  A deep understanding of the queuing performance of wireless networks is
essential for the advancement of future wireless communications. The stochastic
nature of wireless channels in general gives rise to a time varying
transmission rate. In such an environment, interference is increasingly
becoming a key constraint. Obtaining an expressive model for offered service of
such channels has major implications in the design and optimization of future
networks. However, interference channels are not well-understood with respect
to their higher layer performance. The particular difficulty for handling
interference channels arises from the superposition of random fading processes
for the signals of the transmitters involved (i.e., for the signal of interest
and for the signals of the interferers). Starting from the distribution of the
signal-to-interference-plus-noise ratio (SINR), we derive a statistical
characterization of the underlying service process in terms of its Mellin
transform. Then, we adapt a recent stochastic network calculus approach for
fading channels to derive measures of the queuing performance of single- and
multi-hop wireless interference networks. Special cases of our solution include
noise-limited and interference-limited systems. A key finding of our analysis
is that for a given average signal and average sum interference power, the
performance of interfered systems not only depends on the relative strength of
the sum interference with respect to the signal-of-interest power, but also on
the interference structure (i.e., the number of interferers) as well as the
absolute levels.
