IEEE Transactions on Green Communications and Networking最新文献_第8页

Toward More Energy Efficient VLC Networks: A Study on Space Division Multiplexing and Smart Lighting 迈向更节能的VLC网络：空分复用和智能照明的研究

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-17 DOI: 10.1109/TGCN.2024.3415528

Elahe Zolala;Mohammad Amir Dastgheib;Hamzeh Beyranvand;Jawad A. Salehi

{"title":"Toward More Energy Efficient VLC Networks: A Study on Space Division Multiplexing and Smart Lighting","authors":"Elahe Zolala;Mohammad Amir Dastgheib;Hamzeh Beyranvand;Jawad A. Salehi","doi":"10.1109/TGCN.2024.3415528","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3415528","url":null,"abstract":"This paper addresses the challenge of enhancing energy efficiency in Visible Light Communication (VLC) networks through Space Division Multiplexing (SDM) and smart lighting integration. We mathematically formulate the problem of energy-efficient multi-user VLC networking with SDM and smart illumination, tailoring the light output according to the users’ demands. To address the arising intricate optimization problem, we propose Clustered Light Emitting Diode (LED) Assignment and Power optimization (CLAP). This heuristic approach leverages density-based spatial clustering for efficient user grouping and employs a greedy sequential algorithm for LED assignment. The constrained optimization by linear approximation technique is employed to determine transmitted optical power levels. By incorporating density functions of achievable rates into precise transmitter models, our study accurately assesses power consumption in VLC system optimization, significantly enhancing energy efficiency. A comparative analysis of three popular VLC network transmitters shows that precise power consumption determination is superior to using common approximations. The proposed methodology showcases remarkable improvements, achieving up to a 55% increase in energy efficiency and up to a 58% reduction in power consumption for a VLC network, with best results observed when utilizing bias-T transmitters, which can accommodate DC biasing, equipped with class AB amplifiers, known for their efficiency.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"96-107"},"PeriodicalIF":5.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trade-Off Between Renewable Energy Utilizing and Communication Quality for Base Stations: A Heterogeneous Multi-Agent Safe RL Method 基站可再生能源利用与通信质量的权衡：一种异构多智能体安全RL方法

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-17 DOI: 10.1109/TGCN.2024.3415034

Min Yan;Li Wang;Lianming Xu;Luyang Hou;Zhu Han

{"title":"Trade-Off Between Renewable Energy Utilizing and Communication Quality for Base Stations: A Heterogeneous Multi-Agent Safe RL Method","authors":"Min Yan;Li Wang;Lianming Xu;Luyang Hou;Zhu Han","doi":"10.1109/TGCN.2024.3415034","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3415034","url":null,"abstract":"The ultra-dense deployment of base stations (BSs) results in significant energy costs, while the increasing use of fluctuating renewable energy sources (RESs) threatens the safe operation of electric network (EN). These issues can be addressed by coordinating BSs’ active/sleep states with RES generation. However, the coordinated decision-making is challenging due to the conflicting goals of maximizing RES utilization, guaranteeing communication quality of service (QoS). In this paper, we design an electric-cellular collaborative network (ECCN) and formulate a joint optimization problem to minimize electric supply and QoS degradation costs, subjecting to EN’s safety constraints. Considering the uncertainty of RES generation and BS traffic, we propose a heterogeneous multi-agent safe reinforcement learning (HMAS-RL) algorithm to solve the problem. HMAS-RL inherits from the centralized critic and decentralized actor framework, where two heterogeneous agents learn a cooperative policy for joint decision-making through two actor networks design that share observations and a team reward. A cost critic network is designed to handle safety constraints, eliminating the need for manual penalty term design and tuning. We validate the proposed method using an IEEE 33-bus electric distribution test feeder. Results demonstrate HMAS-RL achieves superior performance in RES utilization, communication QoS, and EN safety constraints maintenance.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"83-95"},"PeriodicalIF":5.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Coalitional Game-Based Adaptive Scheduler Leveraging Task Heterogeneity for Greener Data Centers 基于联盟博弈的自适应调度器，利用任务异质性实现绿色数据中心

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-14 DOI: 10.1109/TGCN.2024.3414671

