  For the multivariate trigonometric polynomials we study convolution with the
corresponding the de la Vallee Poussin kernel from the point of view of
discretization. In other words, we replace the normalized Lebesgue measure by a
discrete measure in such a way, which preserves the convolution properties and
provides sampling discretization of integral norms. We prove that in the
two-variate case the Fibonacci point sets provide an ideal (in the sense of
order) solution. We also show that the Korobov point sets provide a suboptimal
(up to logarithmic factors) solution for an arbitrary number of variables.
