Nonlinear communication system simulation via conditional importance sampling

The basic concepts and advantages of the conditional importance sampling (CIS) technique are presented. By conditioning on random sources, this technique simplifies the problem of biasing to lower dimensionalities and, because of its adaptive nature, its biased PDF can be brought closer to the optimum solution. The CIS technique is applied to the simulation of bit error rate in nonlinear digital communication systems. The results obtained from a performance comparison of the CIS with an improved importance sampling technique using a system with two additive white Gaussian noise sources are presented.<<ETX>>

[1]  N.C. Beaulieu.  A composite importance sampling technique for digital communication system simulation , 1990, IEEE Trans. Commun..

[2]  Paul Bratley,et al.  A guide to simulation (2nd ed.) , 1986 .

[3]  Michel C. Jeruchim,et al.  Techniques for Estimating the Bit Error Rate in the Simulation of Digital Communication Systems , 1984, IEEE J. Sel. Areas Commun..

[4]  Linus Schrage,et al.  A guide to simulation , 1983 .

[5]  P. Balaban,et al.  A Modified Monte-Carlo Simulation Technique for the Evaluation of Error Rate in Digital Communication Systems , 1980, IEEE Trans. Commun..

[6]  Bruce R. Davis.  An Improved Importance Sampling Method for Digital Communication System Simulations , 1986, IEEE Trans. Commun..

[7]  Qiang Wang,et al.  On the Application of Importance Sampling to BER Estimation in the Simulation of Digital Communication Systems , 1987, IEEE Trans. Commun..

[8]  Michel C. Jeruchim,et al.  Developments in the Theory and Application of Importance Sampling , 1987, IEEE Trans. Commun..

[9]  Michel C. Jeruchim.  On the Application of Importance Sampling to the Simulation of Digital Satellite and Multihop Links , 1984, IEEE Trans. Commun..

[10]  D. Lu,et al.  Estimation variance bounds of importance sampling simulations in digital communication systems , 1991, IEEE Trans. Commun..

[11]  Michel C. Jeruchim,et al.  An experimental investigation of conventional and efficient importance sampling , 1989, IEEE Trans. Commun..

[12]  Kung Yao,et al.  Improved importance sampling technique for efficient simulation of digital communication systems , 1988, IEEE J. Sel. Areas Commun..

[13]  Michel C. Jeruchim,et al.  On optimum and suboptimum biasing procedures for importance sampling in communication simulation , 1990, IEEE Trans. Commun..

[14]  Behnaam Aazhang,et al.  On the theory of importance sampling applied to the analysis of detection systems , 1989, IEEE Trans. Commun..

[15]  B. Lusignan.  The 'optimum' BER estimator for digital satellite communication systems , 1986 .