TY - GEN
T1 - Reconfigurable Intelligent Surface-Aided MISO Systems with Statistical CSI
T2 - 22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2021
AU - Zhi, Kangda
AU - Pan, Cunhua
AU - Ren, Hong
AU - Wang, Kezhi
AU - Elkashlan, Maged
N1 - Funding Information:
This work was supported in part by the National Key Research and Development Project under Grant 2019YFE0123600, and the Research Fund of National Mobile Communications Research Laboratory, Southeast University (No.2021B01).
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This paper investigates the reconfigurable intelligent surface (RlS)-aided multiple-input-single-output (MISO) systems with imperfect channel state information (CSI), where RIS-related channels are modeled by Rician fading. Considering the overhead and complexity in practical systems, we employ the low-complexity maximum ratio combining (MRC) at the base station (BS), and configure the phase shifts of the RIS based on long-term statistical CSI. Specifically, we first estimate the overall channel matrix based on the linear minimum mean square error (LMMSE) estimator, and evaluate the performance of mean square error (MSE) and normalized MSE (NMSE). Then, with the estimated channel, we derive the closed-form expressions of the ergodic rate. The derived expressions show that with Rician RIS-related channels, the rate can maintain at a non-zero value when the transmit power is scaled down proportionally to 1 /M or 1 /N2, where M and N are the number of antennas and reflecting elements, respectively. However, if all the RIS-related channels are purely Rayleigh, the transmit power of each user can only be scaled down proportionally to 1√sqrt M or 1/N. Finally, numerical results verify the promising benefits from the RIS to traditional MISO systems.
AB - This paper investigates the reconfigurable intelligent surface (RlS)-aided multiple-input-single-output (MISO) systems with imperfect channel state information (CSI), where RIS-related channels are modeled by Rician fading. Considering the overhead and complexity in practical systems, we employ the low-complexity maximum ratio combining (MRC) at the base station (BS), and configure the phase shifts of the RIS based on long-term statistical CSI. Specifically, we first estimate the overall channel matrix based on the linear minimum mean square error (LMMSE) estimator, and evaluate the performance of mean square error (MSE) and normalized MSE (NMSE). Then, with the estimated channel, we derive the closed-form expressions of the ergodic rate. The derived expressions show that with Rician RIS-related channels, the rate can maintain at a non-zero value when the transmit power is scaled down proportionally to 1 /M or 1 /N2, where M and N are the number of antennas and reflecting elements, respectively. However, if all the RIS-related channels are purely Rayleigh, the transmit power of each user can only be scaled down proportionally to 1√sqrt M or 1/N. Finally, numerical results verify the promising benefits from the RIS to traditional MISO systems.
KW - channel estimation
KW - Intelligent reflecting surface (IRS)
KW - Reconfigurable Intelligent Surface (RIS)
KW - Rician fading
KW - statistical CSI
UR - http://www.scopus.com/inward/record.url?scp=85113891754&partnerID=8YFLogxK
U2 - 10.1109/SPAWC51858.2021.9593154
DO - 10.1109/SPAWC51858.2021.9593154
M3 - Conference contribution
AN - SCOPUS:85113891754
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
SP - 576
EP - 580
BT - 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 September 2021 through 30 September 2021
ER -