A key factor determining the performance of an AMC scheme is the method used at the receiver to estimate the channel condition and thereby deciding for the appropriate MCS to be used in the next frame. The effect of channel estimation errors is first addressed in [6].
In [10], the proposed scheme uses pilot symbols to estimate channel state at the receiver, and utilizes both an interpolation filter and a linear prediction filter to interpolate and predict channel conditions, respectively.
In [11],the design of adaptive trellis-coded modulation schemes using only a single outdated channel estimation is discussed.
In most works, the decision of whichMCS to use for the next frame is based on the basic idea of partitioning the estimated channel Signal-to-Noise Ratio (SNR) into regions using a set of
“thresholds”. Each such region is associated with a particular MCS while the “threshold” values are optimized to maximize the overall throughput. In this paper, we propose a new method for selecting MCS with the objective of maximizing the statistical
average of the channel throughput when there may exist an error in predicting the channel SNR. A simplified model with fewer parameters is also proposed, which accounts for the
changes in the fading characteristics by updating the model parameters in an adaptive manner. Numerical results show that our method outperforms the conventional “threshold” method.