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Signalling over a Gaussian channel with feedback and autoregressive noise

Published online by Cambridge University Press:  14 July 2016

J. Wolfowitz
J. Wolfowitz*
Affiliation:
University of Illinois
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Abstract

We study in detail the case of first-order regression, but our results can be extended to the general regression in a straightforward manner. An average energy constraint ((1.2) below) is imposed on each signal. In Section 2 we give an optimal linear signalling scheme (definition and proof in Section 4) for this channel. We conjecture that this scheme is optimal among all signalling schemes. Then the capacity C of the channel is (see Section 5) – log b, where b is the unique positive root (in x) of the equation x2 = (1 + g2(1 + |α|x)2)–1. Here a is the regression coefficient, and g2 is the ratio of the average energy per signal to the variance of the noise. An equivalent expression is C = ½log(1 + g2(1 + |α| b)2).

Keywords

GAUSSIAN CHANNELFEEDBACKENERGY CONSTRAINT FOR EACH SIGNALOPTIMAL LINEAR FUNCTION OF SIGNALSESTIMATIONLINEAR CAPACITYREGRESSIONOPTIMAL LINEAR SIGNALLING SCHEME
Type
Research Papers
Information
Journal of Applied Probability , Volume 12 , Issue 4 , December 1975 , pp. 713 - 723
Copyright
Copyright © Applied Probability Trust 1975 

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References

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