I found a contradiction I couldn't resolve by my self. It's about a "Uniform White Noise".
Let ${x}_{t}$ be a "White Noise" i.i.d. Random Process:
$ \forall t \in \mathbb{R}, \ {x}_{t} \sim U[-1, \ 1] $
If we chose to go by the PSD definition of "White Noise" (Constant all over the Frequencies) we get:
$ {R}_{xx}( \tau ) = var({x}_{t}) \delta ( \tau ) $
Yet, Clearly:
$ E[{x}_{t} {x}_{t + \tau}] \underset{ \tau = 0}{=}E[{x}_{t} {x}_{t}]= \frac{1}{3} $
Intuitively, a Process with bounded variance and values can't be "White Noise".
Please mind this is a Continuous Random Process. We don't have such problem in the Discrete case.
What am I missing here? Either there's no such "White Noise" (Why?) or There's a good explanation (Could someone derive it Mathematically) how to get the Delta in The Variance.
Thanks.