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

Prediction-based Adaptation (PRADA) Algorithm for Modulation and Coding