Saeed Akbar;Ubaid Ul Akbar;Rahmat Ullah;Zhonglong Zheng

{"title":"A Coalitional Game-Based Adaptive Scheduler Leveraging Task Heterogeneity for Greener Data Centers","authors":"Saeed Akbar;Ubaid Ul Akbar;Rahmat Ullah;Zhonglong Zheng","doi":"10.1109/TGCN.2024.3414671","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3414671","url":null,"abstract":"Managing power and its subsequent thermal implications is of paramount concern in modern Data Centers (DCs) management. Failure to adequately address the escalating energy use can result in excessive heat dissipation, leading to thermal imbalances and hotspots. In addition, the prolonged execution of CPU-intensive user jobs on servers operating at higher temperatures can significantly aggravate the DCs cooling efforts. Researchers advocate Thermal-aware (TA) scheduling as a promising tool to counter the said issue. However, existing state-of-the-art overlooks user jobs runtime heterogeneity, potentially causing aggravated heat dissipation when CPU-intensive tasks run on servers at elevated temperatures for longer duration. Moreover, existing works do not provide any mechanism to detect overloaded computing nodes at runtime in a TA context. Finally, existing strategies do not adapt according to the DCs dynamic thermal conditions. This paper offers a Coalitional Game-based Thermal-aware Adaptive Scheduling (CGTAS) tailored for heterogeneous DCs to minimize the cooling cost stemming from excessive heat generated during compute-intensive job execution. CGTAS intelligently differentiates incoming jobs based on their thermal profiles and CPU-time for optimal thermal outcomes. In addition, it dynamically allocates user jobs to computing nodes based on their real-time marginal thermal performance using the Core solution concept from game theory. Finally, unlike existing TA strategies, the proposed design identifies thermally overloaded computing elements using the Core and performs task migrations to optimize thermal-efficiency. Extensive simulations confirm substantial energy savings (up to 26.08%) compared to its TA substitutes, promoting sustainable and high-performance computing infrastructure in large-scale cloud DCs.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"55-69"},"PeriodicalIF":5.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Dual-Hop Uplink IM-OFDMA System With Amplify-and-Forward Relays 带放大转发中继的双跳上行IM-OFDMA系统

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-10 DOI: 10.1109/TGCN.2024.3411673

Saud Althunibat;Khalid Qaraqe

{"title":"A Dual-Hop Uplink IM-OFDMA System With Amplify-and-Forward Relays","authors":"Saud Althunibat;Khalid Qaraqe","doi":"10.1109/TGCN.2024.3411673","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3411673","url":null,"abstract":"Index Modulation based Orthogonal Frequency Division Multiple Access (IM-OFDMA) is an uplink scheme that allows a set of users to share a chunk of frequency subcarriers by the means of IM. IM-OFDMA has shown a promising performance as compared to its counterparts, which makes it a good candidate for future networks. To this end, this paper aims to investigate the performance of a dual-hop IM-OFDMA with the aid of Amplify-and-Forward (AF) relays. Unlike other links, employing AF relaying poses a challenge in IM-OFDMA because the identities and the number of active users over a subcarrier is unknown at the relays, which makes popular amplifying strategies not applicable. As such, a dual-hop uplink IM-OFDMA system requires a new amplifying strategy that is compatible with the data-driven subcarrier activation followed in IM-OFDMA systems. This paper proposes two different amplifying strategies that do not rely on the channel gains between the users and the AF relays. The performance of both amplifying strategies are analytically quantified in terms of the Average Bit Error Rate (ABER) at the base station and the energy consumption at the relays. Analytical and simulation results demonstrate the improvement in BER and energy saving achieved by the proposed dual-hop AF-based IM-OFDMA.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"45-54"},"PeriodicalIF":5.3,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Multi-Level Amplitude-Shift Keying for Channel Norm-Based SIMO Wireless Communication System in Rician Fading Environment 衰落环境下基于信道规范的SIMO无线通信系统多级最优移幅键控

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-07 DOI: 10.1109/TGCN.2024.3411170

