Artificial intelligence (AI) for computational electromagnetics (CEM) has drawn an increasing attention in recent years. However, current AI-based CEM methods face two key challenges: the high production cost of training datasets and poor generalization ability of trained neural networks (NNs). In this communication, we employ active learning (AL) and incremental learning (IL) to tackle the issues. AL cuts the dataset production cost by selecting the most informative samples before NN training, guided by evaluating how well the predicted results by a pretrained NN satisfy the boundary conditions or governing equations. By this way, the dataset generation time and storage are significantly reduced compared to fully supervised learning (SL). IL improves the generalization ability by enabling an NN pretrained for one type of targets to efficiently acquire knowledge for a new type of targets while retaining prior learning. This strategy is substantially more efficient than training new NNs from scratch for each type of targets. The effectiveness of the proposed AL-IL framework is demonstrated for 3-D conducting, dielectric, and metal–dielectric composite targets. It establishes a valuable paradigm for AI-based CEM, accelerating dataset generation and enhancing model generalization.
{"title":"AI for Evaluation of Electromagnetic Scattering Using Active and Incremental Learning","authors":"De-Hua Kong;Wen-Wei Zhang;Jia-Qi Kang;Wen-Chi Huang;Jia-Ning Cao;Xing-Yue Guo;Ming-Yao Xia","doi":"10.1109/TAP.2025.3624223","DOIUrl":"https://doi.org/10.1109/TAP.2025.3624223","url":null,"abstract":"Artificial intelligence (AI) for computational electromagnetics (CEM) has drawn an increasing attention in recent years. However, current AI-based CEM methods face two key challenges: the high production cost of training datasets and poor generalization ability of trained neural networks (NNs). In this communication, we employ active learning (AL) and incremental learning (IL) to tackle the issues. AL cuts the dataset production cost by selecting the most informative samples before NN training, guided by evaluating how well the predicted results by a pretrained NN satisfy the boundary conditions or governing equations. By this way, the dataset generation time and storage are significantly reduced compared to fully supervised learning (SL). IL improves the generalization ability by enabling an NN pretrained for one type of targets to efficiently acquire knowledge for a new type of targets while retaining prior learning. This strategy is substantially more efficient than training new NNs from scratch for each type of targets. The effectiveness of the proposed AL-IL framework is demonstrated for 3-D conducting, dielectric, and metal–dielectric composite targets. It establishes a valuable paradigm for AI-based CEM, accelerating dataset generation and enhancing model generalization.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"74 1","pages":"1245-1250"},"PeriodicalIF":5.8,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This communication presents the theory and design of a joint fast-and-slow time modulation for space-time-modulated metasurfaces (ST-MTSs) to simultaneously and precisely generate 1-D high-resolution range profile (HRRP), range-Doppler profile, and micro-Doppler signature. The design process is guided via scattering center model of the deceptive target to be reproduced by the stationary metasurface. To achieve such a multiradar-characteristics jamming, fast-time modulation is implemented to generate deceptive HRRPs, whereas extra phase terms are introduced in slow-time domain to compensate for the phase differences between adjacent pulses in the echo caused by the motion and micromotion of the deceptive target. For precise jamming, the scattered electromagnetic (EM) field of a deceptive target is first expressed to derive the radar multicharacteristics with the help of scattering center models. A vector analysis in the complex plane is then employed to synthesize the amplitude–phase reconfigurable reflection coefficients using a 2-bit phase reconfigurable metasurface, further improving the performance of the jamming method. Both numerical simulations and experimental results confirm the effectiveness of the proposed jamming method.
