Paper Info
Title
Blind Separation of DS-CDMA Signals with ICA Method.
Abstract
The Estimation of pseudo noise sequence and information sequence is of great importance in the security of DS-CDMA system, which remains a hot research problem in reconnaissance and supervision of wireless communication. In DS-CDMA system, the pseudo noise sequences of different users are uncorrelated and the information sequences of different users are statistical independent, thus independent component analysis (ICA) could be introduced to separate the DS-CDMA signals with little prior knowledge. In multipath situations, the recovered pseudo noise sequence with ICA is overlapped. For DSCDMA signals which utilize m-sequence as pseudo noise sequence, the triple correlation function (TCF) is introduced to eliminate the influence of overlap in this paper, which increases the estimation correct ratio greatly. Under the non-cooperative conditions, it is very difficult for the interceptor to aim at the very beginning of the transmitted signal. Certain offsets between the interceptor and the transmitter deteriorate the blind separation method obviously. The relationship between none convergence and the offset is found out and explained from eigen value decomposition. The validity of the proposed method and theory analysis is proved well by the simulation results at last. © 2011 Academy Publisher.
Year
DOI
Venue
2011
10.4304/jnw.6.2.198-205
JNW
Keywords
Field
DocType
average filter,blind estimation,convergence,ds-cdma,ica,pseudo noise sequence,tcf
Multipath propagation,Convergence (routing),Transmitter,Computer science,Algorithm,Speech recognition,Independent component analysis,Eigendecomposition of a matrix,Code division multiple access,Offset (computer science),Distributed computing,Triple correlation
Journal
Volume
Issue
Citations 
6
2
0
PageRank 
References 
Authors
0.34
5
4
Name
Order
Citations
PageRank
Miao Yu100.34
Jianzhong Chen200.68
Lei Shen303.38
Shiju Li4207.40