Study on Precoding Optimization Algorithms in Massive MIMO System with Multi-Antenna Users

TL;DR

This paper introduces a novel L-BFGS based precoding optimization algorithm for massive MIMO systems with multi-antenna users, demonstrating improved capacity and efficiency over heuristic methods in realistic channel scenarios.

Contribution

It proposes a new L-BFGS optimization scheme for multi-user precoding in massive MIMO, simplifying the problem and enhancing performance compared to existing heuristics.

Findings

Monotonic capacity improvement over heuristics

Reasonable computation time demonstrated in simulations

Significant advantage over standard approaches

Abstract

The paper studies the multi-user precoding problem as a non-convex optimization problem for wireless multiple input and multiple output (MIMO) systems. In our work, we approximate the target Spectral Efficiency function with a novel computationally simpler function. Then, we reduce the precoding problem to an unconstrained optimization task using a special differential projection method and solve it by the Quasi-Newton L-BFGS iterative procedure to achieve gains in capacity. We are testing the proposed approach in several scenarios generated using Quadriga - open-source software for generating realistic radio channel impulse response. Our method shows monotonic improvement over heuristic methods with reasonable computation time. The proposed L-BFGS optimization scheme is novel in this area and shows a significant advantage over the standard approaches. The proposed method has a simple implementation and can be a good reference for other heuristic algorithms in this field.