{"title":"Scattering Center Model Guided Joint Fast-and-Slow Time Modulation: Theoretical Foundations and Multiradar-Characteristics Spoofing","authors":"Yonggeng Zhu;Xinyu Fang;Mengmeng Li;Jihong Gu;Davide Ramaccia;Alessandro Toscano;Filiberto Bilotti;Dazhi Ding","doi":"10.1109/TAP.2025.3623293","DOIUrl":"https://doi.org/10.1109/TAP.2025.3623293","url":null,"abstract":"This communication presents the theory and design of a joint fast-and-slow time modulation for space-time-modulated metasurfaces (ST-MTSs) to simultaneously and precisely generate 1-D high-resolution range profile (HRRP), range-Doppler profile, and micro-Doppler signature. The design process is guided via scattering center model of the deceptive target to be reproduced by the stationary metasurface. To achieve such a multiradar-characteristics jamming, fast-time modulation is implemented to generate deceptive HRRPs, whereas extra phase terms are introduced in slow-time domain to compensate for the phase differences between adjacent pulses in the echo caused by the motion and micromotion of the deceptive target. For precise jamming, the scattered electromagnetic (EM) field of a deceptive target is first expressed to derive the radar multicharacteristics with the help of scattering center models. A vector analysis in the complex plane is then employed to synthesize the amplitude–phase reconfigurable reflection coefficients using a 2-bit phase reconfigurable metasurface, further improving the performance of the jamming method. Both numerical simulations and experimental results confirm the effectiveness of the proposed jamming method.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"74 1","pages":"1275-1280"},"PeriodicalIF":5.8,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-23DOI: 10.1109/TAP.2025.3622372
Zhiqiang Liu;Shaowei Liao;Quan Xue
This communication introduces a novel orbital angular momentum (OAM) eigenfield mode analysis method for both distance and misalignment estimations, including angle of arrival (AoA) and lateral displacement, of single- or multimode OAM waves. First, the OAM eigenfield mode analysis method is developed, which can be used to extract the OAM spectrum of an arbitrary incident OAM wave. The phase distribution of the OAM eigenfield is distance-dependent, which thus enables accurate estimation of propagation distance of an arbitrary incident OAM wave. Then, combined with an iterative method, the proposed method can effectively address practical distance and misalignment estimation challenges, such as lateral displacements and tilts, which can cause OAM mode distortion and intermode coupling. Finally, simulation results show that the proposed method can accurately estimate both the distance and misalignment of OAM waves, once the incident OAM field on the observation plane is obtained.
{"title":"Distance and Misalignment Estimations of OAM Waves Based on Eigenfield Mode Analysis","authors":"Zhiqiang Liu;Shaowei Liao;Quan Xue","doi":"10.1109/TAP.2025.3622372","DOIUrl":"https://doi.org/10.1109/TAP.2025.3622372","url":null,"abstract":"This communication introduces a novel orbital angular momentum (OAM) eigenfield mode analysis method for both distance and misalignment estimations, including angle of arrival (AoA) and lateral displacement, of single- or multimode OAM waves. First, the OAM eigenfield mode analysis method is developed, which can be used to extract the OAM spectrum of an arbitrary incident OAM wave. The phase distribution of the OAM eigenfield is distance-dependent, which thus enables accurate estimation of propagation distance of an arbitrary incident OAM wave. Then, combined with an iterative method, the proposed method can effectively address practical distance and misalignment estimation challenges, such as lateral displacements and tilts, which can cause OAM mode distortion and intermode coupling. Finally, simulation results show that the proposed method can accurately estimate both the distance and misalignment of OAM waves, once the incident OAM field on the observation plane is obtained.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"74 1","pages":"1239-1244"},"PeriodicalIF":5.8,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-14DOI: 10.1109/TAP.2025.3611246
{"title":"IEEE Transactions on Antennas and Propagation Information for Authors","authors":"","doi":"10.1109/TAP.2025.3611246","DOIUrl":"https://doi.org/10.1109/TAP.2025.3611246","url":null,"abstract":"","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"73 10","pages":"C3-C3"},"PeriodicalIF":5.8,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11203820","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145352133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2025-10-14DOI: 10.1109/TAP.2025.3611248
{"title":"Institutional Listings","authors":"","doi":"10.1109/TAP.2025.3611248","DOIUrl":"https://doi.org/10.1109/TAP.2025.3611248","url":null,"abstract":"","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"73 10","pages":"C4-C4"},"PeriodicalIF":5.8,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11203843","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145289541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2025-10-08DOI: 10.1109/TAP.2025.3617236
Sarah E. Wessinger;Leslie N. Smith;Jacob Gull;Jonathan Gehman;Zachary Beever;Andrew J. Kammerer
Accurately estimating propagation factor over multiple frequencies within the marine atmospheric boundary layer is crucial for the effective deployment of radar technologies. Traditional parabolic equation simulations, while effective, can be computationally expensive and time-intensive, limiting their practical application. This communication explores a novel approach using deep neural networks (DNNs) to estimate the pattern propagation factor, a critical parameter for characterizing environmental impacts on signal propagation. Image-to-image translation generators designed to ingest modified refractivity data and generate predictions of pattern propagation factors over the same domain are developed. Findings demonstrate that DNNs can be trained to analyze multiple frequencies and reasonably predict the pattern propagation factor, offering an alternative to traditional methods.
