SIMULASI IDENTIFIKASI KANAL LINTAS-JAMAK PADA WCDMA SECARA ADAPTIF DENGAN FILTER NLMS DAN LMS

Abstract

This research was solely conducted to observe the adaptive filter ability in identification of multipath channel for Wideband Code Division Multiple Access (WCDMA). The method used was limited to a simulation of mutipath channel identification by adaptive filter, which imitated the characteristics of the channel. LMS (Least Mean Square) and NLMS (Normalized Least Mean Square) filter were observed, where as Kalman was used to compare the results. There were some variable to be varied in this simulation, namely the convergence variable, the filter length, and the SNR. Channel identification analysis is based on the estimated channel coefficients compared with channel coefficients, the convergence constant of adaptive filter, the adaptation time, the mean square errors (MSE), and the bit error rates. The results show that NLMS filter has a good performance in channel identification. LMS filter has largest mean square error in the channel identification. Kalman gives more precise results but has complex algorithm. Kalman left the least mean square error, which is 4.1e-34 at 0.16 of convergence rate. All filters have good performance on signal detection in various signal to noise ratio, especially for SNR ³ 10 dB.  Bit error rate at 10 dB SNR is 3.33e-4.