On the Monte Carlo simulation of digital communication systems in Gaussian noise

We consider the general problem of the simulation of highly reliable systems operating in the presence of Gaussian noise. Our methodology uses importance sampling which has been shown to be a particularly effective method in the general discipline of rare-event simulation. The methods we propose are optimal in a certain sense, i.e., they are efficient. We also give a new class of simulation distributions that are universally efficient in the sense that they depend only on a single scalar parameter, regardless of the dimensionality of the underlying system or of the error sets to be simulated.