{"title":"A Deep Learning Framework for 2-D, Multifrequency Propagation Factor Estimation","authors":"Sarah E. Wessinger;Leslie N. Smith;Jacob Gull;Jonathan Gehman;Zachary Beever;Andrew J. Kammerer","doi":"10.1109/TAP.2025.3617236","DOIUrl":"https://doi.org/10.1109/TAP.2025.3617236","url":null,"abstract":"Accurately estimating propagation factor over multiple frequencies within the marine atmospheric boundary layer is crucial for the effective deployment of radar technologies. Traditional parabolic equation simulations, while effective, can be computationally expensive and time-intensive, limiting their practical application. This communication explores a novel approach using deep neural networks (DNNs) to estimate the pattern propagation factor, a critical parameter for characterizing environmental impacts on signal propagation. Image-to-image translation generators designed to ingest modified refractivity data and generate predictions of pattern propagation factors over the same domain are developed. Findings demonstrate that DNNs can be trained to analyze multiple frequencies and reasonably predict the pattern propagation factor, offering an alternative to traditional methods.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"74 1","pages":"1263-1268"},"PeriodicalIF":5.8,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11197212","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2025-09-22DOI: 10.1109/TAP.2025.3610231
Jorge Gomez-Ponce;Dmitry Chizhik;Jinfeng Du;Reinaldo Valenzuela;Kelvin Arana;Naveed A. Abbasi;Andreas F. Molisch
Ray tracers (RTs) are widely used tools to simulate wireless communication channels. For high-frequency bands (e.g., mm-waves), RT using only building databases overpredicts parameters such as path gain (PG) in line-of-sight (LoS) urban canyons environments due to the lack of accounting for street-clutter (SC) effects, primarily foliage. This work presents a systematic measurement-based modeling treatment for incorporating clutter into classical RT simulations, including homogeneous absorbing volumes, reflection coefficient, and clutter loss definition. Ten different configurations were tested for the added volumes, and an extensive evaluation against a measurement dataset of over 1000 links and 150 000 power samples was done to validate the statistical robustness of the approach. PG root-mean-square error (RMSE) between fits based on RT and measurement samples from 11 different routes in Manhattan, NY, USA, were reduced from 12.5 to 6.6 dB by including street-clutter effects, while 3GPP LoS model results in 9.8-dB RMSE.
{"title":"Efficient Integration of Street Clutter Into mm-Wave Ray Tracing in Urban Environments Based on More Than 1000 Measurements","authors":"Jorge Gomez-Ponce;Dmitry Chizhik;Jinfeng Du;Reinaldo Valenzuela;Kelvin Arana;Naveed A. Abbasi;Andreas F. Molisch","doi":"10.1109/TAP.2025.3610231","DOIUrl":"https://doi.org/10.1109/TAP.2025.3610231","url":null,"abstract":"Ray tracers (RTs) are widely used tools to simulate wireless communication channels. For high-frequency bands (e.g., mm-waves), RT using only building databases overpredicts parameters such as path gain (PG) in line-of-sight (LoS) urban canyons environments due to the lack of accounting for street-clutter (SC) effects, primarily foliage. This work presents a systematic measurement-based modeling treatment for incorporating clutter into classical RT simulations, including homogeneous absorbing volumes, reflection coefficient, and clutter loss definition. Ten different configurations were tested for the added volumes, and an extensive evaluation against a measurement dataset of over 1000 links and 150 000 power samples was done to validate the statistical robustness of the approach. PG root-mean-square error (RMSE) between fits based on RT and measurement samples from 11 different routes in Manhattan, NY, USA, were reduced from 12.5 to 6.6 dB by including street-clutter effects, while 3GPP LoS model results in 9.8-dB RMSE.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"74 1","pages":"1257-1262"},"PeriodicalIF":5.8,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-19DOI: 10.1109/TAP.2025.3607274
Tingting Chen;Lizhong Song;Youkui Zhang;Min Zhang
This study presents a reconfigurable folded transmitarray (RFTA) capable of dual-polarization beam scanning in both the azimuth and elevation planes. A wideband fan-cross-shaped (FCS) unit cell which constitutes the reconfigurable transmitarray (RTA), separates the polarization and phase control layers, exhibiting high cross-polarization isolation and enabling polarization selection (PS), polarization conversion, and phase modulation. The bias lines are elaborately designed to ensure that the control lines for both polarizations are located on the same layer, thus significantly reducing the design complexity. Subsequently, a wheel-rudder-shaped reflective unit cell is developed to form a dual-polarized reflectarray (DPRA) with phase control capabilities, replacing traditional polarization-selective surfaces. The three components of the dual-polarized RFTA (DPRFTA)—DPRTA, DPRA, and feed—are fabricated, assembled, and measured. The array aperture size is $4.91lambda _{0}, times 4.91 lambda _{0}$ , with an H/D ratio of 0.17, and the profile height is one-third that of conventional RTAs. Simulation and measurement results confirm that the proposed DPRFTA can achieve beam steering of ±60°, with a peak gain of 16.85 dBi and an aperture efficiency of 16%. The proposed DPRFTA integrates key technologies, including folded structure, dual-polarization operation, and electronic reconfiguration, demonstrating a broad application prospect in modern communication and radar systems.
