The work derives an approximate local secrecy capacity and defines secret local contraction coefficients as largest generalized eigenvalues of channel matrix pencils, obtained via local Euclidean geometry approximations to the wiretap channel optimization problem.
Secure coding for the gaussian wiretap channel with sparse regression codes,
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Local Information-Theoretic Security via Euclidean Geometry
The work derives an approximate local secrecy capacity and defines secret local contraction coefficients as largest generalized eigenvalues of channel matrix pencils, obtained via local Euclidean geometry approximations to the wiretap channel optimization problem.