Linear Transceiver Optimization in Multicell MIMO Based on the Generalized Benders Decomposition

TL;DR

This paper addresses the complex problem of optimizing linear transceivers in multicell MIMO systems with interference, proposing a reformulation that enables the use of generalized Benders decomposition for improved optimization strategies.

Contribution

It introduces a reformulation of the NP-hard sum rate maximization problem, facilitating the application of generalized Benders decomposition for transceiver design in multicell MIMO systems.

Findings

Decomposition enables local and promising global optimization approaches.

Two optimization strategies are developed, one guaranteeing local convergence.

The methods improve transceiver design in interference-limited MIMO networks.

Abstract

We study the maximum sum rate optimization problem in the multiple-input multiple-output interfering broadcast channel. The multiple-antenna transmitters and receivers are assumed to have perfect channel state information. In this setting, finding the optimal linear transceiver design is an NP-hard problem. We show that a reformulation of the problem renders the application of generalized Benders decomposition suitable. The decomposition provides us with an optimization structure which we exploit to apply two different optimization approaches. While one approach is guaranteed to converge to a local optimum of the original problem, the other approach hinges on techniques which can be promising for devising a global optimization method.