Abstract—We propose a numerical method for finding packings of MIMO semi-unitary precoding matrices in Grassmannian manifolds with different metrics. The proposed expansion– compression algorithm (ECA) is practical, simple and produces efficient packings without the need for a sophisticated initialization. With chordal distance metric, the algorithm tends to converge into a degenerated point constellation, where two points contain identical as well as orthogonal columns and distance between them cannot increase further along geodesic. Therefore, we alternate between max-min and min-max clustering parts of ECA algorithm, where the latter prevents degenerated constellations. With Fubini-Study distance metric, the algorithm converges to best known packings without extra min-max processing. I
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.