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Failure-Aware Access Point Selection for Resilient Cell-Free Massive MIMO Networks

Mostafa Rahmani Ghourtani, Junbo Zhao, Yi Chu, Hamed Ahmadi, David Grace, Alister G. Burr

TL;DR

The paper addresses resilience in CF-mMIMO by introducing Failure-Aware AP Selection (FAAS), which selects per-user APs based on both channel strength and AP failure probabilities, controlled by a tunable stress parameter $α$. FAAS integrates reliability into the user–AP association, maintaining a minimum cluster size to prevent single-point outages and providing a tractable analytical framework for failure impact. Through simulations, FAAS demonstrates improved minimum-user SE and significantly reduced outage compared to failure-agnostic clustering, especially under high failure stress and dense single-antenna deployments. The work highlights the practical value of incorporating hardware resilience into CF-mMIMO design and points to future exploration in disaggregated architectures and distributional performance guarantees.

Abstract

This paper presents a Failure-Aware Access Point Selection (FAAS) method aimed at improving hardware resilience in cell-free massive MIMO (CF-mMIMO) networks. FAAS selects APs for each user by jointly considering channel strength and the failure probability of each AP. A tunable parameter \(α\in [0,1]\) scales these failure probabilities to model different levels of network stress. We evaluate resilience using two key metrics: the minimum-user spectral efficiency, which captures worst-case user performance, and the outage probability, defined as the fraction of users left without any active APs. Simulation results show that FAAS maintains significantly better performance under failure conditions compared to failure-agnostic clustering. At high failure levels, FAAS reduces outage by over 85\% and improves worst-case user rates. These results confirm that FAAS is a practical and efficient solution for building more reliable CF-mMIMO networks.

Failure-Aware Access Point Selection for Resilient Cell-Free Massive MIMO Networks

TL;DR

The paper addresses resilience in CF-mMIMO by introducing Failure-Aware AP Selection (FAAS), which selects per-user APs based on both channel strength and AP failure probabilities, controlled by a tunable stress parameter . FAAS integrates reliability into the user–AP association, maintaining a minimum cluster size to prevent single-point outages and providing a tractable analytical framework for failure impact. Through simulations, FAAS demonstrates improved minimum-user SE and significantly reduced outage compared to failure-agnostic clustering, especially under high failure stress and dense single-antenna deployments. The work highlights the practical value of incorporating hardware resilience into CF-mMIMO design and points to future exploration in disaggregated architectures and distributional performance guarantees.

Abstract

This paper presents a Failure-Aware Access Point Selection (FAAS) method aimed at improving hardware resilience in cell-free massive MIMO (CF-mMIMO) networks. FAAS selects APs for each user by jointly considering channel strength and the failure probability of each AP. A tunable parameter scales these failure probabilities to model different levels of network stress. We evaluate resilience using two key metrics: the minimum-user spectral efficiency, which captures worst-case user performance, and the outage probability, defined as the fraction of users left without any active APs. Simulation results show that FAAS maintains significantly better performance under failure conditions compared to failure-agnostic clustering. At high failure levels, FAAS reduces outage by over 85\% and improves worst-case user rates. These results confirm that FAAS is a practical and efficient solution for building more reliable CF-mMIMO networks.
Paper Structure (12 sections, 13 equations, 3 figures)

This paper contains 12 sections, 13 equations, 3 figures.

Table of Contents

  1. Introduction
  2. Problem Statement
  3. System Model
  4. Pilot Transmission and Channel Estimation
  5. Uplink Data Transmission
  6. User-centric Network with Dynamic Cooperative Cluster
  7. Failure-Aware Access Point Selection
  8. FAAS Algorithm with Stress-Level Parameter
  9. Analytical Modeling of Failure Impact
  10. Resilience Metric
  11. Numerical Analysis
  12. Conclusion

Figures (3)

  • Figure 1: Failure-aware AP selection framework: each AP is associated with a failure probability $p_m^f$ and CPU selects APs based on both channel strength and failure probability.
  • Figure 2: CDF of uplink minimum user rate for cell-free massive MIMO with MMSE combining and considering failure probability for APs, as previously mentioned $\alpha = 0$ corresponds to a failure-free network, and $\alpha = 1$ reflects maximum stress.
  • Figure 3: Impact of failure intensity $\alpha$ on mean spectral efficiency and user outage probability for CF-mMIMO with MMSE combining under different AP selection strategies. Note: The outage curve for "All available APs" is omitted as it remains zero for all $\alpha$; with a logarithmic scale, it is not visible.