Implementation comparisons of the QR decomposition for MIMO detection

Authors:
Gabriel Luca Nazar;Christina Gimmler;Norbert Wehn
Affiliations:
Universidade Federal do Rio Grande do Sul and Technische Universität Kaiserslautern, Porto Alegre and Kaiserslauter, Brazil;Technische Universität Kaiserslautern, Kaiserslautern, Germany;Technische Universität Kaiserslautern, Kaiserslautern, Germany
Venue:
SBCCI '10 Proceedings of the 23rd symposium on Integrated circuits and system design
Year:
2010

Citing 0
Cited 2

A system view on iterative MIMO detection: dynamic sphere detection versus fixed effort list detection

VLSI Design - Special issue on Flexible Radio Design: Trends and Challenges in Digital Baseband Implementation
Implementations of Sorted-QR Decomposition for MIMO Receivers: Complexity, Reusability and Efficiency Analysis

Journal of Signal Processing Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the context of decoding multiple-input multiple-output (MIMO) symbols, many approaches rise as promising, such as successive interference cancellation and sphere decoding. The QR decomposition (QRD) of the channel impulse response matrix is a critical point to ensure good performance of the subsequent decoding steps for both approaches. This paper presents a low-complexity hardware architecture for the basic QRD algorithm, which is extended to two improved versions, namely the sorted QR decomposition (SQRD) and the minimum mean-square error SQRD. The main contribution of this work is a comparison of hardware implementations of the three variants and an analysis of their impact on a MIMO-BICM system regarding system communications performance and computational complexity.