Let $\mu$ be a Borel probability measure on $\mathbb{R}^d$ and and let $(\mu_n : n \in \mathbb{N})$ be a sequence of such measures. Suppose that $\mu_n(f) \to \mu(f)$ for all smooth $f$ of compact support. How can I show that $\mu_n$ converges weakly to $\mu$ on $\mathbb{R}^d$?
I have tried to prove this result by contradiction and directly, however I am unable to make any serious progress on it. I know that if for any continuous bounded $g$ I could find smooth $f_k$ of compact support converging uniformly to $g$ then for any $\varepsilon > 0$ I have $$|\mu(g)-\mu_i(g)| \leq |\mu(g)-\mu(f_k)|+|\mu(f_k)-\mu_i(f_k)|+|\mu_i(f_k)-\mu_i(g)| $$ $$ \leq \varepsilon +|\mu(f_k)-\mu_i(f_k)|+\varepsilon$$ by uniform convergence and the fact that $\mu_i$ are probability measures so we can find some $k$ such that $\|g-f_k\|_\infty \leq \varepsilon$. Then we use the fact that $\mu_i(f_k) \to \mu(f_k)$ to get $|\mu(g)-\mu_i(g)| \leq 3\varepsilon$ for all large enough $i$, giving us weak convergence.
However I don't believe that there exist smooth $f_k$ of compact support converging uniformly to $g$ for this to work (or at least I can't prove it). I know the result is true if we had a compact subset of $\mathbb{R}^d$ by the Stone-Weierstrass theorem but that does not generalise to this case which leaves me stumped as I can't find any other way to attack the problem.
How should I proceed on this question?