8 research outputs found
Joint Compressed Sensing and Manipulation of Wireless Emissions with Intelligent Surfaces
Programmable, intelligent surfaces can manipulate electromagnetic waves
impinging upon them, producing arbitrarily shaped reflection, refraction and
diffraction, to the benefit of wireless users. Moreover, in their recent form
of HyperSurfaces, they have acquired inter-networking capabilities, enabling
the Internet of Material Properties with immense potential in wireless
communications. However, as with any system with inputs and outputs, accurate
sensing of the impinging wave attributes is imperative for programming
HyperSurfaces to obtain a required response. Related solutions include field
nano-sensors embedded within HyperSurfaces to perform minute measurements over
the area of the HyperSurface, as well as external sensing systems. The present
work proposes a sensing system that can operate without such additional
hardware. The novel scheme programs the HyperSurface to perform compressed
sensing of the impinging wave via simple one-antenna power measurements. The
HyperSurface can jointly be programmed for both wave sensing and wave
manipulation duties at the same time. Evaluation via simulations validates the
concept and highlight its promising potential.Comment: Published at IEEE DCOSS 2019 / IoT4.0 workshop
(https://www.dcoss.org/workshops.html). Funded by the European Union via the
Horizon 2020: Future Emerging Topics - Research and Innovation Action call
(FETOPEN-RIA), grant EU736876, project VISORSURF (http://www.visorsurf.eu
ABSense: Sensing Electromagnetic Waves on Metasurfaces via Ambient Compilation of Full Absorption
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.Comment: Publication: Proceedings of ACM NANOCOM 2019. This work was funded by
the European Union via the Horizon 2020: Future Emerging Topics call
(FETOPEN), grant EU736876, project VISORSURF (http://www.visorsurf.eu