{"title":"A Dual-Polarized Reconfigurable Folded Transmitarray With Beam-Scanning Capabilities","authors":"Tingting Chen;Lizhong Song;Youkui Zhang;Min Zhang","doi":"10.1109/TAP.2025.3607274","DOIUrl":"https://doi.org/10.1109/TAP.2025.3607274","url":null,"abstract":"This study presents a reconfigurable folded transmitarray (RFTA) capable of dual-polarization beam scanning in both the azimuth and elevation planes. A wideband fan-cross-shaped (FCS) unit cell which constitutes the reconfigurable transmitarray (RTA), separates the polarization and phase control layers, exhibiting high cross-polarization isolation and enabling polarization selection (PS), polarization conversion, and phase modulation. The bias lines are elaborately designed to ensure that the control lines for both polarizations are located on the same layer, thus significantly reducing the design complexity. Subsequently, a wheel-rudder-shaped reflective unit cell is developed to form a dual-polarized reflectarray (DPRA) with phase control capabilities, replacing traditional polarization-selective surfaces. The three components of the dual-polarized RFTA (DPRFTA)—DPRTA, DPRA, and feed—are fabricated, assembled, and measured. The array aperture size is <inline-formula> <tex-math>$4.91lambda _{0}, times 4.91 lambda _{0}$ </tex-math></inline-formula>, with an H/D ratio of 0.17, and the profile height is one-third that of conventional RTAs. Simulation and measurement results confirm that the proposed DPRFTA can achieve beam steering of ±60°, with a peak gain of 16.85 dBi and an aperture efficiency of 16%. The proposed DPRFTA integrates key technologies, including folded structure, dual-polarization operation, and electronic reconfiguration, demonstrating a broad application prospect in modern communication and radar systems.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"73 12","pages":"10907-10912"},"PeriodicalIF":5.8,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This communication proposes a dual-linear polarized 2-bit reconfigurable transmitarray (DLPRTA) operating at Ku-band. The independent dual-linear polarization unit cell consists of two mutually orthogonal subunit cells with identical structures. The subunit cell is a receiver–transmitter structure, which is composed of an active symmetrical receiving dipole and an active asymmetric transmitting dipole, respectively, integrated with a pair of p-i-n diodes. A total of four p-i-n diodes of each subunit cell realize four operating states of the 2-bit phase quantization. A DLPRTA prototype consisting of $22 times 22$ unit cells was designed, fabricated, and measured. At 15.2 GHz, the maximum gains of the DLPRTA in x- and y-polarization are 24.65 and 24.61 dBi, respectively, corresponding to the aperture efficiency (AE) of 23.85% and 23.59%. Its beam scanning capability has also been verified to cover the scan range of ±50° in both linear polarizations with sidelobe levels (SLL) lower than 10 dB. The gain loss of the maximum angle beam scanning are 2.26 and 2.37 dB, respectively, which proved good beam scanning performance.
{"title":"Dual-Linear Polarized 2-bit Reconfigurable Transmitarray at Ku-Band","authors":"Xiangshuai Meng;Yujie Wang;Haoyu Zhang;Tao Wu;Anxue Zhang;Xiaoming Chen","doi":"10.1109/TAP.2025.3605995","DOIUrl":"https://doi.org/10.1109/TAP.2025.3605995","url":null,"abstract":"This communication proposes a dual-linear polarized 2-bit reconfigurable transmitarray (DLPRTA) operating at Ku-band. The independent dual-linear polarization unit cell consists of two mutually orthogonal subunit cells with identical structures. The subunit cell is a receiver–transmitter structure, which is composed of an active symmetrical receiving dipole and an active asymmetric transmitting dipole, respectively, integrated with a pair of p-i-n diodes. A total of four p-i-n diodes of each subunit cell realize four operating states of the 2-bit phase quantization. A DLPRTA prototype consisting of <inline-formula> <tex-math>$22 times 22$ </tex-math></inline-formula> unit cells was designed, fabricated, and measured. At 15.2 GHz, the maximum gains of the DLPRTA in x- and y-polarization are 24.65 and 24.61 dBi, respectively, corresponding to the aperture efficiency (AE) of 23.85% and 23.59%. Its beam scanning capability has also been verified to cover the scan range of ±50° in both linear polarizations with sidelobe levels (SLL) lower than 10 dB. The gain loss of the maximum angle beam scanning are 2.26 and 2.37 dB, respectively, which proved good beam scanning performance.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"73 12","pages":"10871-10876"},"PeriodicalIF":5.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-10DOI: 10.1109/TAP.2025.3600943
{"title":"Institutional Listings","authors":"","doi":"10.1109/TAP.2025.3600943","DOIUrl":"https://doi.org/10.1109/TAP.2025.3600943","url":null,"abstract":"","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"73 9","pages":"C4-C4"},"PeriodicalIF":5.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11156171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
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