Balancing Egoism and Altruism on MIMO Interference Channel

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 channel state information (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 interferencealignment 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.