  The emergence of massive ultra-reliable and low latency communications
(mURLLC) as a category of time/reliability-sensitive service over 6G networks
has received considerable research attention, which has presented unprecedented
challenges. As one of the key enablers for 6G, satellite-terrestrial integrated
networks (STIN) have been developed to offer more expansive connectivity and
comprehensive 3D coverage in space-aerial-terrestrial domains for supporting 6G
mission-critical mURLLC applications while fulfilling diverse and rigorous
quality of service (QoS) requirements. In the context of these mURLLC-driven
satellite services, data freshness assumes paramount importance, as outdated
data may engender unpredictable or catastrophic outcomes. To effectively
measure data freshness in satellite-terrestrial integrated communications, age
of information (AoI) has recently surfaced as a new dimension of QoS metric to
support time-sensitive applications. It is crucial to design new analytical
models that ensure stringent and diverse QoS metrics bounded by different key
parameters, including AoI, delay, and reliability, over 6G
satellite-terrestrial integrated networks. However, due to the complicated and
dynamic nature of satellite-terrestrial integrated network environments, the
research on efficiently defining new statistical QoS schemes while taking into
account varying degrees of freedom has still been in their infancy. To remedy
these deficiencies, in this paper we develop statistical QoS provisioning
schemes over 6G satellite-terrestrial integrated networks in the finite
blocklength regime. Particularly, we firstly introduce and review key
technologies for supporting mURLLC. Secondly, we formulate a number of novel
fundamental statistical-QoS metrics in the finite blocklength regime. Finally,
we conduct a set of simulations to evaluate our developed statistical QoS
schemes.
