Optimum soft decision decoding with channel state information in the presence of fading

The article first presents the formulation for computing the optimum soft decision metrics for decoding of convolutional codes on fading channels and then demonstrate the performance gains achieved in using the optimum soft decision metrics. The optimum soft decision metrics use channel state information to account for signal strength variations due to fading. The formulation for computing the optimum soft decision metrics is given for the general case in which the statistics of the additive noise on the channel is nonstationary. However, the formulation is applied to a more simple case in which the noise is assumed to be stationary. The results indicate that at moderate signal-to-noise ratios, the 2 dB advantage usually claimed for soft decision decoding over hard decision decoding on Gaussian channels is achievable on fading channel, with the rate 3/4 code used, if the channel state information is incorporated in the soft decision metrics.