  Inter-operator spectrum sharing in millimeter-wave bands has the potential of
substantially increasing the spectrum utilization and providing a larger
bandwidth to individual user equipment at the expense of increasing
inter-operator interference. Unfortunately, traditional model-based spectrum
sharing schemes make idealistic assumptions about inter-operator coordination
mechanisms in terms of latency and protocol overhead, while being sensitive to
missing channel state information. In this paper, we propose hybrid model-based
and data-driven multi-operator spectrum sharing mechanisms, which incorporate
model-based beamforming and user association complemented by data-driven model
refinements. Our solution has the same computational complexity as a
model-based approach but has the major advantage of having substantially less
signaling overhead. We discuss how limited channel state information and
quantized codebook-based beamforming affect the learning and the spectrum
sharing performance. We show that the proposed hybrid sharing scheme
significantly improves spectrum utilization under realistic assumptions on
inter-operator coordination and channel state information acquisition.
