An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel

TLDR: This paper proposes a linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean squared error (MSE) and extends the algorithm to a general class of utility functions and establishes its convergence.

Abstract: Consider the MIMO interfering broadcast channel whereby multiple base stations in a cellular network simultaneously transmit signals to a group of users in their own cells while causing interference to the users in other cells. The basic problem is to design linear beamformers that can maximize the system throughput. In this paper we propose a linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean squared error (MSE). The proposed algorithm only needs local channel knowledge and converges to a stationary point of the weighted sum-rate maximization problem. Furthermore, we extend the algorithm to a general class of utility functions and establish its convergence. The resulting algorithm can be implemented in a distributed asynchronous manner. The effectiveness of the proposed algorithm is validated by numerical experiments.