University of Oulu

S. Samarakoon, J. Park and M. Bennis, "Robust Reconfigurable Intelligent Surfaces via Invariant Risk and Causal Representations," 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2021, pp. 301-305, doi: 10.1109/SPAWC51858.2021.9593252.

Robust reconfigurable intelligent surfaces via invariant risk and causal representations

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Author: Samarakoon, Sumudu1; Park, Jihong2; Bennis, Mehdi1
Organizations: 1Centre for Wireless Communication, University of Oulu, Finland
2School of Information Technology, Deakin University, Geelong, VIC 3220, Australia
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2023-01-03


In this paper, the problem of robust reconfigurable intelligent surface (RIS) system design under changes in data distributions is investigated. Using the notion of invariant risk minimization (IRM), an invariant causal representation across multiple environments is used such that the predictor is simultaneously optimal for each environment. A neural network-based solution is adopted to seek the predictor and its performance is validated via simulations against an empirical risk minimization-based design. Results show that leveraging invariance yields more robustness against unseen and out-of-distribution testing environments.

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Series: SPAWC
ISSN: 1948-3244
ISSN-E: 1948-3252
ISSN-L: 1948-3244
ISBN: 978-1-6654-2851-4
ISBN Print: 978-1-6654-2852-1
Pages: 301 - 305
DOI: 10.1109/SPAWC51858.2021.9593252
Host publication: 22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2021
Conference: IEEE Workshop on Signal Processing Advances in Wireless Communications
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This research was partly supported by Academy of Finland6G Flagship (grant no.318927) and projects NEGEIN, SMARTER, EU-ICT IntellIoT, EUCHISTERA LearningEdge, and Infotech-NOOR.
EU Grant Number: (957218) IntellIoT - Intelligent, distributed, human-centered and trustworthy IoT environments
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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