This paper evaluates the performance of reconfigurable intelligent surface (RIS) optimization algorithms, which utilize channel estimation methods, in ray tracing (RT) simulations within urban digital twin environments. Beyond Sionna’s native capabilities, we implement and benchmark additional RIS optimization algorithms based on channel estimation, enabling an evaluation of RIS strategies under various deployment conditions. Coverage maps for RIS-assisted communication systems are generated through t...
This paper evaluates the performance of reconfigurable intelligent surface (RIS) optimization algorithms, which utilize channel estimation methods, in ray tracing (RT) simulations within urban digital twin environments. Beyond Sionna’s native capabilities, we implement and benchmark additional RIS optimization algorithms based on channel estimation, enabling an evaluation of RIS strategies under various deployment conditions. Coverage maps for RIS-assisted communication systems are generated through the integration of Sionna’s RT simulations. Moreover, real-world experimentation underscores the necessity of validating algorithms in near-realistic simulation environments, as minor variations in measurement setups can significantly affect performance.
RIS Optimization Algorithms for Urban Wireless Scenarios in Sionna RT
Ahmet Esad Güneşer, Kocaeli University; Berkay Şekeroğlu, Boğaziçi University; Sefa Kayraklık, TÜBİTAK BİLGEM; Erhan Karakoca, TUBITAK BILGEM; İbrahim Hökelek, TÜBİTAK; Sultan Aldirmaz Colak, Kocaeli University; Ali Gorcin, Istanbul Technical University
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