A Novel Iterative Control Variates Algorithm for Efficient Simulation in AWGN Channels

In this paper, we propose a fast convergent simulation algorithm for additive white Gaussian noise (AWGN) channel which can obtain the unbiased and effective estimators of bit error rate (BER) and amplitude of the transmitted signal (TSA). It utilizes a certain cumulative distribution function as the control variate. Compared with Monte-Carlo (MC) methods, this algorithm does not require knowing TSA while its estimator of BER has a lower variance. Its estimator of TSA also has a lower variance than traditional methods. The simulation result demonstrates the conclusion, viz. both the variance of BER´s estimator and that of TSA´s estimator present inverse ratio to square of simulation data number