Stochastic Successive Weighted Sum-Rate Maximization For Multiuser Mimo Systems With Finite-Alphabet Inputs

Weighted sum-rate maximization (WSRM) is a fundamental problem for multiuser multiple-input-multiple-output (MU-MIMO) systems with finite-alphabet inputs. However, solving this problem is challenging because of the intractable expectation involved in rate functions. The state-of-art WSRM methods for the case of finite-alphabet inputs suffer from high computational complexity due to the issue of complicated numerical integrals for expectation calculation. Inspired by the stochastic successive upper-bound minimization (SSUM) method [1], this paper proposes a stochastic successive inexact lower-bound maximization (SSILM) algorithm for the WSRM problem with finite-alphabet inputs. Our algorithm significantly differs from SSUM in that we use an inexact lower bound of the objective function which is skillfully devised based on an exact but extremely loose lower bound of the objective function. Simulation results show that the proposed algorithm exhibits much faster convergence than state-of-art algorithms.