The MISO interference channel from a game-theoretic perspective: A combination of selfishness and altruism achieves pareto optimality

We study the MISO interference channel from a game-theoretic perspective. Recently, it was shown that the rates at the non-cooperative Nash equilibrium (NE) strategy are poor especially in the medium and high SNR regimes. A reasonable outcome of the cooperative approach, close to the Pareto boundary of the achievable rate region, was shown to be the zero-forcing (ZF) strategy. In this work, we prove that any point on the Pareto boundary can be achieved by a certain linear combination of the NE and ZF strategies. A scalar weight per user chooses between "selfish" (NE) and altruistic (ZF) behavior. Thereby, the difficult beamforming optimization is reduced to a simple weight optimization. Different optimal operating points, e.g. maximum weighted sum-rate, the Nash-bargaining solution, or the Egalitarian solution, can be obtained by a computationally efficient iterative algorithm. The results are characterized by instantaneous achievable rate regions and the corresponding operating points.