Density of Spherically-Embedded Stiefel and Grassmann Codes
Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, and Camilla Hollanti

TL;DR
This paper analyzes the density of codes in complex Stiefel and Grassmann manifolds using geometric approximations, deriving bounds and refining classical coding bounds for high-dimensional spaces.
Contribution
It introduces asymptotic volume approximations and bounds on the density of Stiefel and Grassmann codes, extending coding theory to these manifolds with new geometric insights.
Findings
Density of codes can be approximated using hyperspherical cap models.
Bounds on the kissing radius lead to density bounds as functions of minimum distance.
Stiefel and Grassmann codes have higher density than spherical codes in high dimensions.
Abstract
The density of a code is the fraction of the coding space covered by packing balls centered around the codewords. This paper investigates the density of codes in the complex Stiefel and Grassmann manifolds equipped with the chordal distance. The choice of distance enables the treatment of the manifolds as subspaces of Euclidean hyperspheres. In this geometry, the densest packings are not necessarily equivalent to maximum-minimum-distance codes. Computing a code's density follows from computing: i) the normalized volume of a metric ball and ii) the kissing radius, the radius of the largest balls one can pack around the codewords without overlapping. First, the normalized volume of a metric ball is evaluated by asymptotic approximations. The volume of a small ball can be well-approximated by the volume of a locally-equivalent tangential ball. In order to properly normalize this…
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