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تسجيل مستخدم جديدRobust Reconfigurable Intelligent Surfaces via Invariant Risk and Causal Representations
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نشر من قبل
Sumudu Samarakoon Dr.
تاريخ النشر
2021
مجال البحث
الهندسة المعلوماتية
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English
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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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Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), or large intelligent surfaces (LISs), have received significant attention for their potential to enhance the capacity and coverage of wireless networks
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