This paper considers the so-called multiple-inputmultiple-
output interference channel (MIMO-IC) which has relevance
in applications such as multi-cell coordination in cellular
networks as well as spectrum sharing in cognitive radio networks
among others. We consider a beamforming design framework
based on striking a compromise between beamforming gain at
the intended receiver (Egoism) and the mitigation of interference
created towards other receivers (Altruism). Combining egoistic
and altruistic beamforming has been shown previously in several
papers to be instrumental to optimizing the rates in a multipleinput-
single-output interference channel MISO-IC (i.e. where
receivers have no interference canceling capability). Here, by
using the framework of Bayesian games, we shed more light
on these game-theoretic concepts in the more general context
of MIMO channels and more particularly when coordinating
parties only have CSI of channels that they can measure directly.
This allows us to derive distributed beamforming techniques. We
draw parallels with existing work on the MIMO-IC, including
rate-optimizing and interference-alignment precoding techniques,
showing how such techniques may be improved or re-interpreted
through a common prism based on balancing egoistic and altruistic
beamforming. Our analysis and simulations currently limited
to single stream transmission per user attest the improvements
over known interference alignment based methods in terms
of sum rate performance in the case of so-called asymmetric
networks.
