  Stochastic orders are binary relations defined on probability distributions
which capture intuitive notions like being larger or being more variable. This
paper introduces stochastic ordering of instantaneous SNRs of fading channels
as a tool to compare the performance of communication systems over different
channels. Stochastic orders unify existing performance metrics such as ergodic
capacity, and metrics based on error rate functions for commonly used
modulation schemes through their relation with convex, and completely monotonic
(c.m.) functions. Toward this goal, performance metrics such as instantaneous
error rates of M-QAM and M-PSK modulations are shown to be c.m. functions of
the instantaneous SNR, while metrics such as the instantaneous capacity are
seen to have a completely monotonic derivative (c.m.d.). It is shown that the
commonly used parametric fading distributions for modeling line of sight (LoS),
exhibit a monotonicity in the LoS parameter with respect to the stochastic
Laplace transform order. Using stochastic orders, average performance of
systems involving multiple random variables are compared over different
channels, even when closed form expressions for such averages are not
tractable. These include diversity combining schemes, relay networks, and
signal detection over fading channels with non-Gaussian additive noise, which
are investigated herein. Simulations are also provided to corroborate our
results.
