A Parallel Algorithm for Energy Efficiency Maximization in Massive MIMO Networks

In this paper, we propose a novel iterative algorithm based on successive convex approximation for the nonconvex energy efficiency optimization problem in massive MIMO networks. The stationary points of the original problem are found by solving a sequence of successively refined approximate problems, and the proposed algorithm has the following advantages: 1) fast convergence as the structure of the original energy efficiency function is preserved as much as possible in the approximate problem, and 2) easy implementation as each approximate problem is natural for parallel computation and all variable updates have a closed-form expression. The proposed algorithm is guaranteed to converge and its advantages are also illustrated numerically.