IEEE Open Journal of Vehicular Technology最新文献

{"title":"A Low Complexity Linear Precoding Method for Extremely Large-Scale MIMO Systems","authors":"Salah Berra;Abderrazak Benchabane;Sourav Chakraborty;Kazuki Maruta;Rui Dinis;Marko Beko","doi":"10.1109/OJVT.2024.3514749","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3514749","url":null,"abstract":"Massive multiple-input multiple-output (MIMO) systems are critical technologies for the next generation of networks. In this field of research, new forms of deployment are emerging, such as extremely large-scale MIMO (XL-MIMO), in which the antenna array at the base station (BS) is of extreme dimensions. As a result, spatial non-stationary features emerge as users view just a section of the antenna array, known as the visibility regions (VRs). The XL-MIMO systems can achieve higher spectral efficiency, improve cell coverage, and provide significantly higher data rates than standard MIMO systems. It is a promising technology for future sixth-generation (6G) networks. However, due to the large number of antennas, linear precoding algorithms such as Zero-Forcing (ZF) and regularized Zero-Forcing (RZF) methods suffer from unacceptable computational complexity, primarily due to the required matrix inversion. This work aims to develop low-complexity precoding techniques for the downlink XL-MIMO system. These low-complexity linear precoding methods are based on Gauss-Seidel (GS) and Successive Over-Relaxation (SOR) techniques, which avoid calculating the complex matrix inversion and lead to stable linear precoding performance. To further enhance linear precoding performance, we incorporate the Chebyshev acceleration method with the SOR and GS methods, referred to as the Cheby-SOR and Cheby-GS methods. As these proposed methods require optimizing parameters, we create a deep unfolded network (DUN) to optimize the algorithm parameters. Our performance results demonstrate that the proposed method significantly reduces computational complexity from to \u0000<inline-formula><tex-math>$mathcal {O}(K^{2})$</tex-math></inline-formula>\u0000, where \u0000<inline-formula><tex-math>$K$</tex-math></inline-formula>\u0000 represents the number of users. Moreover, our approach outperforms the original algorithms, requiring only a few iterations to achieve the RZF bit error rate (BER) performance.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"240-255"},"PeriodicalIF":5.3,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10787224","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905783","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":"Optimal Linear Precoding Under Realistic Satellite Communications Scenarios","authors":"Geoffrey Eappen;Jorge Luis Gonzalez;Vibhum Singh;Rakesh Palisetty;Alireza Haqiqtnejad;Liz Martinez Marrero;Jevgenij Krivochiza;Jorge Querol;Nicola Maturo;Juan Carlos Merlano Duncan;Eva Lagunas;Stefano Andrenacci;Symeon Chatzinotas","doi":"10.1109/OJVT.2024.3509646","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3509646","url":null,"abstract":"In this paper, optimal linear precoding for the multibeam geostationary earth orbit (GEO) satellite with the multi-user (MU) multiple-input-multiple-output (MIMO) downlink scenario is addressed. Multiple-user interference is one of the major issues faced by the satellites serving the multiple users operating at the common time-frequency resource block in the downlink channel. To mitigate this issue, the optimal linear precoders are implemented at the gateways (GWs). The precoding computation is performed by utilizing the channel state information obtained at user terminals (UTs). The optimal linear precoders are derived considering beamformer update and power control with an iterative per-antenna power optimization algorithm with a limited required number of iterations. The efficacy of the proposed algorithm is validated using the In-Lab experiment for 16 × 16 precoding with multi-beam satellite for transmitting and receiving the precoded data with digital video broadcasting satellite-second generation extension (DVB-S2X) standard for the GW and the UTs. The software defined radio platforms are employed for emulating the GWs, UTs, and satellite links. The validation is supported by comparing the proposed optimal linear precoder with full frequency reuse (FFR), and minimum mean square error (MMSE) schemes. The experimental results demonstrate that with the optimal linear precoders it is possible to successfully cancel the inter-user interference in the simulated satellite FFR link. Thus, optimal linear precoding brings gains in terms of enhanced signal-to-noise-and-interference ratio, and increased system throughput and spectral efficiency.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"81-91"},"PeriodicalIF":5.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10772061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825893","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":"Optimizing Small Cell Performance: A New MIMO Paradigm With Distributed ASTAR-RISs","authors":"Shakil Ahmed;Ahmed E. Kamal;Mohamed Y. Selim;Md Akbar Hossain;Saifur Rahman Sabuj","doi":"10.1109/OJVT.2024.3509736","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3509736","url":null,"abstract":"As the demand for high-speed data transmission grows with the expected emergence of 6G networks and the proliferation of wireless devices, more than traditional wireless infrastructure may be required. Small cell networks (ScNs) integrated with reconfigurable intelligent surfaces (RISs) and multiple-inputmultiple-output (MIMO) have emerged as promising solutions to address this issue. However, ScNs have resource allocation limitations, and traditional RISs can only reflect signals in a limited propagation space