Channel Estimation and Symbol Detection in AWGN Channel for New Structure of CDMA Signals
Sahar Naserzadeh, Mehrdad Jalali · 2011
this paper is focused on simulation of stochastic adaptive detectors of a direct sequence (DS) spread spectrum signals as a member of code-division multiplex access (CDMA). The kalman filter (KF) algorithm has shown better performance in compare of the other LMS and RLS algorithm which can be used for channel estimation and data detection. KF acted more stable in different ranges of SNR and represented the same BER. The space state model of KF is used in regard to estimating the model of MMSE. An adaptive algorithm is proposed for estimating the weight vector of multi path fading AWGN channel. In regard to improving BER, it has been trained an adaptive receiver with a long sequence of data which consists the iteration of expanded main signal. Finally, simulation was shown the different results of detecting in multi path fading AWGN channel and single AWGN channel.