Adaptive M -ary quadrature amplitude modulation \ud (M -QAM) with subset diversity (SSD) is a way to cope with \ud quality of service variations in small and large-scale fading chan- \ud nels. We consider a slow adaptive modulation (SAM) technique \ud that adapts the constellation size to the slow variation of the \ud channel due, for example, to shadowing. SAM technique is more \ud practical than fast adaptive modulation (FAM) techniques, that \ud require adaptation to fast fading variations, even if it has been \ud has been shown to provide substantial increase in throughput \ud with respect to ﬁxed schemes while maintaining an acceptable \ud low bit error outage (BEO). In addition SAM is less complex \ud than FAM and requires a lower feedback rate to the transmitter. \ud Performance of adaptive modulation and SSD techniques are \ud affected by non-ideal channel estimation. Here, we propose an \ud analytical framework to evaluate spectral efﬁciency and BEO for \ud slow adaptive QAM with SSD and imperfect channel knowledge. \ud We propose a utility-based approach to SAM, which accounts \ud for the abovementioned CSI imperfections. Our utility-based \ud approach is relevant to the game-theoretic approach, in which a \ud particular strategy (the transmitted power and the modulation \ud constellation option) is chosen by the decision-making control- \ud unit of the transceiver as a response to the set of possible (however uncertain) channel conditions
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