Title :
The Stochastic Sinusoidal Model for Rayleigh Fading Channel Simulation
Author :
Grolleau, J. ; Labarre, D. ; Grivel, Eric ; Najim, M.
Author_Institution :
Equipe Signal et Image, Bordeaux I Univ., Talence, France
Abstract :
In this paper, we propose a new Rayleigh channel simulator. Modeling the channel by an AR process leads to numerical problems due to the bandlimitation of the theoretical power density spectrum (PSD) of a Rayleigh channel. Therefore, we suggest modeling the channel by a low-pass filtered version of the so-called stochastic sinusoidal process. It consists of sinusoids in quadrature with random magnitudes modeled as AR processes. To estimate the AR parameters of the amplitudes, we take advantage of the asymptotic behavior of the first-kind zero-order Bessel function. We show that unlike an AR channel modeling, this simulator has the advantage of exhibiting the PSD peaks at the maximum Doppler frequency, for any AR process order.
Keywords :
Bessel functions; Rayleigh channels; autoregressive processes; low-pass filters; Rayleigh fading channel simulation; first-kind zero-order Bessel function; low-pass filter; maximum Doppler frequency; power density spectrum; stochastic sinusoidal model; Computational modeling; Fading; Filtering; Frequency; Low pass filters; Parameter estimation; Predictive models; Rayleigh channels; Stochastic processes; White noise; Bessel functions; Rayleigh channels; autoregressive processes;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.366510