Distributed vs. Centralized Precoding in Cell-Free Systems: Impact of Realistic Per-AP Power Limits

TL;DR

This paper compares distributed and centralized precoding in cell-free massive MIMO, revealing that practical per-AP power constraints diminish the performance advantage of centralized schemes, favoring distributed approaches.

Contribution

It highlights the impact of realistic per-AP power limits on precoding performance, showing that simple heuristics can make distributed precoding more robust in practical scenarios.

Findings

Centralized precoding's advantage diminishes under per-AP power constraints.

Heuristics like global power scaling and local normalization effectively enforce power limits.

Distributed precoding becomes a robust alternative in realistic power-limited settings.

Abstract

In cell-free massive MIMO, centralized precoding is {theoretically known} to {remarkably} outperform its distributed counterparts, albeit {with} high implementation complexity. However, this letter highlights a practical limitation {often overlooked:} {widely used closed-form} centralized {precoders} are typically derived under a sum-power constraint, which often demands unrealistic power allocation that exceeds hardware capabilities. {When two simple heuristics (global power scaling and local normalization) are applied to enforce the per-AP instantaneous power constraint}, the centralized performance superiority disappears, making distributed precoding {a robust option}.