Comparative analysis of statistical models for the simulation of Rayleigh faded cellular channels

• Published in: IEEE transactions on communications Vol. 53; no. 6; pp. 1017 - 1026
• Main Authors: Patel, C.S., Stuber, G.L., Pratt, T.G.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.2005; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytical models; Applied sciences; Autocorrelation; Channel models; Channels; Collaborative work; Computer simulation; Convergence; Detection, estimation, filtering, equalization, prediction; Doppler; Doppler effect; Exact sciences and technology; Fading; fading channel simulator; Frequency; Information, signal and communications theory; Mathematical models; Performance assessment; Rayleigh channels; Rayleigh fading; Rayleigh scattering; Signal and communications theory; Signal, noise; Statistical analysis; sum-of-sinusoids (SoS); System testing; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Fading channels; Performance evaluation; Parameter estimation; Rayleigh channels; sum-of-sinusoids (SoS); Time variation; fading channel simulator; Statistical method; Doppler frequency; Simulation; Level crossing rate; Channel estimation; Statistical model; Rayleigh fading; Autocorrelation; Sinusoidal signal; Channel models; Simulator
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2005.849735

Several new "sum-of-sinusoids" models have recently been introduced for the simulation of Rayleigh fading channels. These models are statistical in nature implying that their simulation parameters such as the Doppler frequencies are random. They have been shown to accurately reproduce some of the desired statistical properties of the faded envelope such as the time autocorrelation and the level crossing rate. However, a comparative analysis of these models, hitherto scattered throughout the literature, is not available. This paper compares these models in terms of their complexity and performance. The performance assessment is based upon the variance of the time average statistical properties from their ideal ensemble averages.