of 1800 with fixed reflection properties. This paper proposes a novel approach to overcome these challenges by introducing actively simultaneously transmitting and reflecting (ASTAR)-RISs. Unlike conventional RIS, ASTAR-RISs actively amplify and transmit signals, effectively mitigating the limited propagation challenge and improving signal strength, especially in dense ScNs. This approach enhances the quality of service in complex channel environments by amplifying, on top of reflection, from the macro base station (mBS), improving the overall signal strength, and providing 3600 flexible propagation space. Furthermore, ASTAR-RIS enables dynamic beam management, significantly improving signal coverage and interference management, which are crucial in dense deployments. In this work, we propose a network architecture where distributed ASTAR-RIS units are deployed to assist small cell mBSs by optimizing signal coverage and enhancing communication performance. ASTAR-RISs dynamically control signal reflection and amplification, complementing the functionality of traditional small-cell BSs in dense network environments. Using the MIMO technique, we design phase shifts for ASTAR elements and develop optimal hybrid beamforming for users at the mBS. We dynamically control the ON/OFF status of the ASTAR-RIS based on active or idle status. We propose an efficient model that ensures fairness of signal-to-noise ratio (SNR) for all users and minimizes overall power consumption while meeting user SNR and phase shift constraints. To this end, we integrate robust beamforming and power allocation strategies, ensuring the system maintains reliable performance even under imperfect channel state information (CSI). We formulate a max-min optimization problem that optimizes the SNR and power consumption, subject to the ON/OFF status, phase shift, and power budget of the ASTAR-RIS. Our proposed method uses an alternating optimization algorithm to optimize the phase shift matrix at the ASTAR-RIS and the hybrid beamforming at the mBS. The approach includes two transmission schemes, and the phase optimization problem is solved using a successive convex approximation method that offers a closed-form solution at each step. Additionally, we use the dual method to determine the optimal ON/OFF status of the ASTAR-RIS. Comprehensive simulations validate the robustness and scalability of our proposed solution, particularly under varying network densities and CSI uncertaint","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"128-144"},"PeriodicalIF":5.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10772072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859068","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":"Conditioned Adaptive Barrier Function Based Integral Super-Twisting Sliding Mode Control for Electric Vehicles With Hybrid Energy Storage System","authors":"Afaq Ahmed;Iftikhar Ahmad;Habibur Rehman;Ammar Hasan","doi":"10.1109/OJVT.2024.3509686","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3509686","url":null,"abstract":"This paper proposes a conditioned adaptive barrier function-based integral super-twisting sliding mode controller for the hybrid energy storage system (HESS) with a field-oriented control of 3-phase induction motor for the electric vehicles (EVs). The conditioned approach ensures that the control input stays within bounds, the adaptive barrier adjusts the sliding mode controller (SMC) gains, and the super-twisting technique helps in reducing the chattering. Consequently, the overall system performance is improved. The HESS consists of a fuel cell, battery, and super-capacitor. A rule-based energy management system has been designed, defining different modes of operation for an efficient use of energy sources under different loading conditions. The designed energy management system accounts for the power inflow and the status of the energy sources. The proposed controller ensures smooth energy sources current tracking and stabilizes the DC bus voltage while controlling the motor speed and flux under various operating conditions. The controller's global asymptotic stability has been verified through Lyapunov stability analysis. Intensive computer simulations using Matlab/Simulink are performed to validate the proposed controller's performance and compare it with the conventional PI and SMC controllers. Finally, controller hardware-in-the-loop validation has been conducted for the real-time performance validation.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"92-108"},"PeriodicalIF":5.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10772067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844588","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":"Unified 3D Networks: Architecture, Challenges, Recent Results, and Future Opportunities","authors":"Mohamed Rihan;Dirk Wübben;Abhipshito Bhattacharya;Marina Petrova;Xiaopeng Yuan;Anke Schmeink;Amina Fellan;Shreya Tayade;Mervat Zarour;Daniel Lindenschmitt;Hans Schotten;Armin Dekorsy","doi":"10.1109/OJVT.2024.3508026","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3508026","url":null,"abstract":"The very new evolution towards 6G networks necessitates a paradigm shift towards unified 3D network architectures, encompassing space, air, and ground segments. This paper outlines the conceptualization, challenges, and prospects of such a transformative architecture. We outline the foundational principles, drawn from standardization endeavors and cutting-edge research initiatives, to articulate the envisioned architecture poised to redefine network capabilities. Driven by the need to enhance capacity, increase data rates, support diverse mobility models, and facilitate heterogeneous connectivity, the conceptual framework of a unified 3D network is presented. The focus is on seamlessly integrating diverse network segments and fostering holistic network orchestration. In examining the technical challenges inherent to the realization of a unified 3D network, we outline our strategies to address mobility management, handover optimization, interference mitigation, and the integration of distributed physical layer concepts. Proposals encompass federated learning mechanisms, advanced beamforming techniques, and energy-efficient computational offloading strategies, aimed at enhancing network performance and resilience. Moreover, we outline compelling utilization scenarios and highlighted promising avenues for future research.