2019/07/09 by Christos Liaskos, George Pirialakos, Liaskos, C. +29 · 1 citation
Engineering · Materials Science · #Advanced Antenna and Metasurface Technologies #Antenna Design and Analysis #FOS: Electrical engineering #Metamaterials and Metasurfaces Applications #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1907.04811
openalex publication_date 2019/07/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Metasurfaces constitute effective media for manipulating and transforming impinging EM waves. Related studies have explored a series of impactful MS capabilities and applications in sectors such as wireless communications, medical imaging and energy harvesting. A key-gap in the existing body of work is that the attributes of the EM waves to-be-controlled (e.g., direction, polarity, phase) are known in advance. The present work proposes a practical solution to the EM wave sensing problem using the intelligent and networked MS counterparts-the HyperSurfaces (HSFs), without requiring dedicated field sensors. An nano-network embedded within the HSF iterates over the possible MS configurations, finding the one that fully absorbs the impinging EM wave, hence maximizing the energy distribution within the HSF. Using a distributed consensus approach, the nano-network then matches the found configuration to the most probable EM wave traits, via a static lookup table that can be created during the HSF manufacturing. Realistic simulations demonstrate the potential of the proposed scheme. Moreover, we show that the proposed workflow is the first-of-its-kind embedded EM compiler, i.e., an autonomic HSF that can translate high-level EM behavior objectives to the corresponding, low-level EM actuation commands.