  Interference alignment (IA) is a promising technique to efficiently mitigate
interference and to enhance the capacity of a wireless communication network.
This paper proposes a grouping-based interference alignment (GIA) with
optimized IA-Cell assignment for the multiple cells interfering multiple-input
and multiple-output (MIMO) multiple access channel (MAC) network under limited
feedback. This work consists of three main parts: 1) a complete study
(including some new improvements) of the GIA with respect to the degrees of
freedom (DoF) and optimal linear transceiver design is performed, which allows
for low-complexity and distributed implementation; 2) based on the GIA, the
concept of IA-Cell assignment is introduced. Three IA-Cell assignment
algorithms are proposed for the setup with different backhaul overhead and
their DoF and rate performance is investigated; 3) the performance of the
proposed GIA algorithms is studied under limited feedback of IA precoders. To
enable efficient feedback, a dynamic feedback bit allocation (DBA) problem is
formulated and solved in closed-form. The practical implementation, the
required backhaul overhead, and the complexity of the proposed algorithms are
analyzed. Numerical results show that our proposed algorithms greatly
outperform the traditional GIA under both unlimited and limited feedback.
