  This paper considers the so-called MIMO interference channel. This situation
has relevance in applications such as multi-cell coordination in cellular
networks as well as spectrum sharing in cognitive radio networks among others.
We address the design of precoding (i.e. beamforming) vectors at each sender
with the aim of 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 to be instrumental to optimizing the rates in a MISO
interference channel (i.e. where receivers have no interference canceling
capability) . Here we explore these game-theoretic concepts in the more general
context of MIMO channels and using the framework of Bayesian games, allowing us
to derive (semi-)distributed precoding techniques. We draw parallels with
existing work on the MIMO interference channel, including rate-optimizing and
interference-alignement precoding techniques, showing how such techniques may
be improved and re-interpretated through a common prism based on balancing
egoistic and altruistic beamforming.
