Low-complexity Leakage Minimization Beamforming for Large-scale Multi-user Cell-Free Massive MIMO

TL;DR

This paper introduces a low-complexity beamforming method for cell-free massive MIMO systems that minimizes information leakage, using fractional programming and CCP to achieve high secrecy rates with reduced computational effort.

Contribution

It presents a novel low-complexity beamforming design leveraging fractional programming and CCP for secrecy maximization in large-scale MU CF-mMIMO systems.

Findings

Achieves secrecy rates comparable to state-of-the-art methods.

Significantly reduces computational complexity.

Improves convergence speed in beamforming optimization.

Abstract

We propose a low-complexity beamforming (BF) design for information leakage minimization in multi-user (MU) cell-free massive multiple-input multiple-output (CF-mMIMO) systems. Our approach leverages fractional programming (FP) to reformulate the secrecy rate maximization problem into a tractable difference-of-convex form. To efficiently solve the resulting non-convex problem, we employ the Concave-Convex Procedure (CCP), enabling fast convergence to a local optimum. Simulation results demonstrate that the proposed scheme achieves secrecy rates comparable to state-of-the-art (SotA) methods, while significantly reducing computational complexity and improving convergence speed.