  In this paper, we propose a novel adaptive modulation and coding (AMC)
algorithm dedicated to reduce the feedback frequency of the channel state
information (CSI). There have been already plenty of works on AMC so as to
exploit the bandwidth more efficiently with the CSI feedback to the
transmitter. However, in some occasions, frequent CSI feedback is not favorable
in these systems. This work considers finite-state Markov chain (FSMC) based
channel prediction to alleviate the feedback while maximizing the overall
throughput. We derive the close-form of the frame error rate (FER) based on
channel prediction using limited CSI feedback. In addition, instead of
switching settings according to the CSI, we also provide means to combine both
CSI and FER as the switching parameter. Numerical results illustrate that the
average throughput of the proposed algorithm has significant performance
improvement over fixed modulation and coding while the CSI feedback being
largely reduced.
