Let $$n(t) = Re\{z(t)e^{j2\pi f_ct}\},\ $$ where $z(t)$ is the low pass equivalent of white noise $n(t)$. We know the autocorrelation of $n(t)$ is $$R_n(\tau) = \frac{N_0}{2} \delta(\tau),\ $$
$\delta(\tau)$ being the Dirac delta function and the PSD is $S_n(f) = N_0/2$.
From Proakis' Digital Communication book, I learned that the autocorrelation of $z(t)$, $R_z(\tau) = N_0\delta(\tau)$, and PSD is naturally, $N_0$.
Now consider $$z(t) = x(t) + jy(t)$$ I also know that $$R_z(\tau) = R_x(\tau) + jR_y(\tau)$$ So what are $R_x(\tau)$ and $R_y(\tau)$? Proakis' book mentions $R_z(\tau) = R_x(\tau) = R_y(\tau)$. But that seems a bit off to me.
Since, $R_z(\tau)$ is real then shouldn't $R_y(\tau)$ be zero being as it is the imaginary term in a real quantity?
Reference: Proakis, Digital Communication, Third edition, Chapter 4: Characterization of communication signals and systems, section 4-1-4, Representation of Bandpass Stationary Stochastic Processes.