  Meta distribution is a fine-grained unified performance metric that enables
us to evaluate the {reliability and latency} of next generation wireless
networks, in addition to the conventional coverage probability. In this paper,
using stochastic geometry tools, we develop a systematic framework to
characterize the meta distributions of the downlink
signal-to-interference-ratio (SIR)/signal-to-noise-ratio (SNR) and data rate of
a typical device in a cellular network with coexisting sub-6GHz and millimeter
wave (mm-wave) spectrums. Macro base-stations (MBSs) transmit on sub-6GHz
channels (which we term "microwave" channels), whereas small base-stations
(SBSs) communicate with devices on mm-wave channels. The SBSs are connected to
MBSs via a microwave ($\mu$wave) wireless backhaul. The $\mu$wave channels are
interference limited and mm-wave channels are noise limited; therefore, we have
the meta-distribution of SIR and SNR in $\mu$wave and mm-wave channels,
respectively. To model the line-of-sight (LOS) nature of mm-wave channels, we
use Nakagami-m fading model. To derive the meta-distribution of SIR/SNR, we
characterize the conditional success probability (CSP) (or equivalently
reliability) and its $b^{\mathrm{th}}$ moment for a typical device (a) when it
associates to a $\mu$wave MBS for {\em direct} transmission, and (b) when it
associates to a mm-wave SBS for {\em dual-hop} transmission (backhaul and
access transmission). Performance metrics such as the mean and variance of the
local delay (network jitter), mean of the CSP (coverage probability), and
variance of the CSP are derived. Numerical results validate the analytical
results. Insights are extracted related to the reliability, coverage
probability, and latency of the considered network.
