  Residual radio resources are abundant in wireless networks due to dynamic
traffic load, which can be exploited to support high throughput for serving
non-real-time (NRT) traffic. In this paper, we investigate how to achieve this
by resource allocation with predicted time-average rate, which can be obtained
from predicted average residual bandwidth after serving real-time traffic and
predicted average channel gains of NRT mobile users. We show the connection
between the statistics of their prediction errors. We formulate an optimization
problem to make a resource allocation plan within a prediction window for NRT
users that randomly initiate requests, which aims to fully use residual
resources with ensured quality of service (QoS). To show the benefit of knowing
the contents to be requested and the request arrival time in advance, we
consider two types of NRT services, video on demand and video on reservation.
The optimal solution is obtained, and an online policy is developed that can
transmit according to the plan after instantaneous channel gains are available.
Simulation and numerical results validate our analysis and show a dramatic gain
of the proposed method in supporting high arrival rate of NRT requests with
given tolerance on QoS.
