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Support vector machine-based handover scheme for heterogeneous ultra dense network of high-speed railway 基于支持向量机的高速铁路异构超密集网络切换方案
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-08-05 DOI: 10.1049/cmu2.12814
Siling Wang, Li Zhang
{"title":"Support vector machine-based handover scheme for heterogeneous ultra dense network of high-speed railway","authors":"Siling Wang,&nbsp;Li Zhang","doi":"10.1049/cmu2.12814","DOIUrl":"https://doi.org/10.1049/cmu2.12814","url":null,"abstract":"<p>In order to meet the growing demands and extend network coverage for high-speed railway (HSR) system, the dense deployment of a large number of small cells (SCs) is considered for 5G networks. However, the deployment of dense SCs and the high speed of trains result in challenging problems such as interference, frequent handovers (HOs), increased HO failure rate, and consequently the deteriorated overall quality of service (QoS). In order to address the challenges in handover, an improved handover decision strategy is proposed based on Support Vector Machine (SVM). The HO decision making is considered as a classification problem taking into account available states that they may have in the HSR network. From the simulation results, it is observed that the proposed scheme is capable of decreasing the number of HO, HO failure rate and enhancing the network performance remarkably.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 18","pages":"1191-1204"},"PeriodicalIF":1.5,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Two stage beamforming and combining scheme for FDD massive MIMO systems with multi-antenna users 多天线用户 FDD 大规模 MIMO 系统的两级波束成形和组合方案
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-30 DOI: 10.1049/cmu2.12811
Wu Zheng, Chen Liu, Yunchao Song, Tianbao Gao
{"title":"Two stage beamforming and combining scheme for FDD massive MIMO systems with multi-antenna users","authors":"Wu Zheng,&nbsp;Chen Liu,&nbsp;Yunchao Song,&nbsp;Tianbao Gao","doi":"10.1049/cmu2.12811","DOIUrl":"https://doi.org/10.1049/cmu2.12811","url":null,"abstract":"<p>This paper proposes a two-stage beamforming and combining scheme in frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems with multi-antenna users. Specifically, the proposed scheme is a two-stage scheme, where the pre-beamforming matrix and pre-combining matrix are designed using the channel covariance matrix (CCM) in the first stage. The problem of the pre-beamforming matrix and pre-combining matrix design are formulated as an 0–1 quadratic integer programming problem. To solve this problem, it is further transformed into an 0–1 mixed linear integer programming problem. In the second stage, the sparse code multiple access and multi-user precoding and combining are adopted to mitigate the inter-user interference. Different from the previous transmission scheme using CCM, the proposed scheme consider the multi-antenna user system, and uses the CCM to design both the pre-beamforming and pre-combining matrices to sparsify the effective channel matrix, such that the overhead of pilot and feedback can be reduced. Moreover, the sparse code multiple access can help to better reduce the inter-user interference. Simulation results validate the good performance of the proposed scheme.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 18","pages":"1166-1178"},"PeriodicalIF":1.5,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12811","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142574153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Dynamic Twitter friend grouping based on similarity, interaction, and trust to account for ever-evolving relationships 根据相似性、互动性和信任度对 Twitter 好友进行动态分组,以考虑不断发展的关系
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-26 DOI: 10.1049/cmu2.12807
Nisha P. Shetty, Balachandra Muniyal, Leander Melroy Maben, Rithika Jayaraj, Sameer Saxena
{"title":"Dynamic Twitter friend grouping based on similarity, interaction, and trust to account for ever-evolving relationships","authors":"Nisha P. Shetty,&nbsp;Balachandra Muniyal,&nbsp;Leander Melroy Maben,&nbsp;Rithika Jayaraj,&nbsp;Sameer Saxena","doi":"10.1049/cmu2.12807","DOIUrl":"10.1049/cmu2.12807","url":null,"abstract":"<p>Online social networks have become ubiquitous, allowing users to share opinions on various topics. However, oversharing can compromise privacy, leading to potential blackmail or fraud. Current platforms lack friend categorization based on trust levels. This study proposes simulating real-world friendships by grouping users into three categories: acquaintances, friends, and close friends, based on trust and engagement. It also introduces a dynamic method to adjust relationship status over time, considering users' past and present offenses against peers. The proposed system automatically updates friend lists, eliminating manual grouping. It calculates relationship strength by considering all components of online social networks and trust variations caused by user attacks. This method can be integrated with clustering algorithms on popular platforms like Facebook, Twitter, and Instagram to enable constrained sharing. By implementing this system, users can better control their information sharing based on trust levels, reducing privacy risks. The dynamic nature of the relationship status adjustment ensures that the system remains relevant as user interactions evolve over time. This approach offers a more nuanced and secure social networking experience, reflecting real-world relationship dynamics in the digital sphere.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 17","pages":"1018-1048"},"PeriodicalIF":1.5,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12807","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141799854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fine-grained spectrum map inference: A novel approach based on deep residual network 细粒度频谱图推断:基于深度残差网络的新方法
