论文标题
在采样连续时间AWGN频道
On Sampling Continuous-Time AWGN Channels
论文作者
论文摘要
对于可能反馈的连续时间添加性白色高斯噪声（AWGN）通道，随着采样的无限次数良好，关联离散时间通道的共同信息会收敛到原始连续时通道的相关信息。我们在本文中给出了该结果的更加定量的增强，除其他含义外，它表征了过度采样如何接近具有带宽极限的连续时间高斯通道的真实相互信息。我们的结果中的假设相对温和。特别是，对于非反馈案例，与Shannon-Nyquist采样定理相比，该定理是一种广泛使用的工具，可以将连续的高斯通道连接到其离散时间对应物，而该频率需要通道输入的频带限制，我们的结果只需要在输入功率密度函数上的某些集成性条件。
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.
