Multi-User Flexible Coordinated Beamforming using Lattice Reduction for Massive MIMO Systems

TL;DR

This paper introduces a lattice reduction-aided flexible beamforming algorithm for overloaded multi-user massive MIMO systems, overcoming dimensionality constraints and improving performance.

Contribution

It proposes a novel LR-FlexCoBF algorithm combined with user selection to handle arbitrary overloading in MU-Massive-MIMO systems.

Findings

Significant BER improvements achieved.

Enhanced sum-rate performance demonstrated.

Effective in overloaded scenarios.

Abstract

The application of precoding algorithms in multi-user massive multiple-input multiple-output (MU-Massive-MIMO) systems is restricted by the dimensionality constraint that the number of transmit antennas has to be greater than or equal to the total number of receive antennas. In this paper, a lattice reduction (LR)-aided flexible coordinated beamforming (LR-FlexCoBF) algorithm is proposed to overcome the dimensionality constraint in overloaded MU-Massive-MIMO systems. A random user selection scheme is integrated with the proposed LR-FlexCoBF to extend its application to MU-Massive-MIMO systems with arbitary overloading levels. Simulation results show that significant improvements in terms of bit error rate (BER) and sum-rate performances can be achieved by the proposed LR-FlexCoBF precoding algorithm.