  This paper presents a new Interference Alignment (IA) scheme for K-User
Multiple Input Multiple Output (MIMO) Interference Channel (IC) based on two
metaheuristics, namely Particle Swarm Optimization (PSO) and Artificial Bee
Colony (ABC) Algorithm. Tackling interference is an essential issue in wireless
communications to which Interference Alignment (IA) provides a promising
solution. However, IA still lacks of explicit and straightforward design
procedures. In fact, most of IA procedures aim to minimize a certain
Interference Leakage (IL) which measures the effect of the interference on the
network, this results in complex optimization tasks involving a large amount of
decision variables, together with a problem of convergence of the IA solutions.
In this paper the IA optimization is performed using PSO, ABC and their
cooperative counterparts, more suitable for large scale optimization. A
comparison between the four algorithms is also carried out. The cooperative
proposed approaches seem to be promising.
