A Measure Preserving Mapping for Structured Grassmannian Constellations in SIMO Channels.

In this paper, we propose a new structured Grassmannian constellation for noncoherent communications over single-input multiple-output (SIMO) Rayleigh block-fading channels. The constellation, which we call Grass-Lattice, is based on a measure preserving mapping from the unit hypercube to the Grassmannian of lines. The constellation structure allows for onthe-fly symbol generation, low-complexity decoding, and simple bit-to-symbol Gray coding. Simulation results show that GrassLattice has symbol error rate performance close to that of a numerically optimized unstructured constellation, and is more power efficient than other structured constellations proposed in the literature.