Distributed Weighted Sum-Rate Maximization in Multicell MU-MIMO OFDMA Downlink

TL;DR

This paper introduces a distributed beamforming method for multicell MU-MIMO OFDMA downlink networks that maximizes weighted sum-rate efficiently without requiring inter-BS communication during iterations.

Contribution

It proposes a novel two-stage convex approximation approach based on interference alignment analysis for distributed weighted sum-rate maximization.

Findings

Achieves fast convergence in distributed beamforming optimization.

Reduces communication overhead between base stations during optimization.

Outperforms conventional iterative algorithms in efficiency and practicality.

Abstract

This paper considers distributed linear beamforming in downlink multicell multiuser orthogonal frequency-division multiple access networks. A fast convergent solution maximizing the weighted sum- rate with per base station (BS) transmiting power constraint is formulated. We approximate the non- convex weighted sum-rate maximization (WSRM) problem with a semidefinite relaxed solvable convex form by means of a series of approximation based on interference alignment (IA) analysis. The WSRM optimization is a two-stage optimization process. In the first stage, the IA conditions are satisfied. In the second stage, the convex approximation of the non-convex WSRM is obtained based on the consequences of IA, and high signal-to-interference-plus-noise ratio assumption. Compared to the conventional iterative distributed algorithms where the BSs exchange additional information at each iteration, the BSs of our proposed solution optimize their beamformers locally without reporting additional information during the iterative procedure.