TY - GEN
T1 - Asymptotic Performance Analysis of the Regularized Least Squares Precoding with Restricted Transmit Power in Multi-User Massive MIMO
AU - Ma, Xiuxiu
AU - Kammoun, Abla
AU - Alrashdi, Ayed M.
AU - Ballal, Tarig
AU - Alouini, Mohamed Slim
AU - Al-Naffouri, Tareq Y.
N1 - Publisher Copyright:
© 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.
PY - 2023
Y1 - 2023
N2 - This paper characterizes the regularized least squares (RLS) precoding scheme in multi-user massive multiple-input multiple-output (MU-mMIMO) communication systems. To allow for the use of cheap power amplifiers (PAs) with very limited dynamic ranges, the studied precoder is formulated as a non-closed form solution of a convex problem in which the power at each antenna is constrained below a predefined maximum power. By leveraging the convex Gaussian min-max theorem (CGMT), we characterize the statistics of the precoded symbols and the distortion error at each user under the assumption of Gaussian channels. Based on this, the bit error rate (BER) and a tight lower bound of the signal-to-noise and distortion ratio (SINADlb) are asymptotically approximated. As a major outcome of our analysis, we establish that there is an average transmit power that asymptotically optimizes the SINADlb and the BER performance. Such a value can be achieved by properly tuning the power control parameter. Numerical simulations are provided to support the accuracy of our theoretical predictions.
AB - This paper characterizes the regularized least squares (RLS) precoding scheme in multi-user massive multiple-input multiple-output (MU-mMIMO) communication systems. To allow for the use of cheap power amplifiers (PAs) with very limited dynamic ranges, the studied precoder is formulated as a non-closed form solution of a convex problem in which the power at each antenna is constrained below a predefined maximum power. By leveraging the convex Gaussian min-max theorem (CGMT), we characterize the statistics of the precoded symbols and the distortion error at each user under the assumption of Gaussian channels. Based on this, the bit error rate (BER) and a tight lower bound of the signal-to-noise and distortion ratio (SINADlb) are asymptotically approximated. As a major outcome of our analysis, we establish that there is an average transmit power that asymptotically optimizes the SINADlb and the BER performance. Such a value can be achieved by properly tuning the power control parameter. Numerical simulations are provided to support the accuracy of our theoretical predictions.
KW - asymptotic analysis
KW - convex Gaussian min-max theorem (CGMT)
KW - convex optimization
KW - Non-linear precoder
KW - regularized least squares
UR - http://www.scopus.com/inward/record.url?scp=85178365251&partnerID=8YFLogxK
U2 - 10.23919/EUSIPCO58844.2023.10290123
DO - 10.23919/EUSIPCO58844.2023.10290123
M3 - Conference contribution
AN - SCOPUS:85178365251
T3 - European Signal Processing Conference
SP - 1450
EP - 1454
BT - 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings
PB - European Signal Processing Conference, EUSIPCO
T2 - 31st European Signal Processing Conference, EUSIPCO 2023
Y2 - 4 September 2023 through 8 September 2023
ER -