TY - GEN
T1 - Exact Statistics and Tight Approximations for RIS-Assisted Communications in Generalized Fading Environments
AU - Luna Alvarado, Maria Cecilia
AU - Rafael Nogueira Da Silva, Carlos
AU - Simmons, Nidhi
AU - Sofotasios, Paschalis C.
AU - Cotton, Simon L.
AU - Yacoub, Michel Daoud
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Reconfigurable Intelligent Surfaces (RISs) are considered a key candidate technology for next-generation 6G wireless systems, promising to extend network coverage, enhance spectral efficiency, and effectively mitigate interference. RISs will achieve this by controlling the propagation environment, enabled by carefully altering the reflective properties of their elements. In this context, this work presents a general framework for deriving the exact probability density function (PDF) and higher-order moments of the signal-to-ratio (SNR) in a RIS system, considering the direct transmission and RIS-assisted links from source to destination. Recognizing the analytical challenges associated with obtaining exact statistics for RIS-assisted systems, which persist in both common and more generalized fading models, the proposed contribution is realized with the aid of the suitable α-μ fading model. To that end, we derive accurate approximations for the κ-μ and the extended η-μ distributions, which constitute effective and versatile multipath fading models. Based on this, the achieved results are virtually indistinguishable from those obtained through simulations for various environmental settings. This renders the proposed framework a valuable tool for evaluating the performance of RIS systems, particularly in terms of the corresponding average symbol error rate (ASER). Tractable closed-form asymptotic expressions are also derived and utilized to provide a deeper understanding of the system's behavior.
AB - Reconfigurable Intelligent Surfaces (RISs) are considered a key candidate technology for next-generation 6G wireless systems, promising to extend network coverage, enhance spectral efficiency, and effectively mitigate interference. RISs will achieve this by controlling the propagation environment, enabled by carefully altering the reflective properties of their elements. In this context, this work presents a general framework for deriving the exact probability density function (PDF) and higher-order moments of the signal-to-ratio (SNR) in a RIS system, considering the direct transmission and RIS-assisted links from source to destination. Recognizing the analytical challenges associated with obtaining exact statistics for RIS-assisted systems, which persist in both common and more generalized fading models, the proposed contribution is realized with the aid of the suitable α-μ fading model. To that end, we derive accurate approximations for the κ-μ and the extended η-μ distributions, which constitute effective and versatile multipath fading models. Based on this, the achieved results are virtually indistinguishable from those obtained through simulations for various environmental settings. This renders the proposed framework a valuable tool for evaluating the performance of RIS systems, particularly in terms of the corresponding average symbol error rate (ASER). Tractable closed-form asymptotic expressions are also derived and utilized to provide a deeper understanding of the system's behavior.
KW - cascaded channels
KW - product distribution
KW - reconfigurable intelligent surfaces
KW - α-μ distribution
UR - https://www.scopus.com/pages/publications/85213061333
U2 - 10.1109/VTC2024-Fall63153.2024.10757729
DO - 10.1109/VTC2024-Fall63153.2024.10757729
M3 - Conference contribution
AN - SCOPUS:85213061333
T3 - IEEE Vehicular Technology Conference
BT - 2024 IEEE 100th Vehicular Technology Conference, VTC 2024-Fall - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 100th IEEE Vehicular Technology Conference, VTC 2024-Fall
Y2 - 7 October 2024 through 10 October 2024
ER -