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-19 DOI: 10.1049/cmu2.12786
Shoushuai He, Lei Zhu, Lei Wang, Weijun Zeng, Zhen Qin
{"title":"Fine-grained spectrum map inference: A novel approach based on deep residual network","authors":"Shoushuai He,&nbsp;Lei Zhu,&nbsp;Lei Wang,&nbsp;Weijun Zeng,&nbsp;Zhen Qin","doi":"10.1049/cmu2.12786","DOIUrl":"10.1049/cmu2.12786","url":null,"abstract":"<p>Spectrum map is a database that stores multidimensional representations of spectrum situation information. It provides support for spectrum sensing and endows wireless communication networks with intelligence. However, the ubiquitous deployment of monitoring devices leads to huge costs of operation and maintenance. It indicates that an approach is needed to reduce the number of monitoring devices, but prevent the degradation of data granularity. Therefore, this paper focuses on the accurate construction of the spectrum map. It aims to infer the fine-grained spectrum situation of the target region based on coarse-grained observation. In order to solve this problem, an inference framework based on deep residual network is developed in this paper. In the case of rule deployment for sensing nodes, it adopts the idea of super resolution to improve the accuracy of the spectrum map. The framework is composed of two major parts: an inference network, which generates fine-grained spectrum maps from coarse-grained counterparts by using feature extraction module and upsampling construction module; and a fusion network, which considers the influence of environmental factors to further improve the performance. A large number of experiments on simulated datasets verify the effectiveness of the proposed method.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 16","pages":"925-937"},"PeriodicalIF":1.5,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12786","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A new hybrid genetic algorithm with tabu search for solving the temporal coverage problem using rotating directional sensors 利用旋转定向传感器解决时间覆盖问题的新型混合遗传算法与塔布搜索
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-16 DOI: 10.1049/cmu2.12796
Mahboobeh Eshaghi, Ali Nodehi, Hosein Mohamadi
{"title":"A new hybrid genetic algorithm with tabu search for solving the temporal coverage problem using rotating directional sensors","authors":"Mahboobeh Eshaghi,&nbsp;Ali Nodehi,&nbsp;Hosein Mohamadi","doi":"10.1049/cmu2.12796","DOIUrl":"10.1049/cmu2.12796","url":null,"abstract":"<p>One of the most important problems in directional sensor networks is coverage problem. The coverage can be measured in two ways: positional or temporal. In temporal coverage, the directional sensors rotate periodically round themselves in a repetitive process. Thus, in each time slot, those targets that are positioned within the sensor nodes radius receive their desired coverage. In this model, if a target is left uncovered, it is said that the target has remained in darkness. The main task defined for the temporal coverage model is the minimization of the total dark time for all the targets in the network. This problem has been solved by greedy-based algorithms in last studies. Greedy-based algorithms are able to solve the temporal coverage problem in real time. Remember that the performance of greedy algorithms is extremely dependent on the closeness of optimal solution and initial candidates. For this reason, greedy algorithms may obtain local minima due to heuristic search. As far as we know meta-heuristic algorithms have not been used in past researches to solve such problems. For solving this problem, in this paper two algorithms were developed, GA-based and hybridized model comprising genetic algorithms and tabu search. A new model was suggested for the chromosome in genetic algorithm. To evaluate the performance of the developed algorithms, they were compared with randomized scenario and greedy-based algorithm presented in last studies. For better comparison, several parameters, including total dark time, number of sensors, number of targets, sector angle, sensing range were taken into account. The results obtained from the comparison of the algorithms indicated that the developed algorithms are effective in solving the temporal coverage problem in terms of minimizing the total dark time of the targets.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 16","pages":"938-949"},"PeriodicalIF":1.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12796","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141640631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
