Metasurfaces-Enabled Wave Computing for Future Wireless Systems: Opportunities and Challenges
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914246207471616 |
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| author | Omam, Zahra Rahimian Taghvaee, Hamidreza Araghi, Ali Garcia-Fernandez, Maria Alvarez-Narciandi, Guillermo Alexandropoulos, George C. Yurduseven, Okan Khalily, Mohsen |
| author_facet | Omam, Zahra Rahimian Taghvaee, Hamidreza Araghi, Ali Garcia-Fernandez, Maria Alvarez-Narciandi, Guillermo Alexandropoulos, George C. Yurduseven, Okan Khalily, Mohsen |
| contents | The next generations of wireless networks are envisioned to integrate communications, sensing, and computing into a unified platform, demanding ultra-high data rates, submillisecond latency, and unprecedented energy efficiency. However, conventional digital processors face limitations in scalability, cost, and power consumption that hinder this vision. Wave computing, enabled by programmable metasurfaces, offers an alternative paradigm according to which signal processing operations are implemented in the domain of the propagation of electromagnetic waves. This approach transforms metasurfaces from passive wavefront shapers into functional analog processors capable of executing tasks such as beamforming, sensing, imaging, and machine learning at the speed of light with minimal power consumption. This article provides an overview of metasurface-enabled wave computing, highlighting its fundamental principles and key application scenarios for future wireless systems, including integrated sensing and communications, artificial intelligence acceleration, over-the-air channel estimation, and computational electromagnetic imaging. Future research directions are outlined in response to the major open challenges of the technology, aiming to enable large-scale deployment of wave computing in practical wireless networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_05173 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Metasurfaces-Enabled Wave Computing for Future Wireless Systems: Opportunities and Challenges Omam, Zahra Rahimian Taghvaee, Hamidreza Araghi, Ali Garcia-Fernandez, Maria Alvarez-Narciandi, Guillermo Alexandropoulos, George C. Yurduseven, Okan Khalily, Mohsen Signal Processing Applied Physics The next generations of wireless networks are envisioned to integrate communications, sensing, and computing into a unified platform, demanding ultra-high data rates, submillisecond latency, and unprecedented energy efficiency. However, conventional digital processors face limitations in scalability, cost, and power consumption that hinder this vision. Wave computing, enabled by programmable metasurfaces, offers an alternative paradigm according to which signal processing operations are implemented in the domain of the propagation of electromagnetic waves. This approach transforms metasurfaces from passive wavefront shapers into functional analog processors capable of executing tasks such as beamforming, sensing, imaging, and machine learning at the speed of light with minimal power consumption. This article provides an overview of metasurface-enabled wave computing, highlighting its fundamental principles and key application scenarios for future wireless systems, including integrated sensing and communications, artificial intelligence acceleration, over-the-air channel estimation, and computational electromagnetic imaging. Future research directions are outlined in response to the major open challenges of the technology, aiming to enable large-scale deployment of wave computing in practical wireless networks. |
| title | Metasurfaces-Enabled Wave Computing for Future Wireless Systems: Opportunities and Challenges |
| topic | Signal Processing Applied Physics |
| url | https://arxiv.org/abs/2501.05173 |