Minimum-energy band-limited predictor with dynamic subspace selection for time-variant flat-fading channels (2007)
| Citations: | 15 - 11 self |
BibTeX
@MISC{Zemen07minimum-energyband-limited,
author = {Thomas Zemen and Christoph F. Mecklenbräuker and Florian Kaltenberger and Bernard H. Fleury},
title = {Minimum-energy band-limited predictor with dynamic subspace selection for time-variant flat-fading channels},
year = {2007}
}
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Abstract
In this paper, we develop and analyze the basic methodology for minimum-energy (ME) band-limited prediction of sampled time-variant flat-fading channels. This predictor is based on a subspace spanned by time-concentrated and bandlimited sequences. The time-concentration of these sequences is matched to the length of the observation interval and the bandlimitation is determined by the support of the Doppler power spectral density of the fading process. Slepian showed that discrete prolate spheroidal (DPS) sequences can be used to calculate the ME band-limited continuation of a finite sequence. We utilize this property to perform channel prediction. We generalize the concept of time-concentrated and band-limited sequences to a band-limiting region consisting of disjoint intervals. For a fading process with constant spectrum over its possibly discontiguous support we prove that the ME band-limited predictor is identical to a reduced-rank maximum-likelihood predictor which is a close approximation of a Wiener predictor. In current cellular communication systems the time-selective fading process is highly oversampled. The essential dimension of the subspace spanned by time-concentrated and band-limited sequences is in the order of two to five only. The prediction error mainly depends on the support of the Doppler spectrum. We exploit this fact to propose low-complexity time-variant flat-fading channel predictors using dynamically selected predefined subspaces. The subspace selection is based on a probabilistic bound on the reconstruction error. We compare the performance of the ME band-limited predictor with a predictor based on complex exponentials. For a prediction horizon of one eights of a wavelength the numerical simulation
Keyphrases
minimum-energy band-limited predictor time-variant flat-fading channel dynamic subspace selection band-limited sequence band-limited predictor fading process doppler power spectral density band-limited continuation band-limited prediction channel prediction reduced-rank maximum-likelihood predictor subspace selection close approximation probabilistic bound disjoint interval finite sequence essential dimension basic methodology low-complexity time-variant flat-fading channel predictor sampled time-variant flat-fading channel numerical simulation constant spectrum predefined subspace complex exponential doppler spectrum observation interval reconstruction error bandlimited sequence prediction horizon prediction error time-selective fading process wiener predictor discontiguous support band-limiting region consisting discrete prolate spheroidal current cellular communication system
