Maximizing Signal to Interference Noise Ratio for Massive MIMO: A Stochastic Neurodynamic Approach

Abstract

In this paper, we consider the problem of maximizing the worst user signal to interference noise ratio (SINR) for massive multiple input multiple output (MaMIMO). We reformulate the nonlinear optimization model as a joint chance-constrained geometric program. We propose a neurodynamic approach to solve the obtained problem. Our numerical results indicate that our approach outperforms the state-of-art convex approximations used to solve joint chance-constrained geometric problems.