TY - GEN
T1 - Intelligent RIS-enabled System Management
AU - Kouvakis, Vasileios
AU - Timotijevic, Aris Karampelas
AU - Chrysologou, Athanasios P.
AU - Trevlakis, Stylianos E.
AU - Tsiftsis, Theodoros A.
N1 - Publisher Copyright:
© 2026 pplied Computational Electromagnetics Society.
PY - 2026
Y1 - 2026
N2 - This paper introduces two novel artificial intelligence-driven frameworks for real-time management in practical reconfigurable intelligent surface-assisted wireless systems. By using realistic ray-tracing simulations in urban environments, a comprehensive comparative performance analysis between the established spiking neural network architecture and the proposed liquid neural network-based model is presented, highlighting their respective strengths and limitations in intelligent system management.
AB - This paper introduces two novel artificial intelligence-driven frameworks for real-time management in practical reconfigurable intelligent surface-assisted wireless systems. By using realistic ray-tracing simulations in urban environments, a comprehensive comparative performance analysis between the established spiking neural network architecture and the proposed liquid neural network-based model is presented, highlighting their respective strengths and limitations in intelligent system management.
UR - https://www.scopus.com/pages/publications/105045179244
M3 - Conference contribution
AN - SCOPUS:105045179244
T3 - 2026 International Applied Computational Electromagnetics Society Symposium, ACES-Greece 2026
BT - 2026 International Applied Computational Electromagnetics Society Symposium, ACES-Greece 2026
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2026 International Applied Computational Electromagnetics Society Symposium, ACES-Greece 2026
Y2 - 24 May 2026 through 27 May 2026
ER -