Estimation-Induced Outage Capacity of Ricean Channels

Classically, communication systems are designed assuming perfect channel state information at least at the receiver. However, in most practical situations, only an estimate of the channel is available that differs from the true channel. In this paper, we address this channel uncertainty scenario by introducing the notion of estimation-induced outage capacity. The maximum achievable outage rate for prescribed outage probability is analytically derived from a coding theorem. We provide numerical results for the case of Ricean fading channels 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, etc.) on the outage capacity. We furthermore compare our results with the capacity of a system where the receiver uses a mismatched ML decoder