We investigate link-quality metrics (LQMs) based on raw bit-error-rate, effective signal-to-interference-plus-noise ratio, and mutual information (MI) for the purpose of fast link adaptation (LA) in communication systems employing orthogonal frequency-division multiplexing and multiple-input–multipleoutput (MIMO) antenna technology. From these LQMs, the packet error rate (PER) can be estimated and exploited to select the modulation and coding scheme (MCS) among a class of candidate MCSs that achieves the maximum throughput for the
current channel state under a speciﬁed target PER objective. We propose a novel MI-based LQM and compare the PER-estimation accuracy obtained with this LQM with that resulting from using other LQMs bymeans of Comprehensive Monte Carlo simulations. Search methods for the MCS in the class that is most suitable for a given channel state are presented. An algorithm for obtaining a practical upper bound on the throughput of any LA scheme is proposed. The investigated LQMs are applied to the IEEE 802.11n standard with a 2 × 2 MIMO conﬁguration and practical channel estimation. The proposed MI-based LQM yields the highest PER estimation accuracy, and its throughput shows only 1.7 dB signalto-noise-ratio (SNR) loss with respect to the upper bound but up to 9.5 dB SNR gain, compared to the MCS maximizing the throughput for the current noise variance.