  Real-time video demands quality-of-service (QoS) guarantees such as delay
bounds for end-user satisfaction. Furthermore, the tolerable delay varies
depending on the use case such as live streaming or two-way video conferencing.
Due to the inherently stochastic nature of wireless fading channels,
deterministic delay bounds are difficult to guarantee. Instead, we propose
providing statistical delay guarantees using the concept of effective capacity.
We consider a multiuser setup whereby different users have (possibly different)
delay QoS constraints. We derive the resource allocation policy that maximizes
the sum video quality and applies to any quality metric with concave
rate-quality mapping. We show that the optimal operating point per user is such
that the rate-distortion slope is the inverse of the supported video source
rate per unit bandwidth, a key metric we refer to as the source spectral
efficiency. We also solve the alternative problem of fairness-based resource
allocation whereby the objective is to maximize the minimum video quality
across users. Finally, we derive user admission and scheduling policies that
enable selecting a maximal user subset such that all selected users can meet
their statistical delay requirement. Results show that video users with
differentiated QoS requirements can achieve similar video quality with vastly
different resource requirements. Thus, QoS-aware scheduling and resource
allocation enable supporting significantly more users under the same resource
constraints.
