A maximum a posteriori MIMO detector using recursive metric computations

Abstract

A complexity reduction technique for soft-output maximum a posteriori probability detection in wireless multiple-input multiple-output (MIMO) channels using rectangular quadrature amplitude modulation (QAM) constellations is derived. In contrast to existing low-complexity detection schemes that reduce the number of candidate tests, we instead focus on lowering the computational burden per candidate. The search over a large number of hypotheses to generate output L-values is facilitated by a doubly recursive mechanism, exploiting differential updates of the distance metrics from candidate to candidate. Moreover, the search over all transmit candidates is simplified using a hierarchical "triangular" (zig-zag) shaped candidate scanning order. The technique is derived conceptually using mathematical terms, and then illustrated by means of a 2 times 2 MIMO system using 64-QAM modulation. Under certain practical assumptions, the new scheme is shown to reduce the overall number of operations per candidate by a factor of about 50-100. While the concept is demonstrated by means of the exhaustive search case, it can be combined with other search-based MIMO detection techniques such as spherical decoding