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
|Author:||Samarakoon, Sumudu1; Park, Jihong2; Bennis, Mehdi1|
1Centre for Wireless Communication, University of Oulu, Finland
2School of Information Technology, Deakin University, Geelong, VIC 3220, Australia
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202301031248
Institute of Electrical and Electronics Engineers,
|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.
|Pages:||301 - 305|
22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2021
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
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 (Academy of Finland Funding decision)
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.