Additive noise

An interference added to the signal during its transmission over a communication channel. More precisely, one says that a given communication channel is a channel with additive noise if the transition function $ Q(y, \cdot ) $ of the channel is given by a density $ q(y, \widetilde{y} ) $, $ y \in {\mathcal Y} $, $ \widetilde{y} \in \widetilde {\mathcal Y} = {\mathcal Y} $( $ {\mathcal Y} $ and $ \widetilde {\mathcal Y} $ are the spaces of the values of the signals at the input and output of the channel, respectively) depending only on the difference $ \widetilde{y} - y $, i.e. $ q(y, \widetilde{y} ) = q( \widetilde{y} -y) $. In this case the signal $ \widetilde \eta $ at the output of the channel can be represented as the sum of the input signal $ \eta $ and a random variable $ \zeta $ independent of it, called additive noise, so that $ \widetilde \eta = \eta + \zeta $.

If one considers channels with discrete or continuous time over finite or infinite intervals, the notion of a channel with additive noise is introduced by the relation $ \widetilde \eta (t) = \eta (t) + \zeta (t) $, where $ t $ is in the given interval, $ \eta (t) $, $ \widetilde \eta (t) $ and $ \zeta (t) $ are random processes representing the signals at the input and the output of the channel with additive noise, respectively; moreover, the process $ \zeta (t) $ is independent of $ \eta (t) $. In particular, if $ \zeta (t) $ is a Gaussian random process, then the considered channel is called a Gaussian channel.

#### References[edit]

[1] |  R. Gallager, "Information theory and reliable communication" , McGraw-Hill (1968)

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[2] |  A.A. Kharkevich, "Channels with noise" , Moscow (1965) (In Russian)

#### Comments[edit]

More generally, especially in system and control theory and stochastic analysis, the term additive noise is used for describing the following way noise enters a stochastic differential equation or observation equation: $ d x = f ( x , t ) d t + d w $, $ d y = h ( x , t ) d t + d v $, where $ w $ and $ v $ are Wiener noise processes. The general situation of a stochastic differential equation of the form $ d x = f ( x , t ) d t + g ( x , t ) d w $ is referred to as having multiplicative noise.