IEEE Open Journal of Vehicular Technology最新文献

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}

{"title":"Large Language Models for UAVs: Current State and Pathways to the Future","authors":"Shumaila Javaid;Hamza Fahim;Bin He;Nasir Saeed","doi":"10.1109/OJVT.2024.3446799","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3446799","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) have emerged as a transformative technology across diverse sectors, offering adaptable solutions to complex challenges in both military and civilian domains. Their expanding capabilities present a platform for further advancement by integrating cutting-edge computational tools like Artificial Intelligence (AI) and Machine Learning (ML) algorithms. These advancements have significantly impacted various facets of human life, fostering an era of unparalleled efficiency and convenience. Large Language Models (LLMs), a key component of AI, exhibit remarkable learning and adaptation capabilities within deployed environments, demonstrating an evolving form of intelligence with the potential to approach human-level proficiency. This work explores the significant potential of integrating UAVs and LLMs to propel the development of autonomous systems. We comprehensively review LLM architectures, evaluating their suitability for UAV integration. Additionally, we summarize the state-of-the-art LLM-based UAV architectures and identify novel opportunities for LLM embedding within UAV frameworks. Notably, we focus on leveraging LLMs to refine data analysis and decision-making processes, specifically for enhanced spectral sensing and sharing in UAV applications. Furthermore, we investigate how LLM integration expands the scope of existing UAV applications, enabling autonomous data processing, improved decision-making, and faster response times in emergency scenarios like disaster response and network restoration. Finally, we highlight crucial areas for future research that are critical for facilitating the effective integration of LLMs and UAVs.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1166-1192"},"PeriodicalIF":5.3,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643253","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169712","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}

{"title":"Utilizing Partial Non-Orthogonal Multiple Access (P-NOMA) in Drone-Enabled Internet-of-Things Wireless Networks","authors":"Hazim Shakhatreh;Sharief Abdel-Razeq;Ala Al-Fuqaha","doi":"10.1109/OJVT.2024.3445768","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3445768","url":null,"abstract":"Future drone-enabled Internet-of-Things (IoT) wireless networks have attracted considerable attention from industry and academia. Future drone-enabled IoT wireless networks are expected to enable the Internet of Everything and provide services with massive connectivity, heterogeneous quality of service, ultra-reliability, and higher throughput. Therefore, future drone-enabled IoT wireless networks necessitate more effective use of wireless resources and efficient interference management approaches. As a result, the multiple access techniques and the physical layer for wireless communication systems have been rethought and redesigned. This paper proposes utilizing the partial non-orthogonal multiple access (P-NOMA) in drone-enabled IoT wireless networks, where a single drone provides wireless coverage for a set of IoT devices. In P-NOMA, a portion of the channel is orthogonal, while the other is non-orthogonal for each IoT device. When using a non-orthogonal channel portion, an IoT device that receives high transmit power from the drone treats a signal of another IoT device as noise and quickly recovers its signal without using a successive interference cancellation (SIC) process. However, an IoT device that receives low transmit power from that drone must perform the SIC process on a non-orthogonal channel portion to recover its signal. The optimization problem in this research aims to find the maximum sum data rate of all IoT devices, considering the 3D placement of the drone, device pairing, and the parameters of P-NOMA. Finding the optimal solution to the optimization problem is challenging because of the NP-completeness of the formulated problem. Therefore, a decomposition framework is proposed to aid in solving it. Particularly, the optimization problem is decomposed into three subproblems: the 3D placement for the drone, device pairing, and P-NOMA parameters. Then efficient techniques are proposed to solve these subproblems. Simulation results verify the efficacy of utilizing P-NOMA in drone-enabled IoT wireless networks. Specifically, our results demonstrate that P-NOMA can boost the sum rate by 22%–28% compared with NOMA and by 83%–104% compared with OMA.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1088-1105"},"PeriodicalIF":5.3,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10640187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090964","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}

{"title":"Navigating the Handover: Reviewing Takeover Requests in Level 3 Autonomous Vehicles","authors":"Joel Andrew Miller;Soodeh Nikan;Mohamed H. Zaki","doi":"10.1109/OJVT.2024.3443630","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3443630","url":null,"abstract":"Autonomous vehicles (AVs) represent a transformative advance in automotive technology, promising increased safety and efficiency by reducing human error. However, integrating human factors remains a critical challenge, especially during takeover scenarios where the human driver must re-assume control of the vehicle. This review paper focuses on the \u0000<italic>engineering and human-centred design of takeover requests (TORs) within Level 3 autonomous vehicles</i>\u0000, emphasizing the importance of seamless transitions between automated driving and manual control. We explore the concept of the Operational Design Domain (ODD), which dictates the specific conditions under which an AV may safely operate, and contextualize its role. Through a comprehensive analysis, we highlight how monitoring both the internal and external environment, and improving human-machine interfaces through the design of takeover requests (TOR), play pivotal roles in ensuring that transitions are safe and efficient. We argue for the necessity of integrating detailed human factors and ergonomic considerations to foster a human-centred approach in AV design. We aim to establish a symbiotic relationship between human drivers and autonomous systems, ensuring that AVs not only function optimally within their designated ODD, but also maintain high safety standards during critical takeover moments.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1073-1087"},"PeriodicalIF":5.3,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10637755","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090965","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}