Sparse Linear Precoders For Mitigating Nonlinearities In Massive MIMO

Dealing with nonlinear effects of the radio-frequency (RF) chain is a key issue in the realization of very large-scale multi-antenna (MIMO) systems. Achieving the remarkable gains possible with massive MIMO requires that the signal processing algorithms systematically take into account these effects...

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Veröffentlicht in:IEEE Statistical Signal Processing Workshop S. 391 - 395
Hauptverfasser: Mezghani, Amine, Plabst, Daniel, Swindlehurst, Lee A., Fijalkow, Inbar, Nossek, Josef A.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 11.07.2021
Schlagworte:
Complexity theory
Massive MIMO
Peak to average power ratio
Phase shift keying
Precoding
Radio frequency
Signal processing algorithms
ISSN:2693-3551
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Zusammenfassung:Dealing with nonlinear effects of the radio-frequency (RF) chain is a key issue in the realization of very large-scale multi-antenna (MIMO) systems. Achieving the remarkable gains possible with massive MIMO requires that the signal processing algorithms systematically take into account these effects. Here, we present a computationally-efficient linear precoding method satisfying the requirements for low peak-to-average power ratio (PAPR) and low-resolution D/Aconverters (DACs). The method is based on a sparse regularization of the precoding matrix and offers advantages in terms of precoded signal PAPR as well as processing complexity. Through simulation, we find that the method substantially improves conventional linear precoders.
ISSN:2693-3551
DOI:10.1109/SSP49050.2021.9513791