  The evolvement of wireless communication services concurs with significant
growth in data traffic, thereby inflicting stringent requirements on
terrestrial networks. This work invigorates a novel connectivity solution that
integrates aerial and terrestrial communications with a cloud-enabled
high-altitude platform station (HAPS) to promote an equitable connectivity
landscape. Consider a cloud-enabled HAPS connected to both terrestrial
base-stations and hot-air balloons via a data-sharing fronthauling strategy.
The paper then assumes that both the terrestrial base-stations and the hot-air
balloons are grouped into disjoint clusters to serve the aerial and terrestrial
users in a coordinated fashion. The work then focuses on finding the
user-to-transmitter scheduling and the associated beamforming policies in the
downlink direction of cloud-enabled HAPS systems by maximizing two different
objectives, namely, the sum-rate and sum-of-log of the long-term average rate,
both subject to limited transmit power and finite fronthaul capacity. The paper
proposes solving the two non-convex discrete and continuous optimization
problems using numerical iterative optimization algorithms. The proposed
algorithms rely on well-chosen convexification and approximation steps, namely,
fractional programming and sparse beamforming via re-weighted $\ell_0$-norm
approximation. The numerical results outline the yielded gain illustrated
through equitable access service in crowded and unserved areas, and showcase
the numerical benefits stemming from the proposed cloud-enabled HAPS
coordination of hot-air balloons and terrestrial base-stations for
democratizing connectivity and empowering the digital inclusion framework.