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"170-201"},"PeriodicalIF":5.3,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10770553","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142858978","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":"Optimizing Energy Consumption and Latency in IoT Through Edge Computing in Air–Ground Integrated Network With Deep Reinforcement Learning","authors":"Vitou That;Kimchheang Chhea;Jung-Ryun Lee","doi":"10.1109/OJVT.2024.3507288","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3507288","url":null,"abstract":"With the increasing computational demands of Internet of Things (IoT) applications, air-ground integrated networks (AGIN), leveraging the capabilities of Unmanned Aerial Vehicles (UAVs) and High-Altitude Platform (HAP), provides an essential solution to these challenges. In this paper, we propose a framework that facilitates local computing at IoT devices and offers the flexibility to offload tasks to aerial platforms when necessary. Specifically, we formulate a multi-objective optimization model aiming at simultaneously minimizing energy consumption and reducing task latency by adjusting control variables such as transmit power, offloading decisions, and UAV placement in a distributed network of IoT devices. Our proposed framework employs Deep Deterministic Policy Gradient (DDPG) techniques to dynamically optimize network operations, allowing for efficient real-time adjustments to network conditions and task demands. The performance of the proposed algorithm is compared to traditional algorithms, including the Whale Optimization Algorithm (WOA), Gradient Search with Barrier, and Bayesian Optimization (BO). Simulation results show that this approach significantly minimizes energy consumption and latency, outperforming conventional optimization methods. Additionally, scalability tests confirm that our framework can efficiently integrate an increasing number of IoT devices and UAVs.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"412-425"},"PeriodicalIF":5.3,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10768987","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106228","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":"Harmonics Measurement, Analysis, and Impact Assessment of Electric Vehicle Smart Charging","authors":"Murat Senol;I. Safak Bayram;Lewis Hunter;Kristian Sevdari;Connor McGarry;David Campos Gaona;Oliver Gehrke;Stuart Galloway","doi":"10.1109/OJVT.2024.3505778","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3505778","url":null,"abstract":"Smart charging for Electric Vehicles (EVs) is gaining traction as a key solution to alleviate grid congestion, delay the need for costly network upgrades, and capitalize on off-peak electricity rates. Governments are now enforcing the inclusion of smart charging capabilities in EV charging stations to facilitate this transition. While much of the current research focuses on managing voltage profiles, there is a growing need to examine harmonic emissions in greater detail. This study presents comprehensive data on harmonic distortion during the smart charging of eight popular EV models. We conducted an experimental analysis, measuring harmonic levels with charging current increments of 1A, ranging from the minimum to the maximum for each vehicle. The analysis compared harmonic emissions from both single and multiple EV charging scenarios against the thresholds for total harmonic distortion (THD) and individual harmonic limits outlined in power quality standards (e.g. IEC). Monte Carlo simulations were employed to further understand the behavior in multi-vehicle scenarios. The results reveal that harmonic distortion increases as the charging current decreases across both single and multiple vehicle charging instances. In case studies where several vehicles charge simultaneously, the findings show that as more EVs charge together, harmonic cancellation effects become more pronounced, leading to a gradual reduction in overall harmonic distortion. However, under worst-case conditions, the aggregate current THD can rise as high as 25%, with half of the tested vehicles surpassing the individual harmonic limits.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"109-127"},"PeriodicalIF":5.