Real-Time Beam steering in mmWave with Reconfigurable Intelligent Meta-surfaces - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2021

Real-Time Beam steering in mmWave with Reconfigurable Intelligent Meta-surfaces

Carola Rizza
  • Function : Author
  • PersonId : 1074591
Valeria Loscrí
  • Function : Author
  • PersonId : 1084587

Abstract

The control logic of a reconfigurable meta-surface in mmWave is investigated in order to perform real-time beam steering in mobility contexts. When it is necessary to track an object or a person in movement, it is required to change the direction of the signal transmitted/reflected by the metasurface. To do so, the meta-surface has to be reconfigured to modify the generated radiation pattern. Here a specific metasurface, working around 78.5 GHz, is adopted, which consists of many unit-cells containing a diode to make its electromagnetic behaviour reconfigurable. In order to enable the system to adaptively compute the new coding schemes, namely to change the states of the meta-surface unit-cells, a machine-learning algorithm is adopted. In particular, we propose a Genetic Algorithm, integrate it in the architecture of our meta-surface and evaluate the performance. Results show that a good accuracy and a good convergence time are achieved for real-time beam steering functionality and the capacity of the system equipped with RIM (reconfigurable intelligent metasurface) is increased.
Fichier principal
Vignette du fichier
Real_Time_Beam_steering_in_mmWave_with_Reconfigurable_Intelligent_Meta_surfaces_based_on_a_Genetic_Algorithm (1).pdf (641.8 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03335444 , version 1 (06-09-2021)

Identifiers

  • HAL Id : hal-03335444 , version 1

Cite

Carola Rizza, Valeria Loscrí, Mohammad Ojaroudi Parchin. Real-Time Beam steering in mmWave with Reconfigurable Intelligent Meta-surfaces. IEEE Global Communications Conference, Dec 2021, Madrid, Spain. ⟨hal-03335444⟩

Collections

INRIA INRIA2
176 View
602 Download

Share

Gmail Mastodon Facebook X LinkedIn More