Capacity of Gaussian Noise Channels with Side Information and Feedback PDF Download
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Author: Thierry Etienne Klein
Publisher:
ISBN:
Category :
Languages : en
Pages : 306
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Book Description
Author: Thierry Etienne Klein
Publisher:
ISBN:
Category :
Languages : en
Pages : 306
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
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Book Description
Continuous time communication channels with additive noise are considered under an average power constraint. The noises are assumed to be Gaussian processes equivalent (or mutually absolutely continuous) to a Brownian motion. We study the problem whether the capacity of the channel is increased by feedback or not. It is given a sufficient condition under which the capacity is not increased by feedback. It is also given an example of a channel whose capacity is doubled by feedback.
Author: Charles R. Baker
Publisher:
ISBN:
Category :
Languages : en
Pages : 25
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Book Description
Sufficient conditions are given for optimal causal feedback to increase information capacity for the discrete-time additive Gaussian channel. The conditions are obtained by assuming linear feedback and reformulating the problem into an equivalent no feedback problem. Keywords: Channel capacity; Shannon theory; Information theory; Channels with feedback; Gaussian channels.
Author: Thomas W. Eddy
Publisher:
ISBN:
Category :
Languages : en
Pages : 11
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Book Description
In this paper the capacity of a non-bandlimited additive gaussian colored noise channel with noiseless feedback is derived. It is proved constructively that the capacity for such a channel is given as Cfb = Pavg/2 min Sn(omega) where Pavg is the average transmitted power and Sn(omega) is the spectral density of the additive noise in the forward channel. With this result it follows that the capacity of the channel with feedback can be larger than the capacity of the corresponding channel without feedback. (Author).
Author: Guy Keshet
Publisher: Now Publishers Inc
ISBN: 1601980485
Category : Computers
Languages : en
Pages : 154
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Book Description
Channel Coding in the Presence of Side Information reviews the concepts and methods of communication systems equipped with side information both from the theoretical and practical points of view. It is a comprehensive review that gives the reader an insightful introduction to one of the most important topics in modern communications systems.
Author: Charles R. Baker
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
Recent results on coding capacity and information capacity for the mismatched Gaussian channel are discussed. Sufficient conditions for causal feedback to increase information capacity are given for the finite-dimensional discrete-time Gaussian channel. Keywords: Gaussian channels; Channel capacity; Shannon theory; Information theory.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
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Book Description
A communications channel model with additive, independent increment, stochastically continuous noise is presented. The information capacity of this channel is obtained for a mean-square constraint imposed on the generalized intensity of the channel encoder. The capacity is derived by exploiting the Levy decomposition of the noise to decompose the channel into a white Gaussian noise channel in parallel with a marked Poisson channel. The information capacity is then obtained using results for these latter channels. In particular, recent results for the Poisson channel with mean-square constrained encoder intensity are exploited. Although only the channel without feedback is explicitly addressed, our results are also seen to be applicable in the presence of delayed causal feedback.
Author: I. W. McKeague
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
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Book Description
We evaluate the information capacity of channels for which the noise process is a Gaussian measure on a quasi-complete locally convex space. The coding capacity is calculated in this setting and for time-continuous Gaussian channels using the information capacity result. The coding capacity of channels with non-Gaussian noise having finite entropy with respect to Gaussian noise of the same covariance is shown not to exceed the coding capacity of the Gaussian channel. The sensitivity of the information capacity to deviations from normality in the noise process is also investigated. (Author).
Author: Lawrence Howard Ozarow
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
Models of the additive white Gaussian noise (AWGN) broadcast channel with feedback are analyzed. A deterministic coding procedure is proposed which allows reliable transmission at all rate points inside the capacity regions of these models. A deterministic coding scheme for the AWGN multiple-access channel with feedback is also evaluated. This scheme achieves rate points beyond those found by Cover and Leung. (Author).
Author: C. R. Baker
Publisher:
ISBN:
Category :
Languages : en
Pages : 15
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Book Description
The capacity of the Gaussian channel without feedback, subject to a generalized energy constraint, is determined in an earlier document, In that work, the constraint is given in terms of the covariance of the channel noise process. However, these are many situation where one may wish to determine capacity subject to a constraint determined by a covariance that is different form that of the channel noise. An example is in jamming or countermeasures situations. Channels where the covariance of the noise is the same as that of the constraint will be called matched channels; otherwise, we say that the channel is mismatched (to the constraint). In this paper, the capacity of the mismatched Gaussian channel is determined for two situations; the finite-dimensional channel, and the infinite-dimensional channel with a dimensionality constraint on the space of transmitted signals. Results on the infinite-dimensional mismatched channel without a dimensionality constraint on the signal are given elsewhere. Various special cases of the mismatched channel have been treated previously. The results for the mismatched channel differ significantly from those for the matched channel. A discussion of these differences follows the proof of the main result.
