Reduced-complexity sphere decoding via detection ordering for linear multi-input multi-output channels

Abstract

Sphere decoding is a powerful approach for maximum-likelihood (ML) detection over Gaussian multi-input multi-output (MIMO) linear channels. We propose a new detection ordering approach, which minimizes the corresponding diagonal element of the upper-triangular matrix R over all possible column permutations in each step of the QR decomposition. Compared with the previously proposed V-BLAST ZF-DFE ordering approach, our approach has two major advantages: (1) it is efficiently embedded in the QR decomposition with a small computational overhead, rendering itself suitable for fast-varying channels, while the V-BLAST ZF-DFE ordering is not suitable for fast-varying channels since it incurs large computation overhead; (2) the sphere decoder with our proposed detection ordering achieves 17%-69% and 9%-59% reductions in the number of multiplications and the number of additions, respectively, in comparison to that with the V-BLAST ZF-DFE ordering.