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10766666","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875114","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":"Optimizing Urban Air Mobility: A Ground-Connected Approach to Select Optimal eVTOL Takeoff and Landing Sites for Short-Distance Intercity Travel","authors":"Yantao Wang;Jiashuai Li;Yujie Yuan;Chun Sing Lai","doi":"10.1109/OJVT.2024.3506277","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3506277","url":null,"abstract":"The progression of low-carbon aviation policies and the maturation of electric vertical take-off and landing (eVTOL) technology have engendered considerable prospects for the advancement of short-haul intercity and intra-city transportation systems. To harness the potential of eVTOL travel in ameliorating transportation carbon emissions and alleviating ground transportation congestion, the judicious selection of optimal eVTOL stop sites emerges as a pivotal consideration. This study delineates a framework for the delineation of intra-city and short-distance inter-city eVTOL site selection predicated on comprehensive analysis of ground transportation system interconnections. The initial phase of the framework entails the identification of potential optimal take-off and landing sites through a multi-faceted assessment of factors encompassing vehicular and passenger traffic flows, regional economic dynamics, travel behavioral patterns, and prevailing eVTOL flight regulations across heterogeneous ground transportation networks. Employing an enhanced iteration of the \u0000<italic>K</i>\u0000-means algorithm, this phase undertakes the clustering of optimal takeoff and landing locations, thereby discerning their spatial distribution to effectively alleviate ground traffic congestion while aligning with eVTOL vertical port requirements and airspace regulatory mandates. The second phase involves the establishment of a demand gravity model to validate the optimal take-off and landing coordinate sites of eVTOL and further assess a service index indicative of traffic flow optimization. The case shows that six optimal eVTOL take-off and landing locations have been discerned by our model within the Beijing-Tianjin-Xiong'an (Hebei) region. These locations are anticipated to yield a cumulative service index of 75,465 instances, thereby efficaciously mitigating travel pressure on ground transportation infrastructure.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"216-239"},"PeriodicalIF":5.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10767205","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890165","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":"N-DriverMotion: Driver Motion Learning and Prediction Using an Event-Based Camera and Directly Trained Spiking Neural Networks on Loihi 2","authors":"Hyo Jong Chung;Byungkon Kang;Yoon Seok Yang","doi":"10.1109/OJVT.2024.3504481","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3504481","url":null,"abstract":"Driver motion recognition is a key factor in ensuring the safety of driving systems. This paper presents a novel system for learning and predicting driver motions, along with an event-based (720 × 720) dataset, N-DriverMotion, newly collected to train a neuromorphic vision system. The system includes an event-based camera that generates a driver motion dataset representing spike inputs and efficient spiking neural networks (SNNs) that are effective in training and predicting the driver's gestures. The event dataset consists of 13 driver motion categories classified by direction (front, side), illumination (bright, moderate, dark), and participant. A novel optimized four-layer convolutional spiking neural network (CSNN) was trained directly without any time-consuming preprocessing. This enables efficient adaptation to energy- and resource-constrained on-device SNNs for real-time inference on high-resolution event-based streams. Compared to recent gesture recognition systems adopting neural networks for vision processing, the proposed neuromorphic vision system achieves competitive accuracy of 94.04% in a 13-class classification task, and 97.24% in an unexpected abnormal driver motion classification task with the CSNN architecture. Additionally, when deployed to Intel Loihi 2 neuromorphic chips, the energy-delay product (EDP) of the model achieved 20,721 times more efficient than that of a non-edge GPU, and 541 times more efficient than edge-purpose GPU. Our proposed CSNN and the dataset can be used to develop safer and more efficient driver-monitoring systems for autonomous vehicles or edge devices requiring an efficient neural network architecture.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"68-80"},"PeriodicalIF":5.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10763457","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810415","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":"Enhancing Information Freshness and Energy Efficiency in D2D Networks Through DRL-Based Scheduling and Resource Management","authors":"Parisa Parhizgar;Mehdi Mahdavi;Mohammad Reza Ahmadzadeh;Melike Erol-Kantarci","doi":"10.1109/OJVT.2024.3502803","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3502803","url":null,"abstract":"This paper investigates resource management in device-to-device (D2D) networks coexisting with cellular user equipment (CUEs). We introduce a novel model for joint scheduling and resource management in D2D networks, taking into account environmental constraints. To preserve information freshness, measured by minimizing the average age of information (AoI), and to effectively utilize energy harvesting (EH) technology to satisfy the network's energy needs, we formulate an online optimization problem. This formulation considers factors such as the quality of service (QoS) for both CUEs and D2Ds, available power, information freshness, and environmental sensing requirements. Due to the mixed-integer nonlinear nature and online characteristics of the problem, we propose a deep reinforcement learning (DRL) approach to solve it effectively. Numerical results show that the proposed joint scheduling and resource management strategy, utilizing the soft actor-critic (SAC) algorithm, reduces the average AoI by 20% compared to other baseline methods.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"52-67"},"PeriodicalIF":5.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10758763","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142798029","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}