Square-Root Generalized Eigenvalue Decomposition Processor for Leakage-Based Multi-User MIMO Precoding With Multi-Antenna Users

Multi-user multiple-input and multiple-output (MU-MIMO) precoding is an effective transmission scheme for achieving very high spectral efficiency in modern wireless communication systems. Although numerous multi-user precoder designs have been proposed over the last few decades, the signal-to-leakag...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on circuits and systems. I, Regular papers Jg. 66; H. 6; S. 2382 - 2393
Hauptverfasser: Lee, Ling, Chen, Chun-An, Chen, Chiao-En, Huang, Yuan-Hao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
ISSN:1549-8328, 1558-0806
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Multi-user multiple-input and multiple-output (MU-MIMO) precoding is an effective transmission scheme for achieving very high spectral efficiency in modern wireless communication systems. Although numerous multi-user precoder designs have been proposed over the last few decades, the signal-to-leakage-and-noise ratio (SLNR)-based precoder is known to achieve favorable performance-complexity tradeoffs. This paper presents a new generalized eigenvalue decomposition (GEVD) processor, that is, the core processing unit dominating the overall complexity in SLNR-based precoders. A low-complexity square-root algorithm is adopted to eliminate the need for matrix multiplications and matrix inversion computations, which reduces the complexity of the GEVD processor considerably. Finally, the proposed processor was designed and implemented by using a 40-nm complementary metal-oxide-semiconductor technology, which exhibited a maximum throughput rate of 1.1-M matrices/s for the MU-MIMO system.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1549-8328
1558-0806
DOI:10.1109/TCSI.2019.2893274