  This paper investigates the information rate loss in analog channels when the
sampler is designed to operate independent of the instantaneous channel
occupancy. Specifically, a multiband linear time-invariant Gaussian channel
under universal sub-Nyquist sampling is considered. The entire channel
bandwidth is divided into $n$ subbands of equal bandwidth. At each time only
$k$ constant-gain subbands are active, where the instantaneous subband
occupancy is not known at the receiver and the sampler. We study the
information loss through a capacity loss metric, that is, the capacity gap
caused by the lack of instantaneous subband occupancy information. We
characterize the minimax capacity loss for the entire sub-Nyquist rate regime,
provided that the number $n$ of subbands and the SNR are both large. The
minimax limits depend almost solely on the band sparsity factor and the
undersampling factor, modulo some residual terms that vanish as $n$ and SNR
grow. Our results highlight the power of randomized sampling methods (i.e. the
samplers that consist of random periodic modulation and low-pass filters),
which are able to approach the minimax capacity loss with exponentially high
probability.
