Asymptotic Performance Analysis of the Regularized Least Squares Precoding with Restricted Transmit Power in Multi-User Massive MIMO
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-clos...
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| Veröffentlicht in: | 2023 31st European Signal Processing Conference (EUSIPCO) S. 1450 - 1454 |
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04.09.2023
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| ISSN: | 2076-1465 |
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| Abstract | 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 (SINAD lb ) are asymptotically approximated. As a major outcome of our analysis, we establish that there is an average transmit power that asymptotically optimizes the SINAD lb 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. |
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| AbstractList | 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 (SINAD lb ) are asymptotically approximated. As a major outcome of our analysis, we establish that there is an average transmit power that asymptotically optimizes the SINAD lb 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. |
| Author | Alouini, Mohamed-Slim Ma, Xiuxiu Alrashdi, Ayed M. Al-Naffouri, Tareq Y. Ballal, Tarig Kammoun, Abla |
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| Snippet | This paper characterizes the regularized least squares (RLS) precoding scheme in multi-user massive multiple-input multiple-output (MU-mMIMO) communication... |
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| SubjectTerms | asymptotic analysis Bit error rate Communication systems convex Gaussian min-max theorem (CGMT) convex optimization Non-linear precoder Nonlinear distortion Power control Precoding regularized least squares Symbols Transmitting antennas |
| Title | Asymptotic Performance Analysis of the Regularized Least Squares Precoding with Restricted Transmit Power in Multi-User Massive MIMO |
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