Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/129703E9-CA30-4177-8BAD-4996461C283C | - |
| Identifier | https://doi.org/10.1109/ACCESS.2022.3219871 | - |
| Identifier | https://ieeexplore.ieee.org/document/9940297 | - |
| Language | en | - |
| Extent | 22 pages | en |
| Title | XR-RF imaging enabled by software-defined metasurfaces and machine learning: foundational vision, technologies and challenges | en |
| Creator | Liaskos Christos | en |
| Creator | Tsioliaridou Ageliki | en |
| Creator | Georgopoulos Konstantinos | en |
| Creator | Γεωργοπουλος Κωνσταντινος | el |
| Creator | Morianos Ioannis | en |
| Creator | Μοριανος Ιωαννης | el |
| Creator | Ioannidis Sotirios | en |
| Creator | Ιωαννιδης Σωτηριος | el |
| Creator | Salem Iosif | en |
| Creator | Manessis Dionysios | en |
| Creator | Schmid Stefan | en |
| Creator | Tyrovolas Dimitrios | en |
| Creator | Tegos Sotiris A. | en |
| Creator | Mekikis Prodromos-Vasileios | en |
| Creator | Diamantoulakis Panagiotis | en |
| Creator | Pitilakis Alexandros | en |
| Creator | Kantartzis, Nikolaos V | en |
| Creator | Karagiannidis, George K | en |
| Creator | Tasolamprou Anna | en |
| Creator | Tsilipakos Odysseas | en |
| Creator | Kafesaki Maria | en |
| Creator | Akyildiz, Ian Fuat | en |
| Creator | Pitsillides, Andreas | en |
| Creator | Pateraki Maria | en |
| Creator | Vakalellis Michael | en |
| Creator | Spais Ilias | en |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Description | This work was supported in part by the Foundation for research and technology-Hellas (FORTH) Synergy Grant WISAR; in part by the European Union's Horizon 2020 Research and Innovation Programme-Project COLLABS under Grant GA EU871518; in part by the European Research Council (ERC) (AdjustNet), 2020-2025, under Agreement 864228; in part by the European Union's Horizon 2020 Research and Innovation Programme under Agreement 957406; Bundesministerium fur Bildung und Forschung (BMBF) Project, 6G Research and Innovation Cluster (6G-RIC), 2021-2025, (ACCORDION), under Grant 871793 and Grant 101016509 (CHARITY). | en |
| Content Summary | In this work, we present a new approach to Extended Reality (XR), denoted as iCOPYWAVES, which seeks to offer naturally low-latency operation and cost effectiveness, overcoming the critical scalability issues faced by existing solutions. Specifically, iCOPYWAVES is enabled by emerging PWEs, a recently proposed technology in wireless communications. Empowered by intelligent metasurfaces, PWEs transform the wave propagation phenomenon into a software-defined process. To this end, we leverage PWEs to: i) create, and then ii) selectively copy the scattered RF wavefront of an object from one location in space to another, where a machine learning module, accelerated by FPGAs, translates it to visual input for an XR headset using PWE-driven, RF imaging principles (XR-RF). This makes an XR system whose operation is bounded in the physical-layer and, hence, has the prospects for minimal end-to-end latency. For the case of large distances, RF-to-fiber/fiber-to-RF is employed to provide intermediate connectivity. The paper provides a tutorial on the iCOPYWAVES system architecture and workflow. Finally, a proof-of-concept implementation via simulations is provided, demonstrating the reconstruction of challenging objects in iCOPYWAVES-produced computer graphics. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2023-12-14 | - |
| Date of Publication | 2022 | - |
| Subject | Extended/virtual/augmented reality | en |
| Subject | Software-defined networking | en |
| Subject | Wireless | en |
| Subject | XR-RF imaging | en |
| Subject | Machine learning | en |
| Subject | Propagation | en |
| Subject | Generative adversarial networks | en |
| Subject | Applications | en |
| Bibliographic Citation | C. Liaskos, A. Tsioliaridou, K. Georgopoulos, I. Morianos, S. Ioannidis, I. Salem, D. Manessis, S. Schmid, D. Tyrovolas, S. A. Tegos, P. -V. Mekikis, P. D. Diamantoulakis, A. Pitilakis, N. V. Kantartzis, G. K. Karagiannidis, A. C. Tasolamprou, O. Tsilipakos, M. Kafesaki, I. F. Akyildiz, A. Pitsillides, M. Pateraki, M. Vakalellis and I. Spais, "XR-RF imaging enabled by software-defined metasurfaces and machine learning: foundational vision, technologies and challenges," IEEE Access, vol. 10, pp. 119841-119862, 2022, doi: 10.1109/ACCESS.2022.3219871. | en |
Copyright © DIAS 2013
