Full-Range Amplitude–Phase Metacells for Sidelobe Suppression of Metalens Antenna Using Prior-Knowledge-Guided Deep- Learning -Enabled Synthesis
Abstract
A prior-knowledge-guided deep-learning-enabled (PK-DL) synthesis method is proposed to design the metacells with the full-range amplitude and phase control for suppressing the sidelobe levels (SLLs) of a metalens antenna. The PK-DL synthesis method is based on a conditional deep convolutional generative adversarial network (cDCGAN). First, the metacells are pixelated to offer the higher degrees of design freedom and expand their transmission responses to full 2-D coverage of amplitude and phase responses so that a full-range metacell dataset is built up to simultaneously control the amplitude and phase of a single metacell. Conventionally, by optimizing the dimensions of predefined patterns of a metacell, only the phase response of a single metacell is achieved with a specific amplitude response, and vice versa. The metalens design based on the synthesized metacells has much higher degrees of freedom so that the metalens antenna has the potential to break the ceiling of performance and to realize more functions than existing metalens designs. As examples, two types of single-lens metalens antennas are designed for sidelobe suppression using the proposed metacell dataset. The first metalens is excited by a dipole antenna with an omnidirectional radiation pattern to demonstrate the simultaneous control of amplitude and phase responses using the synthesized metacells. The second metalens fed by a standard horn antenna is designed to suppress the SLLs in both the E- and H-planes.…
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Liu et al. synthesized a triple-layer meta-atom that enables precise phase shift control across a range of 330°, with a signal loss of less than -1 dB, facilitating the design of metalens that can effectively suppress sidelobes.
“Moreover, Liu et al. [77], [78] synthesized a triple-layer meta-atom that enables precise phase shift control across a range of 330 ◦ , with a signal loss of less than -1 dB. This breakthrough has facilitated the design of metalens that can effectively suppress sidelobes.”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [78]
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Yun, D., Jung, H., Hwang, I., Kim, J.-H., Lee, I., Hong, Y., & Park, J. (2025) · IEEE Antennas and Wireless Propagation Letters · doi:10.1109/lawp.2025.3640591 · Cited by 1 · see citing works
Fan, T., & Zhang, W. (2025) · IEEE Antennas and Wireless Propagation Letters · doi:10.1109/lawp.2025.3613764 · Cited by 1 · see citing works
Filtering Antenna Design and Optimization by the Generative Machine Learning Approach
Cui, L., Huang, K. F., Zhong, Y., Zhang, Y., & Liu, Q. H. (2026) · IEEE Transactions on Antennas and Propagation · doi:10.1109/tap.2026.3653131 · Cited by 1 · see citing works
Generative Adversarial Network-Enabled Inverse Design of Multifunctional Metasurfaces
Liu, X., Cao, X., Hong, T., & Jiang, W. T. (2025) · doi:10.23919/isap63122.2025.11362042 · Cited by 1 · see citing works
Machine-Learning-Based Optimization for Wideband Metasurface Mosaic Antenna
Liu, P., Yan, X., & Chen, Z. N. (2024) · European Conference on Antennas and Propagation · doi:10.23919/eucap60739.2024.10501248 · Cited by 1 · see citing works
Self-citationPrior Knowledge-Guided Deep Learning-Enabled Metantenna Optimization and Synthesis (Invited)
Liu, P., & Chen, Z. N. (2025) · International Workshop on Antenna Technology · doi:10.1109/iwat64079.2025.10931202 · Cited by 1 · see citing works
Self-citationEmerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications
An, J., Debbah, M., Cui, T. J., Chen, Z. N., & Yuen, C. (2024) · arXiv · Cited by 72 · see citing works
“Moreover, Liu et al. [77] and Liu and Chen [78] synthesized a triple-layer meta-atom that enables precise phase-shift control across a range of 330 ◦ , with a signal loss of less than − 1 dB.”
