Level-crossing rate and average duration of fades of deterministic simulation models for Rice fading channels

The concept of Rice's sum of sinusoids is often applied to the design of deterministic simulation models for Rice fading channels. This paper investigates in detail the level-crossing rate (LCR), average duration of fades (ADF), and cumulative distribution function (CDF) of such classes of simulation models. Exact and simple approximative formulas are deduced for these statistical quantities. Several numerical results for the derived expressions are presented by using different procedures for the design of the parameters of the deterministic simulation model. Moreover, comparisons with the corresponding simulation results-obtained by evaluating the deterministic simulation models output data-are also given.

[1]  S. Rice.  Mathematical analysis of random noise , 1944 .

[2]  S. O. Rice,et al.  Statistical properties of a sine wave plus random noise , 1948, Bell Syst. Tech. J..

[3]  S. O. Rice,et al.  Distribution of the duration of fades in radio transmission: Gaussian noise model , 1958 .

[4]  Milton Abramowitz,et al.  Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .

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

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

[7]  H. Omori,et al.  Distribution of burst error lengths in Rayleigh fading radio channels , 1980 .

[8]  H. Omori,et al.  Burst error performance encountered in digital land mobile radio channel , 1981, IEEE Transactions on Vehicular Technology.

[9]  William C. Y. Lee,et al.  Mobile Communications Engineering , 1982 .

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

[11]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[12]  Chun Loo,et al.  A statistical model for a land mobile satellite link , 1985, IEEE Transactions on Vehicular Technology.

[13]  Jean-Paul M. G. Linnartz,et al.  Threshold crossing rate and average non-fade duration in a Rayleigh-fading channel with multiple interferers , 1989 .

[14]  Dariush Divsalar,et al.  Introduction to Trellis-Coded Modulation With Applications , 1991 .

[15]  Joel M. Morris.  Burst error statistics of simulated Viterbi decoded BPSK on fading and scintillating channels , 1992, IEEE Trans. Commun..

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

[17]  Ulrich Killat,et al.  A deterministic model for a shadowed Rayleigh land mobile radio channel , 1994, 5th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Wireless Networks - Catching the Mobile Future..

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

[19]  F. Laue,et al.  On the problems of Monte Carlo method based simulation models for mobile radio channels , 1996, Proceedings of ISSSTA'95 International Symposium on Spread Spectrum Techniques and Applications.

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

[21]  Mitsuo Takeda,et al.  Fade statistics in Nakagami fading environments , 1996, Proceedings of ISSSTA'95 International Symposium on Spread Spectrum Techniques and Applications.

[22]  Matthias Patzold,et al.  Modeling, analysis, and simulation of nonfrequency-selective mobile radio channels with asymmetrical Doppler power spectral density shapes , 1997 .

[23]  Matthias Patzold,et al.  A study of a land mobile satellite channel model with asymmetrical Doppler power spectrum and lognormally distributed line-of-sight component , 1998 .

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

[25]  Matthias Patzold,et al.  An extended Suzuki model for land mobile satellite channels and its statistical properties , 1998 .

[26]  Maria Huhtala,et al.  Random Variables and Stochastic Processes , 2021, Matrix and Tensor Decompositions in Signal Processing.