Consider a communication system in which a single- antenna user equipment exchanges information with a multi- antenna base station via a reconfigurable intelligent surface (RIS) in the presence of spatially correlated channels and electromagnetic interference (EMI). To exploit the attractive advantages of RIS technology, accurate configuration of its reflecting elements is crucial. In this paper, we use statistical knowledge of channels and EMI to optimize the RIS elements for i) accurate channel estimation and ii) reliable data transmission. In both cases, our goal is to determine the RIS coefficients that minimize the mean square error, resulting in the formulation of two non-convex problems that share the same structure. To solve these two problems, we present an alternating optimization approach that reliably converges to a locally optimal solution. The incorporation of the diagonally scaled steepest descent algo- rithm, derived from Newton’s method, ensures fast convergence with manageable complexity. Numerical results demonstrate the effectiveness of the proposed method under various propagation conditions. Notably, it shows significant advantages over existing alternatives that depend on a suboptimal configuration of the RIS and are derived on the basis of different criteria.

MMSE Design of RIS-Aided Communications with Spatially-Correlated Channels and Electromagnetic Interference

WenXuan Long
;
Marco Moretti;Luca Sanguinetti;
2024-01-01

Abstract

Consider a communication system in which a single- antenna user equipment exchanges information with a multi- antenna base station via a reconfigurable intelligent surface (RIS) in the presence of spatially correlated channels and electromagnetic interference (EMI). To exploit the attractive advantages of RIS technology, accurate configuration of its reflecting elements is crucial. In this paper, we use statistical knowledge of channels and EMI to optimize the RIS elements for i) accurate channel estimation and ii) reliable data transmission. In both cases, our goal is to determine the RIS coefficients that minimize the mean square error, resulting in the formulation of two non-convex problems that share the same structure. To solve these two problems, we present an alternating optimization approach that reliably converges to a locally optimal solution. The incorporation of the diagonally scaled steepest descent algo- rithm, derived from Newton’s method, ensures fast convergence with manageable complexity. Numerical results demonstrate the effectiveness of the proposed method under various propagation conditions. Notably, it shows significant advantages over existing alternatives that depend on a suboptimal configuration of the RIS and are derived on the basis of different criteria.
2024
Long, Wenxuan; Moretti, Marco; Abrardo, Andrea; Sanguinetti, Luca; Chen, Rui
File in questo prodotto:
File Dimensione Formato  
MMSE_Design_of_RIS-Aided_Communications_with_Spatially-Correlated_Channels_and_Electromagnetic_Interference.pdf

accesso aperto

Tipologia: Documento in Post-print
Licenza: Creative commons
Dimensione 1.6 MB
Formato Adobe PDF
1.6 MB Adobe PDF Visualizza/Apri
printedVersion.pdf

accesso aperto

Tipologia: Versione finale editoriale
Licenza: Creative commons
Dimensione 10.84 MB
Formato Adobe PDF
10.84 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1272847
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 3
social impact