Badri Ramanjaneya Reddy;Soumya P. Dash

{"title":"Optimal Multi-Level Amplitude-Shift Keying for Channel Norm-Based SIMO Wireless Communication System in Rician Fading Environment","authors":"Badri Ramanjaneya Reddy;Soumya P. Dash","doi":"10.1109/TGCN.2024.3411170","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3411170","url":null,"abstract":"An N-branch receive diversity wireless system subject to prominent line-of-sight (LoS) fading in the multipath is considered in this paper. The fading channels are modeled by Rician distributions and the transmitter employs multi-level amplitude-shift keying (ASK) for data modulation. The receiver is assumed to possess the knowledge of the magnitude of the fading channels and thus, an optimal receiver structure based on the knowledge of the channel-norm is derived. Owing to the complexity of the receiver structure, two novel suboptimal receivers, inspired by the central limit theorem and Euclidean distance, are proposed. Furthermore, series-form expressions for the symbol error probability (SEP) for both these receivers are derived. This is followed by proposing and solving an optimization framework aimed at finding the optimal multi-level ASK constellations to minimize the SEP expressions obtained for the two receivers under an average system energy constraint. The analytical framework is verified by numerical studies that show the efficacy of the obtained optimal ASK constellations over the equally-spaced ASK constellations traditionally used for wireless systems. Moreover, it is observed that the traditional Euclidean distance-based receiver isn’t appropriate for optimal performance and the optimal factor <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula> is dependent on the average signal-to-noise ratio and the number of diversity branches. Additionally, the dependencies of the shape of the optimal constellation schemes on the various system parameters are studied via numerical results. Thus, the proposed novel receivers and multi-level ASK schemes provide crucial design insights for reliable, hardware-efficient, and energy-efficient communication systems with prominent LoS links.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"29-44"},"PeriodicalIF":5.3,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Channel Estimation for RIS-Assisted Time-Varying MIMO System: An Attention-Based Learning Approach ris辅助时变MIMO系统的信道估计：一种基于注意的学习方法

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-05 DOI: 10.1109/TGCN.2024.3410049

Ziwei Qi;Da Liu;Jingbo Zhang

{"title":"Channel Estimation for RIS-Assisted Time-Varying MIMO System: An Attention-Based Learning Approach","authors":"Ziwei Qi;Da Liu;Jingbo Zhang","doi":"10.1109/TGCN.2024.3410049","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3410049","url":null,"abstract":"The challenges of time-varying channel estimation in reconfigurable intelligent surface (RIS)-based MIMO systems are focused on in this paper. We propose a scheme based on deep learning, which includes RIS element selection model (RESM) and a full channel estimation model (FCEM). Firstly, The RESM is designed for choosing the optimal subset of all RIS elements to reduce system overhead. A convolutional network based scorer is established to evaluate relationship between optimal partial channels and full channels, and the differential Top-N operation is used to select the optimal subset of RIS elements, where perturbed maximum method is utilized to ensure end-to-end learning is feasible. Then, the FCEM is developed to realize accurate time-varying channel estimation by exploiting the strong nonlinear fitting capability of attention based deep networks. We develop network structures including improved transformers and residual blocks in the FCEM to counteract the channels’ stochastic characteristic, so as to recover the full channels corresponding to the optimal subset. The numerical results demonstrate the proposed scheme outperforms the benchmark schemes under various comparison conditions and is suitable for high-speed mobile scenarios.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"140-151"},"PeriodicalIF":5.3,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HA-A2C: Hard Attention and Advantage Actor-Critic for Addressing Latency Optimization in Edge Computing HA-A2C：解决边缘计算延迟优化的硬注意和优势参与者-评论家

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-04 DOI: 10.1109/TGCN.2024.3409390

Jing Yang;Jialin Lu;Xu Zhou;Shaobo Li;Chuanyue Xiong;Jianjun Hu

{"title":"HA-A2C: Hard Attention and Advantage Actor-Critic for Addressing Latency Optimization in Edge Computing","authors":"Jing Yang;Jialin Lu;Xu Zhou;Shaobo Li;Chuanyue Xiong;Jianjun Hu","doi":"10.1109/TGCN.2024.3409390","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3409390","url":null,"abstract":"Due to the rapid development of the IoT and data-driven applications, low-latency task scheduling methods that quickly respond to user tasks has become a significant challenge for edge servers. However, the existing task scheduling strategies do not overcome the impact of factors such as task characteristics, resource availability, and network conditions on delays. Meanwhile, the cross-regional maldistribution of edge servers is obvious, and the edge servers are either idle or overloaded. To address these issues, we propose a low-latency edge scheduling strategy based on the Hard Attention Mechanism and Advantage Actor-Critic (HA-A2C). The core element of this method is the adoption of a hard attention mechanism, which reduces computing complexity and increases efficiency. Effective attention allocation during the resource allocation process further reduces job completion time. Additionally, the deep reinforcement learning method is employed to enhance task dynamic scheduling capabilities, thereby reducing scheduling delays. The HA-A2C approach reduces task latency by approximately 40% compared to the DQN method. Consequently, the intelligent allocation of task resources achieved by integrating the hard attention technique significantly reduces task scheduling time in edge environments.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"207-217"},"PeriodicalIF":5.3,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Static Deep Q-Learning for Green Downlink C-RAN 绿色下行链路C-RAN的静态深度q学习