Self-citation(2023) · IEEE Transactions on Antennas and Propagation · doi:10.1109/tap.2023.3273960
Prior-Knowledge-Guided Structural Optimization Method for Microwave Component Design
Qin, P., Li, W., & Huang, G. (2023) · IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP) · doi:10.1109/imws-amp57814.2023.10381104
A Compact Horn Antenna with Low Sidelobes
Harari, G., Nikson, N., Bauer, R., & Matzner, H. (2024) · European Conference on Antennas and Propagation · doi:10.23919/eucap60739.2024.10501655
Dual-Polar Antenna Sidelobe Reduction Through Metasurfaces
Wang, E., & Yang, J. B. (2024) · International Telecommunications Conference (ITC-Egypt) · doi:10.1109/itc-egypt61547.2024.10620523
Research on Broadband W-Band Reflectarray Element Based on Machine Learning Optimization Method
Yang, R., Zhao, J., Li, H., Li, T., Fu, C., Hu, B., Wang, H., & Zhou, Y. (2024) · International Conference on Microwave and Millimeter Wave Technology (ICMMT) · doi:10.1109/icmmt61774.2024.10672452
A Polarization-Insensitive Pancharatnam-Berry Phase Broadband Achromatic Metasurface
Wu, Y., Deng, L. F., & Chen, L. (2024) · International Conference on Microwave and Millimeter Wave Technology (ICMMT) · doi:10.1109/icmmt61774.2024.10671602
Jiang, Y., Rao, J., Xu, G., Zhao, L., Li, Y., & Huang, Z. X. (2025) · International Conference on Microwave and Millimeter Wave Technology (ICMMT) · doi:10.1109/icmmt65948.2025.11188078
Machine Learning-Based Optimization of Beam Steering in Reconfigurable Mushroom Antenna
Liu, P., Gan, Y., & Chen, Z. N. (2025) · IEEE Asia-Pacific Conference on Antennas and Propagation · doi:10.1109/apcap65837.2025.11210497
Self-citationLv, Y., & Chen, Z. N. (2025) · IEEE Asia-Pacific Conference on Antennas and Propagation · doi:10.1109/apcap65837.2025.11210470
Self-citationPrior Knowledge-Guided Deep Learning-Enabled Methods for Generative Design of Metacells
Lv, Y., Hong, Y., & Chen, Z. N. (2025) · Digest - IEEE Antennas and Propagation Society. International Symposium · doi:10.1109/ap-s/cnc-usnc-ursi55537.2025.11266530
Self-citationGenerative Deep Learning-Enabled Method for Interconnected Metasurface Antenna Designs
Hong, Y., Lyu, Y., & Chen, Z. N. (2025) · Digest - IEEE Antennas and Propagation Society. International Symposium · doi:10.1109/ap-s/cnc-usnc-ursi55537.2025.11266786
Self-citationPrior Knowledge in Deep Learning-Enabled Generative Design of Metalens Antennas
Chen, Z. N., Liu, P., & Lyu, Y. (2025) · International Conference on Electromagnetics in Advanced Applications (ICEAA) · doi:10.1109/iceaa65662.2025.11306076
Self-citationLiu, P., & Chen, Z. N. (2026) · IEEE Transactions on Antennas and Propagation · doi:10.1109/tap.2026.3661752
Self-citationMeng, X., Liu, S., Zhang, H., Wu, T., Zhang, A., & Chen, X. (2026) · Advanced Materials Technologies · doi:10.1002/admt.70970
Small-Sample Machine Learning-Based Design Framework for Pixelated Reflective Metasurfaces
Zhou, Z., He, Y., & Lin, W. (2026) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2026.3691457
Lyu, Y., Tong, D., & Chen, Z. N. (2026) · IEEE Transactions on Antennas and Propagation · doi:10.1109/tap.2026.3696819
Self-citationWu, Q. H., Mo, X., Liu, P., You, J. W., Chen, Z. N., Hong, W., & Wang, H. M. (2026) · IEEE Journal of Selected Topics in Electromagnetics Antennas and Propagation · doi:10.1109/jsteap.2026.3708095
Self-citationSolanki, R., Lee, C. W. L., Tan, P. K., & Gan, T. H. (2026) · IEEE Journal on Miniaturization for Air and Space Systems · doi:10.1109/jmass.2026.3715681
Lee, C. W. L., Solanki, R., Tan, P. K., & Gan, T. H. (2026) · European Conference on Antennas and Propagation · doi:10.23919/eucap68105.2026.11612749
Machine Learning-Based Active S-Parameter Modeling for Linear Antenna Arrays
Liu, P., Wu, Y., & Chen, Z. N. (2026) · European Conference on Antennas and Propagation · doi:10.23919/eucap68105.2026.11612540
Self-citationImagery Modeling for Microwave Engineering with Unsupervised Variational Autoencoder
Yue, S.-Z., Wengao, Z., Shao, W., & Xiao, D. (2026) · Journal of Systems Engineering and Electronics · doi:10.23919/jsee.2026.000140
Liu, Q. Z., & Ren, X. S. (2026) · IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP) · doi:10.1109/imws-amp68843.2026.11684095
Liang, H., Zhang, J., Wang, Y., Wei, X., Ma, R., & Yang, R. (2026) · Applied Optics · doi:10.1364/ao.610664
- Authors
- Liu, P., & Chen, Z. N.
- Affiliations
- National University of Singapore (SG)
- Venue
- IEEE Transactions on Antennas and Propagation
- Published
- 2023-06
- Volume
- 71
- Issue
- 6
- Pages
- 5036-5045
- ISSN
- 0018-926X (ISSN-L)
- 1558-2221
- OpenAlex
- W4362714501
- Cited by
- 75
- References
- 49
- Citations by year
- 2026: 18 · 2025: 24 · 2024: 26 · 2023: 7
- FWCI
- 9.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Antennas and Propagation (publishedVersion)
- Funders
- Advanced Research and Technology Innovation Centre (ARTIC), the National University of Singapore (A-0005947-15-00)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Advanced Antenna and Metasurface Technologies
- Physical Sciences › Materials Science › Electronic, Optical and Magnetic Materials › Metamaterials and Metasurfaces Applications
- Physical Sciences › Engineering › Aerospace Engineering › Antenna Design and Optimization
- Keywords
- metacells, sidelobe suppression, amplitude and phase control, metasurface synthesis
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