TY - GEN
T1 - Statistical Characterization of SNR in RIS-Aided Wireless Communication Systems
AU - Aghdam, Mohammad Reza Ghavidel
AU - Elamassie, Mohammed
AU - Uysal, Murat
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Reconfigurable intelligent surfaces (RISs) can significantly improve overall communication quality by mitigating the adverse effects of multipath fading, reducing interference, and extending coverage areas. Most existing works on RIS focus on far-field scenarios and large-scale RIS configurations, where the central limit theorem (CLT) is often used to approximate the distribution of the cascaded channels. However, such an approximation may not accurately reflect the performance of RIS in near-field conditions or when the number of reflecting elements is small. In this paper, we provide a statistical characterization of signal-to-noise ratio (SNR) in RIS-assisted wireless systems in near-field conditions with a small number of RIS elements. Our results demonstrate that Gamma distribution accurately depicts instantaneous SNR distribution. The proposed model provides an accurate tool for understanding and predicting the performance of RIS systems under diverse operational conditions.
AB - Reconfigurable intelligent surfaces (RISs) can significantly improve overall communication quality by mitigating the adverse effects of multipath fading, reducing interference, and extending coverage areas. Most existing works on RIS focus on far-field scenarios and large-scale RIS configurations, where the central limit theorem (CLT) is often used to approximate the distribution of the cascaded channels. However, such an approximation may not accurately reflect the performance of RIS in near-field conditions or when the number of reflecting elements is small. In this paper, we provide a statistical characterization of signal-to-noise ratio (SNR) in RIS-assisted wireless systems in near-field conditions with a small number of RIS elements. Our results demonstrate that Gamma distribution accurately depicts instantaneous SNR distribution. The proposed model provides an accurate tool for understanding and predicting the performance of RIS systems under diverse operational conditions.
KW - Gamma Distribution
KW - Near-and Far-Field
KW - Probability Density Function
KW - Reconfigurable Intelligent Surface
UR - http://www.scopus.com/inward/record.url?scp=86000269496&partnerID=8YFLogxK
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U2 - 10.1109/MECOM61498.2024.10881405
DO - 10.1109/MECOM61498.2024.10881405
M3 - Conference contribution
AN - SCOPUS:86000269496
T3 - 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024
SP - 286
EP - 290
BT - 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024
Y2 - 17 November 2024 through 20 November 2024
ER -