Efficient simulation of space-time block codes and concatenated convolutional codes over quasi-static fading channels

Space-Time Block Coding (STBC) is a very attractive space-time coding scheme that can offer a maximum possible diversity advantage with very simple maximum likelihood decoding at the receiver. To further improve the code performance, a concatenated coding scheme which consists of an outer convolutional code with an inner space-time block code has been proposed. Because of the system complexity, the analysis of that system in terms of bit error rates (BER) has relied upon upper bounds, which are quite loose from the actual simulated performance in some cases. The evaluation of BER of a digital communication system is usually done via simulation using Monte Carlo (MC) method. For low BER, this method requires very large sample size to achieve accurate estimates. In this paper, we will illustrate the use of importance sampling (IS) for efficient simulating this concatenated scheme over quasi-static Rayleigh fading channels. In particular, we show how to bias the probability density function (pdf) of Rayleigh and additive white Gaussian noise (AWGN) processes using the variance scaling and mean translation methods, respectively, in order to maximize the computational efficiency gain. It is demonstrated that the proposed method requires much smaller sample sizes to achieve the same accuracy required by a conventional MC estimator.