DocumentCode :
1820791
Title :
Introduction of linear cyclostationary filters to model time-variant channels
Author :
Duverdier, Alban ; Lacaze, Bernard ; Roviras, Daniel
Author_Institution :
CNES, Toulouse, France
fYear :
1999
fDate :
1999
Firstpage :
325
Abstract :
In modern telecommunications, the transmission systems are often modelised by linear time-varying filters and linear random filters. We recall the definitions of the linear time-invariant and periodic time-varying filter. The authors generalize then the definition of linear stationary filter into a particular case of the linear random filter, the linear cyclostationary filter. The optimal reconstruction method of a signal submitted to a cyclostationary filter is introduced. It is particularly difficult to apply. Thus, we present a suboptimal reconstruction method. We apply this result to a signal submitted to a particular cyclostationary filter. The signal is in fact filtered successively through a linear periodic time-varying filter and submitted to a stationary jitter. We obtain reconstruction results in the case of a transmission of N.R.Z. signals
Keywords :
filtering theory; jitter; optimisation; random processes; signal reconstruction; time-varying filters; NRZ signals transmission; linear cyclostationary filters; linear periodic time-varying filter; linear random filters; linear stationary filter; linear time-invariant filter; linear time-varying filters; optimal reconstruction method; periodic time-varying filter; reconstruction results; stationary jitter; suboptimal reconstruction method; time-variant channels modeling; transmission systems; Fourier series; Frequency response; Jitter; Land mobile radio; Nonlinear filters; Random processes; Reconstruction algorithms; Scattering; Silicon carbide;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Telecommunications Conference, 1999. GLOBECOM '99
Conference_Location :
Rio de Janeireo
Print_ISBN :
0-7803-5796-5
Type :
conf
DOI :
10.1109/GLOCOM.1999.831658
Filename :
831658
Link To Document :
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