BFT-Net: A transformer-based boundary feedback network for kidney tumour segmentation BFT-Net:用于肾脏肿瘤分割的基于变压器的边界反馈网络
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-12 DOI: 10.1049/cmu2.12802
Tianyu Zheng, Chao Xu, Zhengping Li, Chao Nie, Rubin Xu, Minpeng Jiang, Leilei Li
{"title":"BFT-Net: A transformer-based boundary feedback network for kidney tumour segmentation","authors":"Tianyu Zheng,&nbsp;Chao Xu,&nbsp;Zhengping Li,&nbsp;Chao Nie,&nbsp;Rubin Xu,&nbsp;Minpeng Jiang,&nbsp;Leilei Li","doi":"10.1049/cmu2.12802","DOIUrl":"10.1049/cmu2.12802","url":null,"abstract":"<p>Kidney tumours are among the top ten most common tumours, the automatic segmentation of medical images can help locate tumour locations. However, the segmentation of kidney tumour images still faces several challenges: firstly, there is a lack of renal tumour endoscopic datasets and no segmentation techniques for renal tumour endoscopic images; secondly, the intra-class inconsistency of tumours caused by variations in size, location, and shape of renal tumours; thirdly, difficulty in semantic fusion during decoding; and finally, the issue of boundary blurring in the localization of lesions. To address the aforementioned issues, a new dataset called Re-TMRS is proposed, and for this dataset, the transformer-based boundary feedback network for kidney tumour segmentation (BFT-Net) is proposed. This network incorporates an adaptive context extract module (ACE) to emphasize local contextual information, reduces the semantic gap through the mixed feature capture module (MFC), and ultimately improves boundary extraction capability through end-to-end optimization learning in the boundary assist module (BA). Through numerous experiments, it is demonstrated that the proposed model exhibits excellent segmentation ability and generalization performance. The mDice and mIoU on the Re-TMRS dataset reach 91.1% and 91.8%, respectively.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 16","pages":"966-977"},"PeriodicalIF":1.5,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12802","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Study of construction of Golomb Costas arrays with ideal autocorrelation properties based on extension field 基于扩展场的具有理想自相关特性的戈隆-科斯塔斯阵列构造研究
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-06 DOI: 10.1049/cmu2.12803
Jianguo Yao, Ziwei Liu, Xiaoming Wang
{"title":"Study of construction of Golomb Costas arrays with ideal autocorrelation properties based on extension field","authors":"Jianguo Yao,&nbsp;Ziwei Liu,&nbsp;Xiaoming Wang","doi":"10.1049/cmu2.12803","DOIUrl":"10.1049/cmu2.12803","url":null,"abstract":"<p>This paper proposes a specific algebraic structure and demonstrates its nature as an extension field, enabling the construction of Golomb Costas (GC) arrays. It provides detailed instructions and examples for constructing GC arrays using this extension field, along with a corresponding flowchart. Additionally, the paper conducts a thorough analysis, incorporating calculations and comparisons, to evaluate the autocorrelation of a GC array derived from the extension field compared to that of a diagonal frequency hopping array. The analysis reveals the superior autocorrelation properties of GC arrays based on the extension field. Furthermore, the paper establishes a mathematical model for the signal coded by the frequency hopping array and subsequently simulates and compares the ambiguity function of the signal coded by a GC array with that of a signal coded by a diagonal frequency hopping array. This comparison underscores the thumbtack ambiguity function of frequency hopping signal coded by a GC array. Moreover, the paper thoroughly investigates the relationship between the correlation function of GC arrays and the roots of an algebraic equation in a finite field, and strictly proves the ideal autocorrelation properties of Golomb Costas arrays.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 17","pages":"979-992"},"PeriodicalIF":1.5,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12803","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
BPNN-based flow classification and admission control for software defined IIoT 基于 BPNN 的软件定义 IIoT 流量分类和准入控制
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-05 DOI: 10.1049/cmu2.12798
Cheng Wang, Hai Xue, Zhan Huan
{"title":"BPNN-based flow classification and admission control for software defined IIoT","authors":"Cheng Wang,&nbsp;Hai Xue,&nbsp;Zhan Huan","doi":"10.1049/cmu2.12798","DOIUrl":"10.1049/cmu2.12798","url":null,"abstract":"<p>Flow admission control (FAC) aims to efficiently manage the service requests while maximizing the network utilization. With multiple connection requests, access delay or even service interruption may occur. This paper proposes a novel FAC approach to reduce the contention between the end nodes and ensure high utilization of the networking resources for software defined IIoT. First, incoming flows are classified into different priorities using back propagation neural network based on selected features representing the current network status. Second, with the designed flow admission policies, bandwidth and buffer size are estimated with stochastic network calculus model. Finally, the thresholds of the proposed FAC scheme are dynamically decided based on the above two parameters. Various flows are admitted or rejected via the proposed FAC to maintain real time processing. Unlike traditional FAC schemes rely on static priority systems, the proposed scheme leverages machine learning technique for dynamic flow prioritization and the stochastic network calculus model for precise estimation. Computer simulation reveals that the proposed scheme accurately classifies the flows, and substantially decreases the transmission delay and improves the network utilization compared to the existing FAC schemes. This highlights the superiority of the proposed scheme meeting the demands of software defined IIoT.