Power margin quality measures for correlated random variates derived from the normaldistribution

The lack of a well-defined and meaningful measure of the quality of computer-generated correlated random variates complicates the design and comparison of generation algorithms for communications system simulation applications. This paper presents quantitative quality measures for computer-generated random variates having a multivariate Gaussian distribution or having a distribution that derives from the multivariate Gaussian distribution. These measures are, in particular, useful for digital communication system simulation applications. A theoretical basis for the definition of the measures is given and it is shown that the measures also possess useful intuitive interpretations. Examples of the use of these quality measures are provided.

[1]  Floyd M. Gardner,et al.  Simulation Techniques: Models of Communication Signals and Processes , 1996 .

[2]  William H. Press,et al.  Book-Review - Numerical Recipes in Pascal - the Art of Scientific Computing , 1989 .

[3]  Gordon L. Stuber,et al.  Principles of Mobile Communication , 1996 .

[4]  M. Levin.  Generation of a sampled Gaussian time series having a specified correlation function , 1960, IRE Trans. Inf. Theory.

[5]  Ralph B. D'Agostino,et al.  Goodness-of-Fit-Techniques , 2020 .

[6]  N. Kasdin.  Discrete simulation of colored noise and stochastic processes and 1/fα power law noise generation , 1995, Proc. IEEE.

[7]  A. Afifi,et al.  On Tests for Multivariate Normality , 1973 .

[8]  C. Loo,et al.  Computer models for fading channels with applications to digital transmission , 1991 .

[9]  Charles W. Therrien,et al.  Discrete Random Signals and Statistical Signal Processing , 1992 .

[10]  Kareem E. Baddour,et al.  Autoregressive modeling for fading channel simulation , 2005, IEEE Transactions on Wireless Communications.

[11]  G. Rw.  Decision procedure for indefinite hypergeometric summation , 1978 .

[12]  E. Parzen.  1. Random Variables and Stochastic Processes , 1999 .

[13]  John G. Proakis,et al.  Digital Communications , 1983 .

[14]  Edward J. Wegman,et al.  Statistical Signal Processing , 1985 .

[15]  K. Sam Shanmugan,et al.  Simulation of Communication Systems , 1992 .

[16]  Gregory E. Bottomley,et al.  Jakes fading model revisited , 1993 .

[17]  Norman C. Beaulieu,et al.  The generation of correlated Rayleigh random variates by inverse discrete Fourier transform , 2000, IEEE Trans. Commun..

[18]  Michael Devetsikiotis,et al.  Efficient fractional Gaussian noise generation using the spatial renewal process , 1998, ICC '98. 1998 IEEE International Conference on Communications. Conference Record. Affiliated with SUPERCOMM'98 (Cat. No.98CH36220).

[19]  Matthias Patzold,et al.  A deterministic digital simulation model for Suzuki processes with application to a shadowed Rayleigh land mobile radio channel , 1996 .

[20]  J.I. Smith,et al.  A computer generated multipath fading simulation for mobile radio , 1975, IEEE Transactions on Vehicular Technology.

[21]  W. C. Jakes,et al.  Microwave Mobile Communications , 1974 .

[22]  N. S. Russell,et al.  Evaluation of Multinormal Probabilities Using Fourier Series Expansions , 1985 .

[23]  Peter Adam Hoeher,et al.  A statistical discrete-time model for the WSSUS multipath channel , 1992 .

[24]  Stefan A. Fechtel.  A Novel Approach to Modeling and Efficient Simulation of Frequency-Selective Fading Radio Channels , 1993, IEEE J. Sel. Areas Commun..

[25]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[26]  M. Patzold,et al.  On the statistical properties of deterministic simulation models for mobile fading channels , 1998 .

[27]  G. Rota.  Geometry I and II: M. Berger, Springer-Verlag, 1987, 427 and 405 pp , 1991 .

[28]  A. Duel-Hallen,et al.  On the performance of coherent and noncoherent multiuser detectors for mobile radio CDMA channels , 1996, Proceedings of ICUPC - 5th International Conference on Universal Personal Communications.

[29]  B. Wu,et al.  Maximization of the channel utilization in wireless heterogeneous multi-access networks , 1996, Proceedings of ICUPC - 5th International Conference on Universal Personal Communications.

[30]  Pedro M. Crespo,et al.  Computer simulation of radio channels using a harmonic decomposition technique , 1995 .

[31]  N. C. Beaulieu,et al.  On the generation of correlated Rayleigh random variates by inverse discrete Fourier transform , 1996, Proceedings of ICUPC - 5th International Conference on Universal Personal Communications.

[32]  Xiaojing Huang,et al.  The simulation of independent Rayleigh faders , 2002, IEEE Trans. Commun..

[33]  Irene A. Stegun,et al.  Handbook of Mathematical Functions. , 1966 .

[34]  Norman C. Beaulieu,et al.  On the performance of digital detectors with dependent samples , 1988, IEEE Trans. Commun..

[35]  R. Clarke.  A statistical theory of mobile-radio reception , 1968 .

[36]  Yahong Rosa Zheng,et al.  Improved models for the generation of multiple uncorrelated Rayleigh fading waveforms , 2002, IEEE Communications Letters.