Energy efficiency optimization in MIMO interference channels: A successive pseudoconvex approximation approach

TL;DR

This paper introduces a successive pseudoconvex approximation method for optimizing energy efficiency in MIMO interference channels, providing fast, convergent, and easily implementable algorithms suitable for complex multi-cell systems.

Contribution

It develops a novel iterative algorithm based on pseudoconvex approximation for energy efficiency optimization in multi-cell MIMO systems, ensuring global optimality and convergence.

Findings

Fast convergence of the proposed algorithms.

Easy implementation with closed-form solutions.

Guaranteed convergence to stationary points.

Abstract

In this paper, we consider the (global and sum) energy efficiency optimization problem in downlink multi-input multi-output multi-cell systems, where all users suffer from multi-user interference. This is a challenging problem due to several reasons: 1) it is a nonconvex fractional programming problem, 2) the transmission rate functions are characterized by (complex-valued) transmit covariance matrices, and 3) the processing-related power consumption may depend on the transmission rate. We tackle this problem by the successive pseudoconvex approximation approach, and we argue that pseudoconvex optimization plays a fundamental role in designing novel iterative algorithms, not only because every locally optimal point of a pseudoconvex optimization problem is also globally optimal, but also because a descent direction is easily obtained from every optimal point of a pseudoconvex optimization problem. The proposed algorithms have the following advantages: 1) fast convergence as the structure of the original optimization problem is preserved as much as possible in the approximate problem solved in each iteration, 2) easy implementation as each approximate problem is suitable for parallel computation and its solution has a closed-form expression, and 3) guaranteed convergence to a stationary point or a Karush-Kuhn-Tucker point. The advantages of the proposed algorithm are also illustrated numerically.