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Interference alignment (IA) is a promising technique to efficiently mitigateinterference and to enhance the capacity of a wireless communication network.This paper proposes a grouping-based interference alignment (GIA) withoptimized IA-Cell assignment for the multiple cells interfering multiple-inputand multiple-output (MIMO) multiple access channel (MAC) network under limitedfeedback. This work consists of three main parts: 1) a complete study(including some new improvements) of the GIA with respect to the degrees offreedom (DoF) and optimal linear transceiver design is performed, which allowsfor low-complexity and distributed implementation; 2) based on the GIA, theconcept of IA-Cell assignment is introduced. Three IA-Cell assignmentalgorithms are proposed for the setup with different backhaul overhead andtheir DoF and rate performance is investigated; 3) the performance of theproposed GIA algorithms is studied under limited feedback of IA precoders. Toenable efficient feedback, a dynamic feedback bit allocation (DBA) problem isformulated and solved in closed-form. The practical implementation, therequired backhaul overhead, and the complexity of the proposed algorithms areanalyzed. Numerical results show that our proposed algorithms greatlyoutperform the traditional GIA under both unlimited and limited feedback.

Grouping-based Interference Alignment with IA-Cell Assignment in Multi-Cell MIMO MAC under Limited Feedback