  The performance of systems where multiple users communicate over wireless
fading links benefits from channel-adaptive allocation of the available
resources. Different from most existing approaches that allocate resources
based on perfect channel state information, this work optimizes channel
scheduling along with per user rate and power loadings over orthogonal fading
channels, when both terminals and scheduler rely on quantized channel state
information. Channel-adaptive policies are designed to optimize an average
transmit-performance criterion subject to average quality of service
requirements. While the resultant optimal policy per fading realization shows
that the individual rate and power loadings can be obtained separately for each
user, the optimal scheduling is slightly more complicated. Specifically, per
fading realization each channel is allocated either to a single (winner) user,
or, to a small group of winner users whose percentage of shared resources is
found by solving a linear program. A single scheduling scheme combining both
alternatives becomes possible by smoothing the original disjoint scheme. The
smooth scheduling is asymptotically optimal and incurs reduced computational
complexity. Different alternatives to obtain the Lagrange multipliers required
to implement the channel-adaptive policies are proposed, including stochastic
iterations that are provably convergent and do not require knowledge of the
channel distribution. The development of the optimal channel-adaptive
allocation is complemented with discussions on the overhead required to
implement the novel policies.
