Cooperative beamforming for the MISO interference channel

Abstract

A distributed beamforming algorithm is proposed for the two-user multiple-input single-output (MISO) interference channel (IFC). The algorithm is iterative and uses as bargaining value the interference that each transmitter generates towards the receiver of the other user. It enables cooperation among the transmitters in order to increase both users' rates by lowering the overall interference. In every iteration, as long as both rates keep on increasing, the transmitters mutually decrease the generated interference. They choose their beamforming vectors distributively, solving the constrained optimization problem of maximizing the useful signal power for a given level of generated interference. The algorithm is equally applicable when the transmitters have either instantaneous or statistical channel state information (CSI). The difference is that the core optimization problem is solved in closed-form for instantaneous CSI, whereas for statistical CSI an efficient solution is found numerically via semidefinite programming. The outcome of the proposed algorithm is approximately Pareto-optimal. Extensive numerical illustrations are provided, comparing the proposed solution to the Nash equilibrium, zero-forcing, Nash bargaining, and maximum sum-rate operating points.