architectures have been proposed, including simultaneous transmitting and reflecting RIS (STAR-RIS) and beyond diagonal RIS (BD RIS) architectures. Compared to the conventional RIS architecture, these structures offer broader service ranges and enhanced performance, albeit accompanied by more complex circuit design and higher computational overhead. In this paper, we design a multi-sector RIS joint service model based on the BD RIS architecture and we compare the corresponding system rates, circuit complexity, and gains provided by different architectures. Additionally, we derive the theoretical receive power for the proposed model based on non-diagonal and diagonal phase shift optimization methods, demonstrating that the total rate of the non-diagonal group connected architecture approaches the theoretical values of a fully connected architecture. Theoretical analysis based on the gains between different models under various user-RIS positions confirm that the multi-sector RIS joint service model can achieve \u0000<inline-formula><tex-math>$30%-100%$</tex-math></inline-formula>\u0000 gains as the users' positions change, while also saving on the overall hardware costs of the RIS system design. Furthermore, we explore the optimal trade-off between the performance and circuit complexity among different architectures. Simulation results show that performance versus complexity trade-off of the different considered architectures.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1106-1123"},"PeriodicalIF":5.3,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643263","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137546","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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