Power and Beamforming Control with Generalized Nash Game for Energy-Aware mmWave Networks

This paper studies the problem of joint beamforming and power allocation in ad-hoc mmWave networks. Over the shared spectrum, a number of multi-input-multi-output links attempt to minimize their own supply power by adapting individual transmit powers and beamformers in a self-organized manner. With a two-stage framework of decentralized strategy searching, we address a family of distributed optimization problems with non-convex objectives and coupling-strategy dependent quality-of-service constraints. The proposed scheme allows each link to iteratively adapt its power level in a sub-stage of Generalized Nash Equilibrium (GNE) search, and its beamforming filters in a sub-stage of Minimum Mean Square Error (MMSE)-based receiver shaping, respectively. Our convergence analysis of GNE provides the theoretical guarantee for the convergence of the proposed algorithm. Simulation results show that with our proposed scheme, local link state information suffices to obtain a near optimal overall performance without any need for further acquiring the interference channel state information.