Abstract
In this paper, a blind adaptive detector is proposed for blind separation of user signals and blind estimation of spreading sequences in DS-CDMA systems. The blind separation scheme exploits a charrelation matrix for simple computation and effective extraction of information from observation signal samples. The system model of DS-CDMA signals is modeled as a blind separation framework. The unknown user information and spreading sequence of DS-CDMA systems can be estimated only from the sampled observation signals. Theoretical analysis and simulation results show that the improved performance of the proposed algorithm in comparison with the existing conventional algorithms used in DS-CDMA systems. Especially, the proposed scheme is suitable for when the number of observation samples is less and the signal to noise ratio (SNR) is low.
Highlights
The problem of blind separation in DS-CDMA systems has attracted extensive attention for the past few years [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]
The simulation parameters in DS-CDMA systems are that the number of users is four, the length of spreading code is 31, and Gold Sequence is considered as spreading code, the length of samples is set as short with 1000 bits, 10 simulations are executed, and the modulation mode is BPSK
We investigate the charrelation matrix in DS-CDMA systems for blind user separation and blind chip/speading sequence estimation
Summary
The problem of blind separation in DS-CDMA systems has attracted extensive attention for the past few years [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]. The only prior information utilized is the often soundly justified assumption of statistical independence between the source signals This technique is called as independent component analysis (ICA), which has important applications for blind separation in wireless communications [1,19,20,21,22,23,24]. Some classical ICA algorithms have been proposed to solve blind separation problems in DS-CDMA systems. The existing blind separation techniques utilize the second-order statistics (SOS) and higher-order statistics (HOS) of the observations for source separation [1]. Due to the structural simplicity and ample statistical information, we consider using the new statistics instead of the HOS statistics used in blind separation problems for DS-CDMA systems. The simulation results and discussions and concluding remarks are given in Sections 4 and 5, respectively
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