Soft Handover Procedures in mmWave Cell-Free Massive MIMO Networks

TL;DR

This paper introduces distributed algorithms for joint pilot assignment and cluster formation in mmWave cell-free massive MIMO networks, effectively managing UE mobility and reducing handover complexity while maintaining spectral efficiency.

Contribution

It proposes novel distributed algorithms for AP-UE association and pilot assignment in dynamic environments, addressing mobility and reducing computational and handover overhead.

Findings

Algorithms significantly lower computational time compared to state-of-the-art.

Reduced average number of pilot changes relative to ultra-dense networks.

Enhanced pilot assignment improves massive access in highly loaded scenarios.

Abstract

This paper considers a mmWave cell-free massive MIMO (multiple-input multiple-output) network composed of a large number of geographically distributed access points (APs) simultaneously serving multiple user equipments (UEs) via coherent joint transmission. We address UE mobility in the downlink (DL) with imperfect channel state information (CSI) and pilot training. Aiming at extending traditional handover concepts to the challenging AP-UE association strategies of cell-free networks, distributed algorithms for joint pilot assignment and cluster formation are proposed in a dynamic environment considering UE mobility. The algorithms provide a systematic procedure for initial access and update of the serving APs and assigned pilot sequence to each UE. The principal goal is to limit the necessary number of AP and pilot changes, while limiting computational complexity. We evaluate the performance, in terms of spectral efficiency (SE), with maximum ratio and regularized zero-forcing precoding. Results show that our proposed distributed algorithms effectively identify the essential AP-UE association refinements with orders-of-magnitude lower computational time compared to the state-of-the-art. It also provides a significantly lower average number of pilot changes compared to an ultra-dense network (UDN). Moreover, we develop an improved pilot assignment procedure that facilitates massive access to the network in highly loaded scenarios.