Parallel QR decomposition in LTE-A systems

TL;DR

This paper analyzes various QR decomposition methods for MIMO systems in LTE-A, focusing on their computational complexity, error rate performance, and the benefits of parallel algorithms to reduce latency.

Contribution

It provides a comparative study of QRD algorithms emphasizing their parallelization potential for improved efficiency in LTE-A MIMO systems.

Findings

Parallel QRD algorithms reduce latency significantly.

Certain QRD methods offer better error rate performance.

Parallelization enhances computational efficiency in LTE-A systems.

Abstract

The QR Decomposition (QRD) of communication channel matrices is a fundamental prerequisite to several detection schemes in Multiple-Input Multiple-Output (MIMO) communication systems. Herein, the main feature of the QRD is to transform the non-causal system into a causal system, where consequently efficient detection algorithms based on the Successive Interference Cancellation (SIC) or Sphere Decoder (SD) become possible. Also, QRD can be used as a light but efficient antenna selection scheme. In this paper, we address the study of the QRD methods and compare their efficiency in terms of computational complexity and error rate performance. Moreover, a particular attention is paid to the parallelism of the QRD algorithms since it reduces the latency of the matrix factorization.