학술논문

On Sampling Continuous-Time AWGN Channels
Document Type
Periodical
Author
Source
IEEE Transactions on Information Theory IEEE Trans. Inform. Theory Information Theory, IEEE Transactions on. 68(2):782-794 Feb, 2022
Subject
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Random variables
Entropy
Mutual information
AWGN channels
Standards
Probability distribution
Differential equations
Continuous-time additive white Gaussian noise channel
the Shannon-Nyquist sampling theorem
mutual information
the I-MMSE relationship
stochastic differential equation
Language
ISSN
0018-9448
1557-9654
Abstract
For a continuous-time additive white Gaussian noise (AWGN) channel with possible feedback, it has been shown that as sampling gets infinitesimally fine, the mutual information of the associative discrete-time channels converges to that of the original continuous-time channel. We give in this paper more quantitative strengthenings of this result, which, among other implications, characterize how over-sampling approaches the true mutual information of a continuous-time Gaussian channel with bandwidth limit. The assumptions in our results are relatively mild. In particular, for the non-feedback case, compared to the Shannon-Nyquist sampling theorem, a widely used tool to connect continuous-time Gaussian channels to their discrete-time counterparts that requires the band-limitedness of the channel input, our results only require some integrability conditions on the power spectral density function of the input.