  Classically, communication systems are designed assuming perfect channel
state information at the receiver and/or transmitter. However, in many
practical situations, only an estimate of the channel is available that differs
from the true channel. We address this channel mismatch scenario by using the
notion of estimation-induced outage capacity, for which we provide an
associated coding theorem and its strong converse, assuming a discrete
memoryless channel. We illustrate our ideas via numerical simulations for
transmissions over Ricean fading channels under a quality of service (QoS)
constraint using rate-limited feedback channel and maximum likelihood (ML)
channel estimation. Our results provide intuitive insights on the impact of the
channel estimate and the channel characteristics (SNR, Ricean K-factor,
training sequence length, feedback rate, etc.) on the mean outage capacity.
