 LPTV system involving up- or downconversion to different frequency bands destroys the stationarity of a noise source. As shown in the upper part of the figure, a "leaky" upconversion mixer transfers input noise to both baseband and the carrier frequency, causing the output noise in these frequency bands to be correlated. If noise components are correlated, simply adding their PSDs, e.g. to model the result of a leaky downconversion, is incorrect as it may lead to underestimating noise strength. This mixer transfers input noise to both baseband and the carrier frequency. Clearly, the noise components in these bands is correlated as they originate from a common source. Hence, the resulting noise signal is no longer stationary. Downconverting this signal using a second leaky mixer results in baseband output noise that combines input noise components coming from both baseband and the carrier fre- quency. As indicated in Fig. 3.21, these components are correlated. Therefore, it is no longer allowed to characterize the output noise PSD by adding the PSDs of its consti- tuting components. Such a procedure may lead to over-optimistic noise analysis in a sense that the output noise strength is underestimated (by neglecting what can be seen as stochastic positive interference). As always, it is not a healthy design practice to underestimate potential trouble. It is therefore important to keep track of the cross- correlations that exist between the noise components in the different (non-overlapping) frequency bands. In summary, the basic problem with stationary noise models lies in the fact that they are unable to capture cross-correlations between the noise components in different frequency bands. As illustrated by the example above, many common LPTV sys- tems bring such cross-correlations about. Moreover, knowing the cross-correlations is important since neglecting them may lead to the underestimation of the output noise strength. Hence, we need a noise model that is able to capture cross-correlations be- 3.5.3 Noise ana