A Novel Error Classification Simulation Method for Rayleigh Fading Channel

Evaluation of bit error rate (BER) for digital communication system is usually done via simulations using Monte Carlo (MC) method. For low BER, MC method requires huge sample sizes to achieve certain efficiency. To overcome this limitation, many variance reduction techniques such as importance sampling (IS) have been proposed. In this paper, we put forward a novel simulation method - Monte Carlo simulation with error classification (EC-MC). This method can reduce the estimation variance through dividing the total errors into many sub-categories and optimizing the simulation samples for each sub-category. We apply this method in simulations of single-path Rayleigh fading channel. The simulation results demonstrate EC-MC method can achieve the same accuracy at smaller sample sizes and shorter simulation runtime, comparing with both conventional MC and IS methods, especially at high signal to noise ratios.