Repulsive Clustering Based Pilot Assignment for Cell-Free Massive MIMO Systems

TL;DR

This paper introduces a repulsive clustering-based pilot assignment method for cell-free massive MIMO systems to reduce pilot contamination and improve user uplink rates.

Contribution

It formulates pilot assignment as a diverse clustering problem and proposes a novel repulsive clustering scheme to mitigate pilot contamination in CF mMIMO.

Findings

Proposed method outperforms existing techniques in uplink per-user rate.

Efficient clustering scheme reduces pilot contamination effects.

Demonstrates significant performance gains in simulated environments.

Abstract

Thanks to its capability to provide a uniform service rate for the User Equipments (UEs), Cell-free (CF) massive Multiple-Input, Multiple-Output (mMIMO), has recently attracted considerable attention, both in academia and in industry, and so is considered as one of the potential technologies for beyond-5G and 6G. However, the reuse of the same pilot signals by multiple users can create the so-called pilot contamination problem, which can hinder the CF mMIMO from unlocking its full performance. In this paper, we address the challenge by formulating the pilot assignment as a maximally diverse clustering problem and propose an efficient yet straightforward repulsive clustering-based pilot assignment scheme to mitigate the effects of pilot contamination on CF mMIMO. The numerical results show the superiority of the proposed technique compared to some other methods with respect to the achieved uplink per-user rate.