Optimization of Integer-Forcing Precoding for Multi-User MIMO Downlink

TL;DR

This paper introduces a low-complexity optimization method for Integer-Forcing precoding in multi-user MIMO downlink channels, significantly improving sum rate performance over traditional linear precoding.

Contribution

It proposes a novel, efficient optimization approach for IF precoding parameters applicable to any number of users, enhancing performance with manageable complexity.

Findings

Achieves higher sum rate than heuristic parameter choices

Outperforms conventional linear precoding in simulations

Complexity of the method is O(K^3)

Abstract

Integer-forcing (IF) precoding is an alternative to linear precoding for multi-user (MU) multiple-input-multiple-output (MIMO) channels, with the potential to offer superior performance at a similar complexity. In this letter, a low-complexity suboptimal method is proposed to optimize the parameters of an IF scheme for any number of $K$ users. The proposed method involves solving a relaxation of the problem followed by the application of a lattice reduction algorithm and is shown to have an overall complexity of $\mathcal{O}(K^3)$. Simulation results show that the proposed method achieves a higher sum rate than a heuristic choice of parameters and significantly outperforms conventional linear precoding in all simulated scenarios.