  Data traffic over wireless communication networks has experienced a
tremendous growth in the last decade, and it is predicted to exponentially
increase in the next decades. Enabling future wireless networks to fulfill this
expectation is a challenging task both due to the scarcity of radio resources
(e.g. spectrum and energy), and also the inherent characteristics of the
wireless transmission medium. Wireless transmission is in general subject to
two phenomena: fading and interference. The elegant interference alignment
concept reveals that with proper transmission signalling design, different
interference signals can in fact be aligned together, such that more radio
resources can be assigned to the desired transmission. Although interference
alignment can achieve a larger data rate compared to orthogonal transmission
strategies, several challenges should be addressed to enable the deployment of
this technique in future wireless networks For instance, to perform
interference alignment, normally, global channel state information (CSI) is
required to be perfectly known at all terminals. Clearly, acquiring such
channel knowledge is a challenging problem in practice and proper channel
training and channel state feedback techniques need to be deployed. In
addition, since the channels are time-varying proper adaptive transmission is
needed. This chapter review recent advances in practical aspects of
interference alignment. It also presents recent test-bed implementations of
signal processing algorithms for the realization of interference alignment.