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 15","pages":"882-896"},"PeriodicalIF":1.5,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12798","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancing cloud security: A study on ensemble learning-based intrusion detection systems 加强云安全:基于集合学习的入侵检测系统研究
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-04 DOI: 10.1049/cmu2.12801
Maha Al-Sharif, Anas Bushnag
{"title":"Enhancing cloud security: A study on ensemble learning-based intrusion detection systems","authors":"Maha Al-Sharif,&nbsp;Anas Bushnag","doi":"10.1049/cmu2.12801","DOIUrl":"10.1049/cmu2.12801","url":null,"abstract":"<p>Cloud computing has become an essential technology for people and enterprises due to the simplicity and rapid availability of services on the internet. These services are usually delivered through a third party, which provides the required resources for users. Therefore, because of the distributed complexity and increased spread of this type of environment, many attackers are attempting to access sensitive data from users and organizations. One counter technique is the use of intrusion detection systems (IDSs), which detect attacks within the cloud environment by monitoring traffic activity. However, since the computing environment varies from the environments of most traditional systems, it is difficult for IDSs to identify attacks and continual changes in attack patterns. Therefore, a system that uses an ensemble learning algorithm is proposed. Ensemble learning is a machine learning technique that collects information from weak classifiers and creates one robust classifier with higher accuracy than the individual weak classifiers. The bagging technique is used with a random forest algorithm as a base classifier and compared to three boosting classifiers: Ensemble AdaBoost, Ensemble LPBoost, and Ensemble RUSBoost. The CICID2017 dataset is utilized to develop the proposed IDS to satisfy cloud computing requirements. Each classifier is also tested on various subdatasets individually to analyze the performance. The results show that Ensemble RUSBoost has the best average performance overall with 99.821% accuracy. Moreover, bagging achieves the best performance on the DS2 subdataset, with an accuracy of 99.997%. The proposed model is also compared to a model from the literature to show the differences and demonstrate its effectiveness.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 16","pages":"950-965"},"PeriodicalIF":1.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12801","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141678558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning 基于 Lyapunov 函数和深度强化学习的车载边缘计算优化方案
IF 1.5 4区 计算机科学
IET Communications Pub Date : 2024-07-02 DOI: 10.1049/cmu2.12800
Lin Zhu, Long Tan, Bingxian Li, Huizi Tian
{"title":"An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning","authors":"Lin Zhu,&nbsp;Long Tan,&nbsp;Bingxian Li,&nbsp;Huizi Tian","doi":"10.1049/cmu2.12800","DOIUrl":"10.1049/cmu2.12800","url":null,"abstract":"<p>Traditional vehicular edge computing research usually ignores the mobility of vehicles, the dynamic variability of the vehicular edge environment, the large amount of real-time data required for vehicular edge computing, the limited resources of edge servers, and collaboration issues. In response to these challenges, this article proposes a vehicular edge computing optimization scheme based on the Lyapunov function and Deep Reinforcement Learning. In this solution, this article uses Digital Twin technology (DT) to simulate the vehicular edge environment. The edge server DT is used to simulate the vehicular edge environment under the edge server, and the base station DT is used to simulate the entire vehicular edge system environment. Based on the real-time data obtained from DT simulation, this paper defines the Lyapunov function to simplify the migration cost of vehicle tasks between servers into a multi-objective dynamic optimization problem. It solves the problem by applying the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. Experimental results show that compared with other algorithms, this scheme can effectively optimize the allocation and collaboration of vehicular edge computing resources and reduce the delay and energy consumption caused by vehicle task processing.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 15","pages":"908-924"},"PeriodicalIF":1.5,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12800","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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