I don't know if the title is accurate, but I have this problem:
I have iid RVs $Y_k$ that has a value from {0,1,...,9} with equal probability. I need to show that $$ X_n = \sum_{k=1}^{n}Y_k10^{-k} $$ converges to a uniform distribution between [0,1], as $n \rightarrow\infty$.
Can anyone help about this? Thanks in advance.
--edit--
I've tried to use characteristic functions. I thought that maybe I could show that $$\Phi_{X_n}(\omega) = \frac{1}{j\omega}(e^{j\omega}-1)=\Phi_Y(\omega) $$ as $n\rightarrow\infty$, which is the characteristic function of a uniform RV.
Since $$ X_n = \frac{Y_1}{10^1}+\frac{Y_2}{10^2}+\frac{Y_3}{10^3}+...+\frac{Y_n}{10^n} $$ I know that pdf of $X_n$ can be found by convolution. Therefore, by multiplicating the characteristic functions of $Y_k$'s.
I calculated $\Phi_{Y_k}(\omega)= E[e^{j\omega\frac{Y_k}{10^k}}]$, which is actually $\Phi_Y(\frac{\omega}{10^k})$.
Finally, I get $$ \Phi_{X_n}(\omega)=\Phi_Y(\frac{\omega}{10})\Phi_Y(\frac{\omega}{10^2})\Phi_Y(\frac{\omega}{10^3})...\Phi_Y(\frac{\omega}{10^n}) $$
But I stuck here...
Do you thinks this is a valid way to go on or a dead end?