  This paper characterizes the performance of interference alignment (IA)
technique taking into account the dynamic traffic pattern and the
probing/feedback cost. We consider a time-division duplex (TDD) system where
transmitters acquire their channel state information (CSI) by decoding the
pilot sequences sent by the receivers. Since global CSI knowledge is required
for IA, the transmitters have also to exchange their estimated CSIs over a
backhaul of limited capacity (i.e. imperfect case). Under this setting, we
characterize in this paper the stability region of the system under both the
imperfect and perfect (i.e. unlimited backhaul) cases, then we examine the gap
between these two resulting regions. Further, under each case, we provide a
centralized probing algorithm (policy) that achieves the max stability region.
These stability regions and scheduling policies are given for the symmetric
system where all the path loss coefficients are equal to each other, as well as
for the general system. For the symmetric system, we compare the stability
region of IA with the one achieved by a time division multiple access (TDMA)
system where each transmitter applies a simple singular value decomposition
technique (SVD). We then propose a scheduling policy that consists in switching
between these two techniques, leading the system, under some conditions, to
achieve a bigger stability region. Under the general system, the adopted
scheduling policy is of a high computational complexity for moderate number of
pairs, consequently we propose an approximate policy that has a reduced
complexity but that achieves only a fraction of the system stability region. A
characterization of this fraction is provided.
