Treating Interference as Noise in Cell-Free Massive MIMO Networks

TL;DR

This paper analyzes the conditions under which treating interference as noise (TIN) is optimal in cell-free massive MIMO networks using stochastic geometry, providing analytical expressions and insights for interference management in 6G systems.

Contribution

It introduces a novel analytical framework for TIN in CF mMIMO systems using stochastic geometry with BPP and PPP approximations, deriving the probability of TIN conditions holding.

Findings

Derived closed-form probability expressions for TIN conditions.

Validated analytical results with numerical simulations.

Showed impact of system parameters on TIN feasibility.

Abstract

How to manage the interference introduced by the enormous wireless devices is a crucial issue to address in the prospective sixth-generation (6G) communications. The treating interference as noise (TIN) optimality conditions are commonly used for interference management and thus attract significant interest in existing wireless systems. Cell-free massive multiple-input multiple-output (CF mMIMO) is a promising technology in 6G that exhibits high system throughput and excellent interference management by exploiting a large number of access points (APs) to serve the users collaboratively. In this paper, we take the first step on studying TIN in CF mMIMO systems from a stochastic geometry perspective by investigating the probability that the TIN conditions hold with spatially distributed network nodes. We propose a novel analytical framework for TIN in a CF mMIMO system with both Binomial Point Process (BPP) and Poisson Point Process (PPP) approximations. We derive the probability that the TIN conditions hold in close form using the PPP approximation. Numerical results validate our derived expressions and illustrate the impact of various system parameters on the probability that the TIN conditions hold.