  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.

Signal Processing