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-04 DOI: 10.1109/TGCN.2024.3408828

Yuchao Chang;Hongli Wang;Wen Chen;Yonghui Li;Naofal Al-Dhahir

{"title":"Static Deep Q-Learning for Green Downlink C-RAN","authors":"Yuchao Chang;Hongli Wang;Wen Chen;Yonghui Li;Naofal Al-Dhahir","doi":"10.1109/TGCN.2024.3408828","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3408828","url":null,"abstract":"Power saving is a main pillar in the operation of wireless communication systems. In this paper, we investigate cloud radio access network (C-RAN) capability to reduce power consumption based on the user equipment (UE) requirement. Aiming to save the long-term C-RAN energy consumption, an optimization problem is formulated to manage the downlink power without degrading the UE requirement by designing the power offset parameter. Considering stochastic traffic arrivals at UEs, we first formulate the problem as a Markov decision process (MDP) and then set up a dual objective optimization problem in terms of the downlink throughput and power. To solve this optimization problem, we develop a novel static deep Q-learning (SDQL) algorithm to maximize the downlink throughput and minimize the downlink power. In our proposed algorithm, we design multi-Q-tables to simultaneously optimize power reductions of activated RRHs by assigning one Q-table for each UE. To maximize the accumulative reward in terms of the downlink throughput loss and power reduction, our proposed algorithm performs power reductions of activated RRHs through continuous environmental interactions. Simulation resultsCode can be accessed on website: <uri>https://github.com/yuchaoch/project/tree/main</uri> show that our proposed algorithm enjoys a superior average power reduction compared to the activation and sleep schemes, and enjoys a low computational complexity.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"291-303"},"PeriodicalIF":5.3,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SM and NOMA Joint Assisted Indoor Multi-User VLC Downlink SM和NOMA联合辅助室内多用户VLC下行链路

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-03 DOI: 10.1109/TGCN.2024.3409080

Fasong Wang;Ting Zuo;Jiankang Zhang;Shijie Shi;Yitong Li

{"title":"SM and NOMA Joint Assisted Indoor Multi-User VLC Downlink","authors":"Fasong Wang;Ting Zuo;Jiankang Zhang;Shijie Shi;Yitong Li","doi":"10.1109/TGCN.2024.3409080","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3409080","url":null,"abstract":"In this paper, a novel spatial modulation (SM) assisted successive interference cancelation (SIC) free non-orthogonal multiple access (NOMA) scheme is proposed for indoor multi-user visible light communications (VLC) downlink. In the proposed scheme, all users are grouped according to channel gains. The data information of users in each group is then mapped to the spatial domain and constellation symbol domain according to their bit error rate requirements. In addition, due to the inherent sparsity of SM modulated signals, the compressed sensing (CS) sparse reconstruction algorithm is revoked for demodulating signals at the receiver. In this process, the information carried by the activated light emitting diode index is demodulated using the CS aided sparsity reconstruction algorithm, while the constellation symbol information is demodulated using the maximum likelihood (ML) algorithm. Additionally, by combining the greedy algorithm with the ML algorithm, a new method for sparse signal reconstruction detection is proposed. Compared with traditional NOMA technology, at the receiver side, both the error propagation caused by SIC and intra-group interference can be eliminated. Furthermore, the computational complexity of demodulation is reduced by utilizing the proposed joint signal detection procedure. The effectiveness of the proposed indoor multi-user SM NOMA VLC architecture is validated through Monte Carlo simulations.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"15-28"},"PeriodicalIF":5.3,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving Energy Efficiency in Satellite-to-Ground Communications With Multiple Reflecting Intelligent Surfaces 利用多重反射智能表面提高卫星对地通信的能效

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-06-03 DOI: 10.1109/TGCN.2024.3408295

Muhammad I. Khalil;Jiao Lin;Ke Wang

引用次数: 0