IDENTIFIKASI KANAL LINTASAN JAMAK PADA S (1)
IDENTIFICATION OF MULTIPATH CHANNEL IN SYSTEM COMMUNICATION OF MOBILE RADIO USING RADIAL BASIS
FUNCTION NETWORK
ABSTRACT
The rapid time variation of mobile radio channels is often modeled as a random process with second order moments reflecting vehicle
speed, bandwidth and scattering environment. These statistics typically show that there is a small scale for prediction of channel properties
such as received power or complex taps of impulse response coefficients at least when parameter of channels structures are considered.
This paper proposes a radial basis function network (RBF) approach for modeling Identification of the parameter of multipath channel in
system communication of mobile radio. This identification modeling must to feasibility study it in order that can obtain the best modeling
result which is important to know the characteristic of dynamic channel. Therefore this modeling can do with estimation to make use of
ARMA models. The analysis provides that RBF Network modeling is more predictable for identify and good resolution nonlinearities are
included. The result of learning channel parameter value can do with RBF Network that obtained an optimal value with the error
prediction of 1% in scaling. In this case examination of parameter value as a result of the estimation program for attenuation factor is
1,748 dB/m and the root mean square (rms) delay spread is 11,7 ns in the site room (indoor) at the bandwidth 1600-1800 MHz and relative
power of 20-100 dB.
Keyword: multipath channel
Mobile Radio Communications Systems
Identification system
Neural Networks Radial Basis Function (RBF)
Contributor
:
Dr. Ir. Mauridhi Hery Purnomo, M.Eng
Ir. Endroyono, DEA.
FUNCTION NETWORK
ABSTRACT
The rapid time variation of mobile radio channels is often modeled as a random process with second order moments reflecting vehicle
speed, bandwidth and scattering environment. These statistics typically show that there is a small scale for prediction of channel properties
such as received power or complex taps of impulse response coefficients at least when parameter of channels structures are considered.
This paper proposes a radial basis function network (RBF) approach for modeling Identification of the parameter of multipath channel in
system communication of mobile radio. This identification modeling must to feasibility study it in order that can obtain the best modeling
result which is important to know the characteristic of dynamic channel. Therefore this modeling can do with estimation to make use of
ARMA models. The analysis provides that RBF Network modeling is more predictable for identify and good resolution nonlinearities are
included. The result of learning channel parameter value can do with RBF Network that obtained an optimal value with the error
prediction of 1% in scaling. In this case examination of parameter value as a result of the estimation program for attenuation factor is
1,748 dB/m and the root mean square (rms) delay spread is 11,7 ns in the site room (indoor) at the bandwidth 1600-1800 MHz and relative
power of 20-100 dB.
Keyword: multipath channel
Mobile Radio Communications Systems
Identification system
Neural Networks Radial Basis Function (RBF)
Contributor
:
Dr. Ir. Mauridhi Hery Purnomo, M.Eng
Ir. Endroyono, DEA.