Waterfilling Theorems for Linear Time-Varying Channels and Related Nonstationary Sources

Abstract

The capacity of the linear time-varying (LTV) channel, a continuous-time LTV filter with additive white Gaussian noise, is characterized by waterfilling in the time-frequency plane. Similarly, the rate distortion function for a related nonstationary source is characterized by reverse waterfilling in the time-frequency plane. Constraints on the average energy or on the squared-error distortion, respectively, are used. The source is formed by the white Gaussian noise response of the same LTV filter as before. The proofs of both waterfilling theorems rely on a Szegő theorem for a class of operators associated with the filter. A self-contained proof of the Szegő theorem is given. The waterfilling theorems compare well with the classical results of Gallager and Berger. In the case of a nonstationary source, it is observed that the part of the classical power spectral density is taken by the Wigner-Ville spectrum. The present approach is based on the spread Weyl symbol of the LTV filter, and is asymptotic in nature. For the spreading factor, a lower bound is suggested by means of an uncertainty inequality. Index Terms-Channel capacity, linear time-varying (LTV) channel, nonstationary source, rate distortion function, Szego theorem, time-frequency transfer function, uncertainty. R 2σ P (τ, ν)e −iτ ν/2 f (t − τ )e itν dτ dν

Rate Distortion Function of Gaussian Asymptotically WSS Vector Processes

“…The present paper focuses on the derivation of a closed-form expression for the rate distortion function (RDF) of a wide class of vector processes. As stated in [ 1 , 2 ], there exist very few journal papers in the literature that present closed-form expressions for the RDF of non-stationary processes, and just one of them deals with non-stationary vector processes [ 3 ]. In the present paper, we obtain an integral formula for the RDF of any real Gaussian asymptotically wide sense stationary (AWSS) vector process.…”

Capacity and Normalized Optimal Detection Error in Gaussian Channels

“…The goal of the present paper is to extend this C-NODE relationship 1) to more general vector Gaussian channels, 2) to continuous-time Gaussian channels in the form of the linear time-varying (LTV) channels considered in [6], and 3) to compare the C-NODE relationship with the I-MMSE relationship in either case.…”